(x) written inside the large circle symbolizing the neuron in Fig. 1, according to the following convention: The output of the neuron is excited at time / + 1 if and only if at time / the number of stimulated excitatory inputs k and the number of stimulated inhibitory inputs / satisfy the relation k ^ >(/). (It is reasonable to require that the function (x). For example x
(=0
^r (=oo
(1) x^h)
(i.e. < h inhibitions are absolutely ineffective, ^ h inhibitions are absolutely effective), or M) = XHM = x + h (2) (i.e. the excess of stimulations over inhibitions must be ^ h). We will use XH* and write the inhibition number h (instead of Xh) inside the large circle symbolizing the neuron. Special cases of this type are the three basic organs shown in Fig. 2. These are, respectively, a threshold two neuron with two excitato-y inputs, a threshold one neuron with two excitatory inputs, and finally a threshold one neuron with one excitatory input and one inhibitory input. The automata with one output and one input described by the networks shown in Fig. 3 have simple properties: The first one's output is never stimulated, the second one's output is stimulated at all times if its input has been ever (previously) stimulated. Rather than add these automata to a network, we shall permit lines leading to an input to be either always non-stimulated, or always stimulated. We call the latter "grounded" and designate it by the symbol 11h- and we call the former "live" and designate it by the symbol 111 h-
Fto.2
Fio. 3
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3. Automata and the Propositional Calculus 3.1. The Propositional Calculus. The propositional calculus deals with propo sitions irrespective of their truth. The set of propositions is closed under the operations of negation, conjunction and disjunction. If a is a proposition, then "not a", denoted by a~l (we prefer this designation to the more conventional ones — a and ~ a\ is also a proposition. If a, b are two propositions, then "a and Z>", "a or V\ denoted respectively by ab, a + b, are also propositions. Propo sitions fall into two sets, T and Fy depending whether they are true or false. The proposition a~x is in T if and only if a is in F. The proposition ab is in T if and only if a and b are both in T, and a + b is in T if and only if either a or b is in T. Mathematically speaking the set of propositions, closed under the three funda mental operations, is mapped by a homomorphism onto the Boolean algebra of the two elements \_ and 0. A proposition is true if and only if it is mapped onto the element L For convenience, denote by \_ the proposition a + d~\ by 0 the proposition dd~\ where a is a fixed but otherwise arbitrary proposition. Of course, 0 is false and j_ is true. A polynomial P in n variables, n ^ 1, is any formal expression obtained from xl9 . . . , x„ by applying the fundamental operations to them a finite number of times, for example [(x, + X2l)x3]~l is a polynomial. In the propositional calculus two polynomials in the same variables are considered equal if and only if for any choice of the propositions xx, . . ., xn the resulting two propositions are always either both true or both false. A fundamental theorem of the propositional calculus states that every polynomial P is equal to i, = ± l
i„=±l
where each of the/ f | in is equal to 0 or JL Two polynomials are equal if and only if their/'s are equal. In particular, for each w, there exist exactly 2 (2n) polynomials. 3.2. Propositions, Automata and Delays. These remarks enable us to describe the relationship between automata and the propositional calculus. Given a time delay 5, there exists a one-to-one correspondence between single output automata with time delay s and the polynomials of the propositional calculus. The number n of inputs (to be designated v = 1, . . . , n) is equal to the number of variables. For every combination /, = ± 1, . . . , / „ = ± 1, the coefficient fix . . . ,n = 1, if and only if a stimulation at time t of exactly those inputs v for which /v = 1, produces a stimulation of the output at time / + s. DEFINITION 2: Given a polynomial P = P(xu . . . , x„) and a time delay 5, we mean by a Py 5-network a network built from the three basic organs of Fig. 2, which as an automaton represents P with time delay s. THEOREM 1: Given any P, there exists a (unique) s* = s*(P), such that a Py j-network exists if and only if 5 ^ s*. Proof: Consider a given P. Let S(P) be the set of those s for which a Pf 5-network exists. If s' ;> 5, then tying s'-s unit-delays, as shown in Fig. 4, in series to the output of a P9 5-network produces a P9 5'-network. Hence S(P) contains with an 5 all s' ^ 5. Hence if S(P) is not empty, then it is precisely the set of all 5 ^ 5*,
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where s* = s*(P) is its smallest element. Thus the theorem holds for P if S(P) is not empty, i.e. if the existence of at least one P, 5-network (for some s\) is established.
FIG. 4
Now the proof can be effected by induction over the the number p = p(P) of symbols used in the de^nitory expression for P (counting each occurrence of each symbol separately). If p(p) = 1, then P(xl9. . ., xn) = xv (for one of the v = 1, . . ., n). The "trivial" network which obtains by breaking off all input lines other than v, and taking the input line v directly to the output, solves the problem with 5 = 0. Hence s*(P) = 0. Ifp(P)> 1, thenP = Q~lorP = QR or P = Q + R, wherep{Q),p(R) < p(P). For P = Q~l let the box [g] represent a Q, /-network, with s' = s*(Q). Then the network shown in Fig. 5 is clearly a P9 ^-network, with s = s' + 1. Hence QR or Q + R let the boxes I R represent a Q, s*(P)^s*(Q) + 1. ForP ^'-network and an R, 5*-network, respectively, with s" = Max(s*(£>), s*(R)). Then the network shown in Fig. 6 is clearly a P, j-network, with P = g P or Q + /? for /i = 2 or 1, respectively, and with s = s" + 1. Hence 5*(P) g Max(5*(0), 5*(/?) + 1).
FIG. 5
FIG. 6
Combine the above theorem with the fact that every single output automaton can be equivalently described—apart from its time delay s—by a polynomial P, and that the basic operations ab, a + b9 a'1 of the propositional calculus are represented (with unit delay) by the basic organs of Fig. 2. (For the last one, which represents ab~\ cf. the remark at the beginning of 4.1.1.) This gives: DEFINITION 3: Two single output automata are equivalent in the wider sense, if they differ only in their time delays—but otherwise the same input stimuli produce the same output stimulus (or non-stimulus) in both. THEOREM 2 (Reduction Theorem): Any single output automaton r is equivalent in the wider sense to a network of basic organs of Fig. 2. There exists a (unique) s* = s*(r)y such that the latter network exists if and only if its prescribed time delay J satisfies s > s*. 3.3. Universality. General Logical Considerations. Now networks of arbitrary single output automata can be replaced by networks of basic organs of Fig. 2: It suffices to replace the unit delay in the former system by s unit delays in the
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latter, where s is the maximum of the s*(r) of all the single output automata that occur in the former system. Then all delays that will have to be matched will be multiples of s, hence ^ 5, hence ^ s*(r) for all r that can occur in this situation, and so the Reduction Theorem will be applicable throughout. Thus this system of basic organs is universal: It permits the construction of essentially equivalent networks to any network that can be constructed from any system of single output automata. That is to say, no redefinition of the system of basic organs can extend the logical domain covered by the derived networks. The general automaton is any network of single output automata in the above sense. It must be emphasized, that, in particular, feedbacks, i.e. arrangements of lines which may allow cyclical stimulation sequences, are allowed. (That is to say, configurations like those shown in Fig. 7. There will be various, non-trivial, examples of this later.) The above arguments have shown, that a limitation of the underlying single output automata to our original basic organs causes no essential loss of generality. The question, as to which logical operations can be equivalently represented (with suitable, but not a priori specified, delays) is nevertheless not without difficulties.
FIG.
7
These general automata are, in particular, not immediately equivalent to all of effectively constructive (intuitionistic) logics. That is to say, given a problem involving (a finite number of) variables, which can be solved (identically in these variables) by effective construction, it is not always possible to construct a general automaton that will produce this solution identically (i.e. under all con ditions). The reason for this is essentially, that the memory requirements of such a problem may depend on (actual values assumed by) the variables (i.e. they must be finite for any specific system of values of the variables, but they may be unbounded for the totality of all possible systems of values), while a general automaton in the above sense necessarily has a fixed memory capacity. That is to say, a fixed general automaton can only handle (identically, i.e. gen erally) a problem with fixed (bounded) memory requirements. We need not go here into the details of this question. Very simple addenda can be introduced to provide for a (finite but) unlimited memory capacity. How this can be done has been shown by A. M. Turing [5]. Turing's analysis loc. cit. also shows, that with such addenda general automata become strictly equivalent to effectively constructive (intuitionistic) logics. Our system in its present form (i.e. general automata with limited memory capacity) is still adequate for the treatment of all problems with neurological analogies, as our subsequent examples will show. (Cf. also W. S. McCulloch and W. Pitts [2].) The exact logical domain that they cover has been recently characterized by Kleene [1]. We will return to some of these questions in 5.1.
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4. Basic Organs 4.1. Reduction of the Basic Components 4.1.1. The simplest reductions. The previous section makes clear the way in which the elementary neurons should be interpreted logically. Thus the ones shown in Fig. 2 respectively represent the logical functions aby a + b, and ab~l. In order to get b~ \ it suffices to make the a-terminal of the third organ, as shown in Fig. 8, live. This will be abbreviated in the following, as shown in Fig. 8.
FIG. l
8
Now since ab = ((a~ ) + (6 ))" and a + b = ((a~ l)(b~l))~l, it is clear that the firsi organ among the three basic organs shown in Fig. 2 is equivalent to a system built of the remaining two organs there, and that the same is true for the second organ there. Thus the fiist and second organs shown in Fig. 2 are respec tively equivalent (in the wider sense) to the two networks shown in Fig. 9. This -1
1
FIG.
9
tempts one to consider a new system, in which ° ( / (viewed as a basic entity in its own right, and not an abbreviation for a composite, as in Fig. 8), and either the first or the second basic organ in Fig. 2, are the basic organs. They permit forming the second or the first basic organ in Fig. 2, respectively, as shown above, as (composite) networks. The third basic organ in Fig. 2 is easily seen to be also equivalent (in the wider sense) to a composite of the above, but, as was observed at the beginning of 4.1.1 the necessary organ is in any case not this, but dT J (cf. also the remarks concerning Fig. 8), respectively. Thus either system ofnew basic organs permits reconstructing (as composite networks) all the (basic) organs of the original system. It is true, that these constructs have delays varying from 1 to 3, but since unit delays, as shown in Fig. 4, are available in either new system, all these delays can be brought up to the value 3. Then a trebling of the unit delay time obliterates all differences. To restate: Instead of the three original basic organs shown again in Fig. 10, we can also (essentially equivalently) use the two basic organs Nos. one and three or Nos. two and three in Fig. 10.
FIG.
10
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4.1.2. The double line trick. This result suggests strongly that one consider the one remaining combination, too: The two basic organs Nos. one and two in Fig. 10, as the basis of an essentially equivalent system. One would be inclined to infer that the answer must be negative: No network built out of the first two basic organs of Fig. 10 can be equivalent (in the wider sense) to the last one. Indeed, let us attribute to Tand F, i.e. to the stimulated or non-stimulated state of a line, respectively, the "truth values" _[ or 0, respectively. Keeping the ordering 0 < | in mind, the state of the output is a monotone nondecreasing function of the states of the inputs for both basic organs Nos. one and two in Fig. 10, and hence for all networks built from these organs exclusively as well. This, however, is not the case for the last organ of Fig. 10 (nor for the last organ of Fig. 2), irrespectively of delays. Nevertheless a slight change of the underlying definitions permits one to cir cumvent this difficulty, and to get rid of the negation (the last organ of Fig. 10) entirely. The device which effects this is of additional methodological interest, because it may be regarded as the prototype of one that we will use later on in a more complicated situation. The trick in question is to represent propositions on a double line instead of a single one. One assumes that of the two lines, at all times precisely one is stimulated. Thus there will always be two possible states of the line pair: The first line stimulated, the second non-stimulated; and the second line stimulated, the first non-stimulated. We let one of these states corres pond to the stimulated single line of the original system—that is, to a true proposition—and the other state to the unstimulated single line—that is, to a false proposition. Then the three fundamental Boolean operations can be represented by the first three schemes shown in Fig. 11. (The last scheme shown in Fig. 11 relates to the original system of Fig. 2.) In these diagrams, a true proposition corresponds to 1 stimulated, 2 unstimu lated, while a false proposition corresponds to 1 unstimulated, 2 stimulated. The networks of Fig. 11, with the exception of the third one, have also the correct delays: Unit delay. The third one has zero delay, but whenever this is not wanted, it can be replaced by unit delay, by replacing the third network by the fourth one, making its a\ line live, its a2 line grounded, and then writing a for its b. Summing up: Any two of the three (single delay) organs of Fig. 10—which may simply be designated aby a + by a~l—can be stipulated to be the basic organs, and yield a system that is essentially equivalent to the original one. 4.2. Single Basic Organs 4.2.1. The Sheffer stroke. It is even possible to reduce the number of basic organs to one, although it cannot be done with any of the three organs enumerated above. We will, however, introduce two new organs, either of which suffices by itself. The first universal organ corresponds to the well-known "Sheffer stroke" function. Its use in this context was suggested by K. A. Brueckner and G. GellMann. In symbols, it can be represented (and abbreviated) as shown on Fig. 12.
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Ob — ORGAN NO 1 OF FIGURE 2 OR 10:
ob
0 + b — ORGAN NO. 2 OF FIGURE 2 OR 10:
o+b
O"*1
ORGAN NO. 3 OF FIGURE 10 :
a"*1 ab" 1
ORGAN NO. 3 OF FIGURE 2-
ob"
Flo. 11
(o|b)
=
(at))-' :
FIG.
12
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The three fundamental Boolean operations can now be performed as shown in Fig. 13. The delays are 2, 2, 1, respectively, and in this case the complication caused by these delay-relationships is essential. Indeed, the output of the Sheffer-stroke is an antimonotone function of its inputs. Hence in every network derived from it, even-delay outputs will be monotone functions of its inputs, and odd-delay out puts will be antimonotone ones. Now ab and a + b are not antimonotone, and ab~x and a~l are not monotone. Hence no delay-value can simultaneously accom modate in this set up one of the first two organs and one of the last two organs. ab
ORGAN NO. 1 OF FIGURE
10 :
ob d+ b
ORGAN NO. 2 OF FIGURE 10: S
a+b
a" 1
ORGAN NO. 3 OF FIGURE 10:
o-' FIG. 13
The difficulty can, however, be overcome as follows: ab and a + b are repre sented in Fig. 13, both with the same delay, namely 2. Hence our earlier result (in 4.1.2), securing the adequacy of the system of the two basic organs ab and a + b applies: Doubling the unit delay time reduces the present set up (Sheffer stroke only!) to the one referred to above. 4.2.2. The majority organ. The second universal organ is the "majority organ". In symbols, it is shown (and alternatively designated) in Fig. 14. To get conjunction m(o,b.c) = o b + a c + bc = (a + b)(a+c)(b+c) :
FIG. 14
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and disjunction, is a simple matter, as shown in Fig. 15. Both delays are 1. Thus ab and a + b (according to Fig. 10) are correctly represented, and the new system (majority organ only!) is adequate because the system based on those two organs is known to be adequate (cf. 4.1.2).
ob:
a + b:
FIG. 15
5. Logics and Information 5.1. Intuitionistic Logics. All of the examples which have been described in the last two sections have had a certain property in common; in each, a stimulus of one of the inputs at the left could be traced through the machine until at a certain time later it came out as a stimulus of the output on the right. To be specific, no pulse could ever return to a neuron through which it had once passed. A system with this property is called circle-free by W. S. McCulloch and W. Pitts [2]. While the theory of circle-free machines is attractive because of its simplicity, it is not hard to see that these machines are very limited in their scope. When the assumption of no circles in the network is dropped, the situation is radically altered. In this far more complicated case, the output of the machine at any time may depend on the state of the inputs in the indefinitely remote past. For example, the simplest kind of cyclic circuit, as shown in Fig. 16, is a kind of memory machine. Once this organ has been stimulated by a, it remains stimulated and sends forth a pulse in b at all times thereafter. With more complicated net works, we can construct machines which will count, which will do simple arith metic, and which will even perform certain unlimited inductive processes. Some of these will be illustrated by examples in 6. The use of cycles or feedback in
FIG.
16
automata extends the logic of constructable machines to a large portion of intuition istic logic. Not all of intuitionistic logic is so obtained, however, since these machines are limited by their fixed size. (For this, and for the remainder of this chapter cf. also the remarks at the end of 3.3.) Yet, if our automata are furnished
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with an unlimited memory—for example, an infinite tape, and scanners connected to afferent organs, along with suitable efferent organs to perform motor operations and/or print on the tape—the logic of constructable machines becomes precisely equivalent to intuitionistic logic (see A. M. Turing [5]). In particular, all numbers computable in the sense of Turing can be computed by some such network. 5.2. Information 5.2.1. General observations. Our considerations deal with varying situations, each of which contains a certain amount of information. It is desirable to have a means of measuring that amount. In most cases of importance, this is possible. Suppose an event is one selected from a finite set of possible events. Then the number of possible events can be regarded as a measure of the information content of knowing which event occurred, provided all events are a priori equally probable. However, instead of using the number n of possible events as the measure of information, it is advantageous to use a certain function of/?, namely the logarithm. This step can be (heuristically) justified as follows: If two physical systems I and II represent n and m (a priori equally probable) alternatives, respectively, then union I + II represents nm such alternatives. Now it is desirable that the (numerical) measure of information be (numerically) additive under this (substantively) additive composition I + II. Hence some function/(/i) should be used instead of /?, such that f(nm)=f(n)+f(m)
(3)
In addition, for n > m I represents more information than II, hence it is reason able to require n>m
implies f(n)>f(m)
(4)
Note, that /(/?) is defined for n = 1 , 2 , . . . only. From (3), (4) one concludes easily, that f(n) = C In n
(5)
for some constant C > 0. (Since/(/i) is defined for n = 1, 2 , . . . only, (3) alone does not imply this, even not with a constant C § 0!). Next, it is conventional to let the minimum non-vanishing amount of information, i.e. that which corresponds to n = 2, be the unit of information—the "bit". This means that/(2) = 1, i.e. C = 1/ln 2, and so f(n) = log2 n
(6)
This concept of information was successively developed by several authors in the late 1920's and early 1930's, and finally integrated into a broader system by C. E. Shannon [3]. 5.2.2. Examples. The following simple examples give some illustration: The outcome of the flip of a coin is one bit. That of the roll of a die is log2 6 = 2.5 bits. A decimal digit represents log2 10 = 3.3. bits, a letter of the alphabet repre sents log2 26 = 4.7 bits, a single character from a 44-key, 2-setting typewriter
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represents log2(44 x 2) = 6.5 bits. (In all these we assume, for the sake of the argument, although actually unrealistically, a priori equal probability of all possible choices.) It follows that any line or nerve fibre which can be classified as either stimulated or non-stimulated carries precisely one bit of information, while a bundle of n such lines can communicate n bits. It is important to observe that this definition is possible only on the assumption that a background of a priori know ledge exists, namely, the knowledge of a system of a priori equally probable events. This definition can be generalized to the case where the possible events are not all equally probable. Suppose the events are known to have probabilities Pi*Pi* • • • >P*- Then the information contained in the knowledge of which of these events actually occurs, is defined to be
H=-tp,\oglPi
(bits)
(7)
1=1
In case p{ = p2 = .-. . = pn — 1/w, this definition is the same as the previous one. This result, too, was obtained by C. E. Shannon [3], although it is implicit in the earlier work of L. Szilard [4J. An important observation about this definition is that it bears close resemblance to the statistical definition of the entropy of a thermodynamical system. If the possible events are just the known possible states of the system with their corres ponding probabilities, then the two definitions are identical. Pursuing this, one can construct a mathematical theory of the communication of information pat terned after statistical mechanics. (See L. Szilard [4] and C. E. Shannon [3].) That information theory should thus reveal itself as an essentially thermodynamical discipline, is not at all surprising: The closeness and the nature of the connection between information and entropy is inherent in L. Boltzman's classical definition of entropy (apart from a constant, dimensional factor) as the logarithm of the "configuration number*'. The "configuration number" is the number of a priori equally probable states that are compatible with the macroscopic description of the state—i.e. it corresponds to the amount of (miscroscopic) information that is missing in the (macroscopic) description. 6. Typical Syntheses of Automata 6.1. The Memory Unit. One of the best ways to become familiar with the ideas which have been introduced, is to study some concrete examples of simple net works. This section is devoted to a consideration of a few of them. The first example will be constructed with the help of the three basic organs of Fig. 10. It is shown in Fig. 18. It is a slight refinement of the primitive memory network of Fig. 16. This network has two inputs a and b and one output x. At time /, x is stimulated if and only if a has been stimulated at an earlier time, and no stimulation of/) has occurred since then. Roughly speaking, the machine remembers whether a or b was the last input to be stimulated. Thus x is stimulated, if it has been stimulated immediately before—to be designated by x'—or if a has been stimulated immedi ately before, but b has not been stimulated immediately before. This is expressed
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by the formula x = (x' + a)b~\ i.e. by the network shown in Fig. 17. Now x should be fed back into x' (since x' is the immediately preceding state of x). This gives the network shown in Fig. 18, where this branch of JC is designated by y. However, the delay of the first network is 2, hence the second network's memory extends over past events that lie an even number of time (delay) units back. That is to say, the output x is stimulated if and only if a has been stimulated at an earlier time, an even number of units before, and no stimulation of b has occurred since then, also an even number of units before. Enumerating the time units by an integer /, it is thus seen, that this network represents a separate memory for even and for odd /. For each case it is a simple "off-on", i.e. one bit, memory. Thus it is in its entirety a two bit memory.
FIG.
17
FIG.
18
6.2. Sealers. In the examples that follow, free use will be made of the general family of basic organs considered in 2.3, at least for all = XH (cf. (2) there). The reduction thence to elementary organs in the original sense is secured by the Reduction Theorem in 3.2, and in the subsequently developed interpretations, according to section 4, by our considerations there. It is therefore unnecessary to concern ourselves here with these reductions. The second example is a machine which counts input stimuli by two's. It will be called a "sealer by two". Its diagram is shown in Fig. 19.
FIG.
19
By adding another input, the repressor, the above mechanism can be turned off at will. The diagram becomes as shown in Fig. 20. The result will be called a "sealer by two" with a repressor and denoted as indicated by Fig. 20. In order to obtain larger counts, the "sealer by two" networks can be hooked in series. Thus a "sealer by 2"" is shown in Fig. 21. The use of the repressor is of course optional here. "Sealers by w", where m is not necessarily of the form 2", can also be constructed with little difficulty, but we will not go into this here. 6.3. Learning. Using these "sealers by 2"" (i.e. /i-stage counters), it is possible to construct the following sort of "learning device". This network has two inputs
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a and b. It is designed to learn that whenever a is stimulated, then, in the next instant, b will be stimulated. If this occurs 256 times (not necessarily consecutively and possibly with many exceptions to the rule), the machine learns to anticipate a
Fio. 20
FIG. 21
pulse from b one unit of time after a has been active, and expresses this by being stimulated at its b output after every stimulation of Q. The diagram is shown in Fig. 22. (The "expression" described above will be made effective in the desired sense by the network of Fig. 24, cf. its discussion below.) This is clearly learning in the crudest and most inefficient way, only. With some effort, it is possible to refine the machine so that, first, it will learn only if it receives no counter-instances of the pattern "b follows a" during the time when it is col lecting these 256 instances; and, second, having once learned, the machine can
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unlearn by the occurrence of 64 counter-examples to "b follows a" if no (positive) instances of this pattern interrupt the (negative) series. Otherwise, the behavior is as before. The diagram is shown in Fig. 23. To make this learning effective, one has to use JC to gate a so as to replace b at its normal functions. Let these be represented by an output c. Then this process is mediated by the network shown in Fig. 24. This network must then be attached to the lines a, b and to the output x of the preceding network (according to Figs. 22, 23).
Fto. 22
FIG.
23
FIG.24
7. The Role of Error 7.1. Exemplification with the Help of the Memory Unit. In all the previous considerations, it has been assumed that the basic components were faultless in their performance. This assumption is clearly not a very realistic one. Mechanical devices as well as electrical ones are statistically subject to failure, and the same is probably true for animal neurons too. Hence it is desirable to find a closer
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approximation to reality as a basis for our constructions, and to study this revised situation. The simplest assumption concerning errors is this: With every basic organ is associated a positive number e such that in any operation, the organ will fail to function correctly with the (precise) probability e. This malfunctioning is assumed to occur statistically independently of the general state of the network and of the occurrence of other malfunctions. A more general assumption, which is a good deal more realistic, is this: The malfunctions are statistically dependent on the general state of the network and on each other. In any particular state, however, a malfunction of the basic organ in question has a probability of mal functioning which is <; e. For the present occasion, we make the first (narrower and simpler) assumption, and that with a single e: Every neuron has statistically independently of all else exactly the probability e of misfiring. Evidently, it might as well be supposed e ^ 1/2, since an organ which consistently misbehaves with a probability > 1/2, is just behaving with the negative of its attributed function, and a (complementary) probability of error < 1/2. Indeed, if the organ is thus redefined as its own opposite, its e ( > 1/2) goes then over into 1 — e ( < 1/2). In practice it will be found necessary to have e a rather small number, and one of the objectives of this investigation is to find the limits of this smallness, such that useful results can still be achieved. It is important to emphasize, that the difficulty introduced by allowing error is not so much that incorrect information will be obtained, but rather that irrelevant results will be produced. As a simple example, consider the memory organ Fig. 16. Once stimulated, this network should continue to emit pulses at all later times; but suppose it has the probability e of making an error. Suppose the organ receives a stimulation at time / and no later ones. Let the probability that the organ is still excited after s cycles be denoted ps. Then the recursion formula p s + 1 = ( 1 -E)p 5 + £(1 - p s ) is clearly satisfied. This can be written P. + i - 1/2 = ( 1 - 2 E X P , - 1 / 2 )
and so ps - 1/2 = (1 - 2eY{p0 - 1/2) ~ e" 2 "(Po - 1/2)
(8)
for small e. The quantity p s - 1/2 can be taken as a rough measure of the amount of discrimination in the system after the 5th cycle. According to the above formula, ps -♦ 1/2 as s -+ oo—a fact which is expressed by saying that, after a long time, the memory content of the machine disappears, since it tends to equal likelihood of being right or wrong, i.e. to irrelevancy. 7.2. The General Definition. This example is typical of many. In a complicated network, with long stimulus-response chains, the probability of errors in the basic organs makes the response of the final outputs unreliable, i.e. irrelevant, unless some control mechanism prevents the accumulation of these basic errors. We will consider two aspects of this problem. Let the data be these: The function which the automaton is to perform is given; a basic organ is given (Shefler stroke, for
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example); a number e ( < 1/2), which is the probability of malfunctioning of this basic organ, is prescribed. The first question is: Given S > 0, can a corresponding automaton be constructed from the given organs, which will perform the desired function and will commit an error (in the final result, i.e. output) with probability ^ <5? How small can S be prescribed? The second question is: Are there other ways to interpret the problem which will allow us to improve the accuracy of the result? 7.3. An Apparent Limitation. In partial answer to the first question, we notice now that <5, the prescribed maximum allowable (final) error of the machine, must not be less than c. For any output of the automaton is the immediate result of the operation of a single final neuron and the reliability of the whole system cannot be better.than the reliability of this last neuron. 7.4. The Multiple Line Trick. In answer to the second question, a method will be analyzed by which this threshold restriction S ^ e can be removed. In fact we will be able to prescribe S arbitrarily small (for suitable, but fixed, e). The trick consists in carrying all the messages simultaneously on a bundle of N lines (N is a large integer) instead of just a single or double strand as in the automata described up to now. An automaton would then be represented by a black box with several bundles of inputs and outputs, as shown in Fig. 25. Instead of requiring that all
FIG. 25
or none of the lines of the bundle be stimulated, a certain critical (or fiduciary) level A is set: 0 < A < 1/2. The stimulation of ^ (1 - £)N lines of a bundle is interpreted as a positive state of the bundle. The stimulation of g A7V lines is considered as a negative state. All levels of stimulation between these values are intermediate or undecided. It will be shown that by suitably constructing the automaton, the number of lines deviating from the "correctly functioning" majori ties of their bundles can be kept at or below the critical level AN (with arbitrarily high probability). Such a system of construction is referred to as "multiplexing". Before turning to the multiplexed automata, however, it is well to consider the ways in which error can be controlled in our customary single line networks. 8. Control of Error in Single Line Automata 8.1. The Simplified Probability Assumption. In 7.3 it was indicated that when dealing with an automaton in which messages are carried on a single (or even a double) line, and in which the components have a definite probability e of making an error, there is a lower bound to the accuracy of the operation of the machine. It will now be shown that it is nevertheless possible to keep the accuracy within reasonable bounds by suitably designing the network. For the sake of simplicity
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only circle-free automata (cf. 5.1) will be considered in this section, although the conclusions could be extended, with proper safeguards, to all automata. Of the various essentially equivalent systems of basic organs (cf. section 4) it is, in the present instance, most convenient to select the majority organ, which is shown in Fig. 14, as the basic organ for our networks. The number e (0 < e < 1/2) will denote the probabability each majority organ has for malfunctioning. 8.2. The Majority Organ. We first investigate upper bounds for the probability of errors as impulses pass through a single majority organ of a network. Three lines constitute the inputs of the majority organ. They come from other organs or are external inputs of the network. Let rju rj2t Hi be three numbers (0 < r/, g 1), which are respectively upper bounds for the probabilities that these lines will t*e carrying the wrong impulses. Then e + rjt + v\2 + *fa ls a n upper bound for the probability that the output line of the majority organ will act improperly. This upper bound is valid in all cases. Under proper circumstances it can be improved. In particular, assume: (i) The probabilities of errors in the input lines are inde pendent, (ii) under proper functioning of the network, these lines should always be in the same state of excitation (either all stimulated, or all unstimulated). In this latter case 0 = fhi/2 + M 3 + ri2rj3 - 2>h>72>/3
is an upper bound for at least two of the input lines carrying the wrong impulses, and thence £'
= (l - e)0 + e(l - 0) = £ + (1 - 2e)0
is a smaller upper bound for the probability of failure in the output line. If all r\i ^r\y then e + 3rj is a general upper bound, and £ + (1 - 2£X3fj2 - 2r?) ^ £ + 3rj2 is an upper bound for the special case. Thus it appears that in the general case each operation of the automaton increases the probability of error, since £ + 3rj > r\y so that if the serial depth of the machine (or rather of the process to be performed) is very great, it will be impractical or impossible to obtain any kind of-accuracy. In the special case, on the other hand, this is not necessarily so—e + 3//2 < rj is possible. Hence, the chance of keeping the error under control lies in maintaining the conditions of the special case throughout the construction. We will now exhibit a method which achieves this. 8.3. Synthesis of Automata 8.3.1. The heuristic argument. The basic idea in this procedure is very simple. Instead of running the incoming data into a single machine, the same information is simultaneously fed into a number of identical machines, and the result that comes out of a majority of these machines is assumed to be true. It must be shown that this technique can really be used to control error.
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Denote by O the given network (assume two outputs in the specific instance picture in Fig. 26). Construct O in triplicate, labelling the copies, 0 \ O2, O 3 respectively. Consider the system shown in Fig. 26.
FIG. 26
For each of the final majority organs the conditions of the special case con sidered above obtain. Consequently, if r\ is an upper bound for the probability of error at any output of the original network O, then i f - e + O - 2eK3^2 - 2rj3) =/JLri)
(9)
is an upper bound for the probability of error at any output of the new network O*. The graph is the curve rj* = fe(rj), shown in Fig. 27. Consider the intersections of the curve with the diagonal rj* = JJ: First, r\ = 1/2 is at any rate such an intersection. Dividing rj — ft(r\) by rj — 1/2 gives 2 ( ( l - 2 € > / 2 - ( l - 2 € > 7 + £), hence the other intersections are the roots of (1 — 2e)r}2 — (1 — 2e)rj + c = 0, i.e.
<-\H<m
That is to say, for e ^ 1/6 they do not exist (being complex (for 6 > 1/6) or = 1/2 (for e = 1/6)); while for e < 1/6 they are r\ = r\Qy I — rj0t where
*-kH(m-**-
(10)
For r\ = 0; rj* = e > rj. This, and the monotony and continuity of r\* = ft(r\) therefore imply: First case, e ^ 1/6: 0 ^ r) < 1/2 implies rj < r\* < 1/2; 1/2 < v\ ^ 1 implies 1/2 \/2 < rj < \ - q0 implies r\ < r\* < 1 - r)0\ 1 - rj0 < q < 1 implies 1 — r\0 < r\* < rj. Now we must expect numerous successive occurrences of the situation under consideration, if it is to be used as a basic procedure. Hence the iterative behaviour of the operation r\ -► r\* — Jt(rj) is relevant. Now it is clear from the above, that in the first case the successive iterates of the process in question always converge to 1/2, no matter what the original r\\ while in the second case these iterates con verge to r\Q if the original ^ < 1/2, and to 1 - rj0 if the original r\ > 1/2.
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In other words: In the first case no error level other than rj ~ 1/2 can maintain itself in the long run. That is to say, the process asymptotically degenerates to total irrelevance, like the one discussed in 7.1. In the second case the error-levels ry ~ rjo a n d *\ ~ 1 _ 1o w i , l n o t o n , v maintain themselves in the long run, but they represent the asymptotic behaviour for any original rj < 1/2 or rj > 1/2, re spectively. These arguments, although heuristic, make it clear that the second case alone can be used for the desired error-level control. That is to say, we must require 6 < 1/6, i.e. the error-level for a single basic organ function must be less than ~16 per cent. The stable, ultimate error-level should then be rj0 (we postulate, of course, that the start be made with an error-level r\ < 1/2). rj0 is small if e is, hence e must be small, and so *1o ■■
£ + 3fi2 + . . .
(11)
This would therefore give an ultimate error-level of ~ 10 per cent (i.e. tj0 ~ 0.1). for a single basic organ function error-level of ~ 8 per cent (i.e. e ~ 0.08).
FIG.
27
8.3.2. The rigorous argument—To make this heuristic argument binding, it would be necessary to construct an error controlling network P* for any given network P, so that all basic organs in P* are so connected as to put them into the special case for a majority organ, as discussed above. This will not be uniformly possible, and it will therefore be necessary to modify the above heuristic argument, although its general pattern will be maintained. It is, then desired, to find for any given network P an essentially equivalent net work />*, which is error-safe in some suitable sense, that conforms with the ideas expressed so far. We will define this as meaning, that for each output line of P* (corresponding to one of P) the (separate) probability of an incorrect message (over this line) is ^ t]x. The value of r\x will result from the subsequent discussion. The construction will be an induction over the longest serial chain of basic organs in P, say \i = \i(P\ Consider the structure of/*. The number of its inputs / and outputs a is arbitrary, but every output of P must either come from a basic organ in P, or directly from an input, or from a ground or live source. Omit the first mentioned basic organs from P, as well as the outputs other than the first mentioned ones, and designate
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the network that is left over by Q. This is schematically shown in Fig. 28. (Some of the apparently separate outputs of Q may be split lines coming from a single one, but this is irrelevant for what follows.)
FIG. 28
If Q is void, then there is nothing to prove; let therefore Q be non-void. Then clearly/i(0 = p(P) - 1. Hence the induction permits us to assume the existence of a network Q* which is essentially equivalent to Q> and has for each output a (separate) error-probability We now provide three copies of Q*: Q*\ Q*2, g* 3 , and construct P* as shown in Fig. 29. (Instead of drawing the, rather complicated, connections across the two dotted areas, they are indicated by attaching identical markings to endings that should be connected.) Now the (separate) output error-probabilities of Q* are (by inductive assump tion) ^ >/,. The majority organs in the first column in the above figure (those with out a □ ) are so connected as to belong into the special case for a majority organ (cf. 8.2), hence their outputs have (separate) error-probabilities :g ft(r]x). The majority organs in the second column in the above figure (those with a □ ) are in the general case, hence their (separate) error-probabilities are ^ e + 3£(iy,). Consequently the inductive step succeeds, and therefore the attempted inductive proof is binding, if « + 3/^if t ) g ift
(12)
8.4. Numerical Evaluation. Substituting the expression (9) for fe(rj) into condition (12) gives 4£4-3(l-2£X3^12-2^13)^»y1 i.e.
*'-*>1+W^)'1-*£*)** Clearly the smallest r\x > 0 fulfilling this condition is wanted. Since the left hand side is < 0 for rjl ^ 0, this means the smallest (real, and hence, by the above, positive) root of
" , - * " a + 6(1^) " ' - 3 0 ^ = °
(,3)
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a
i
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We know from the preceding heuristic argument, that e g 1/6 will be necessary— but actually even more must be required. Indeed, for nx = 1/2 the left hand side of (13) is = - ( 1 + e)/(6 - 12E) < 0, hence a significant and acceptable r\x (i.e. an r}x < 1/2), can be obtained from (13) only if it has three real roots. A simple calculation shows, that for e = 1/6 only one real root exists iy, = 1.425. Hence the limiting e calls for the existence of a double root. Further calculation shows, that the double root in question occurs for e = 0.0073, and that its value is r\x = 0.060. Consequently <■ < 0.0073 is the actual requirement, i.e. the errorlevel of a single basic organ function must be < 0.73 percent. The stable, ultimate error-level is then the smallest positive root rjx of (13). v\x is small if a is, hence e must be small, and so (from (13)) //, = 4 f i + 152c2 + . . .
It is easily seen, that e.g. an ultimate error level of 2 per cent (i.e. nx = 0.02) calls for a single basic organ function error-level of 0.41 per cent (i.e. e = 0.0041). This result shows that errors can be controlled. But the method of construction used in the proof about threefolds the number of basic organs in P* for an increase of n(P) by 1, hence P* has to contain about 3' |(F) such organs. Consequently the procedure is impractical. The restriction to £ < 0.0073 has no absolute significance. It could be relaxed by iterating the process of triplication at each step. The inequality e < 1/6 is essential, however, since our first argument showed, that for e ^ 1/6 even for a basic organ in the most favourable situation (namely in the "special" one) no interval of improvement exists. 9. The Technique of Multiplexing 9.1. General Remarks on Multiplexing. The general process of multiplexing in order to control error was already referred to in 7.4. The messages are carried on Nlines. A positive number A(< 1/2) is chosen and the stimulation of ^ (1 — A)N lines of the bundle is interpreted as a positive message, the stimulation of ^ AN lines as a negative message. Any other number of stimulated lines is interpreted as malfunction. The complete system must be organized in such a manner, that a malfunction of the whole automaton cannot be caused by the malfunctioning of a single component, or of a small number of components, but only by the mal functioning of a large number of them. As we will see later, the probability of such occurrences can be made arbitrarily small provided the number of lines in each bundle is made sufficiently great. All of section 9 will be devoted to a descrip tion of the method of constructing multiplexed automata and its discussion, with out considering the possibility of error in the basic components. In section 10 we will then introduce errors in the basic components, and estimate their effects. 9.2. The Majority Organ 9.2.1. 77ie basic executive organ. The first thing to consider is the method of constructing networks which will perform the tasks of the basic organs for bundles of inputs and outputs instead of single lines.
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A simple example will make the process clear. Consider the problem of con structing the analog of the majority organ which will accommodate bundles of five lines. This is easily done using the ordinary majority organ of Fig. 12, as shown in Fig. 30. (The connections are replaced by suitable markings, in the same way as in Fig. 29.)
FIG. 30
9.2.2. The need for a restoring organ. It is intuitively clear that if almost all lines of two of the input bundles are stimulated, then almost all lines of the output bundle will be stimulated. Similarly if almost none of the lines of two of the input bundles are stimulated, then the mechanism will stimulate almost none of its output lines. However, another fact is brought to light. Suppose that a critical level A — 1/5 is set for the bundles. Then if two of the input bundles have 4 lines stimulated while the other has none, the output may have only 3 lines stimulated. The same effect prevails in the negative case. If two bundles have just one input each stimulated, while the third bundle has all of its inputs stimulated, then the resulting output may be the stimulation of two lines. In other words, the relative number of lines in the bundle, which are not in the majority state, can double in passing through the generalized majority system. A more careful analysis (similar to the one that will be considered in more detail for the case of the ShefTer organ in section 10) shows the following: If, in some situation, the operation of the organ should be governed by a two-to-one majority of the input bundles (i.e. if two of these bundles are both prevalently stimulated or both prevalently nonstimulated, while the third one is in the opposite condition), then the most probable level of the output error will be (approximately) the sum of the errors in the two governing input bundles; on the other hand, in an operation in which the organ is governed by a unanimous behavior of its input bundles (i.e. if all three of these bundles are prevalently stimulated or all three are prevalently non-stimulated), then the output error will generally be smaller than the (maximum of the) input errors. Thus in the significant case of two-to-one majorization, two significant inputs may combine to produce a result lying in the intermediate region of un certain information. What is needed therefore, is a new type of organ which will restore the original stimulation level. In other words, we need a network having the property that, with a fairly high degree of probability, it transforms an input bundle with a stimulation level which is near to zero or to one into an output bundle with stimulation level which is even closer to the corresponding extreme.
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Thus the multiplexed systems must contain two types of organs. The first type is the executive organ which performs the desired basic operations on the bundles. The second type is an organ which restores the stimulation level of the bundles, and hence erases the degradation caused by the executive organs. This situation has its analog in many of the real automata which perform logically complicated tasks. For example in electrical circuits, some of the vacuum tubes perform executive functions, such as detection or rectification or gateing or coincidencesensing, while the remainder are assigned the task of amplification, which is a restorative operation. 9.2.3. The restoring organ 9.2.3.1. Construction. The construction of a restoring organ is quite simple in principle, and in fact contained in the second remark made in 9.2.2. In a crude way, the ordinary majority organ already performs this task. Indeed in the simplest case, for a bundle of three lines, the majority organ has precisely the right charac teristics: It suppresses a single incoming impulse as well as a single incoming non-impulse, i.e. it amplifies the prevalence of the presence as well as of the absence of impulses. To display this trait most clearly, it sufficies to split its output line into three lines, as shown in Fig. 31.
FIG.
31
Now for large bundles, in the sense of the remark referred to above, concerning the reduction of errors in the case of a response induced by a unanimous behavior of the input bundles, it is possible to connect up majority organs in parallel and thereby produce the desired restoration. However, it is necessary to assume that the stimulated (or non-stimulated) lines are distributed at random in the bundle. This randomness must then be maintained at all times. The principle is illustrated by Fig. 32. The "black box" U is supposed to permute the lines of the input bundle that pass through it, so as to restore the randomness of the pulses in its lines. This is necessary, since to the left of U the input bundle consists of a set of triads, where the lines of each triad originate in the splitting of a single line, and hence are always all three in the same condition. Yet, to the right of U the lines of the corresponding triad must be statistically independent, in order to permit the application of the statistical formula to be given below for the functioning of the majority organ into which they feed. The way to select such a "randomizing" permutation will not be considered here—it is intuitively plausible that most "complicated" permutations will be suited for this "randomizing" role. (Cf. 11.2.) 9.2.3.2. Numerical evaluation. If OLN of the N incoming lines are stimulated, then the probability of any majority organ being stimulated (by two or three stimulated inputs) is a* = 3a2 - 2a3 = 0(a)
(14)
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Thus approximately (i.e. with high probability, provided N is large) a*N outputs will be excited. Plotting the curve if a* against a, as shown in Fig. 33, indicates clearly that this organ will have the desired characteristics: This curve intersects the diagonal a* = a three times: For a = 0, 1/2, 1. 0 < a < 1/2 implies 0 < a* < a; 1/2 < a < 1 implies a < a* < 1. That is to say successive iterates of this process converge to 0 if the original a < 1/2 and to 1 if the original a > 1/2. In other words: The error levels a ~ 0 and a ~ 1 will not only maintain them selves in the long run, but they represent the asymptotic behavior for any original a < 1/2 or a > 1/2, respectively. Note, that because of #(1 - a) = 1 - ^(a) there is complete symmetry between the a < 1/2 region and the a > 1/2 region.
FIG.
32
FIG.
33
The process a -► a* thus brings every a nearer to that one of 0 and 1, to which it was nearer originally. This is precisely that process of restoration, which was seen in 9.2.2 to be necessary. That is to say one or more (successive) applications of this process will have the required restoring effect. Note, that this process of restoration is most effective when a — a* = 2a 3 — 3a2 + a has its minimum or maximum, i.e. for 6a2 - 6a + 1 = 0,
i.e. for
a = (3 ± V3)/6 = 0.788, 0.212
Then a — a* = +0.096. That is to say the maximum restoration is effected on error levels at the distance of 21.2 per cent from 0 per cent or 100 per cent—these are improved (brought nearer) by 9.6 per cent. 9.3. Other Basic Organs. We have so far assumed that the basic components of the construction are majority organs. From these, an analog of the majority organ —one which picked out a majority of bundles instead of a majority of single lines— was constructed. Since this, when viewed as a basic organ, is a universal organ, these considerations show that it is at least theoretically possible to construct any network with bundles instead of single lines. However there was no necessity for starting from majority organs. Indeed, any other basic system whose universality was established in section 4 can be used instead. The simplest procedure in such a case is to construct an (essential) equivalent of the (single line) majority organ from the given basic system (cf. 4.2.2), and then proceed with this composite majority organ in the same way, as was done above with the basic majority organ.
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Thus, if the basic organs are those Nos. one and two in Fig. 10 (cf. the relevant discussion in 4.1.2), then the basic synthesis (that of the majority organ, cf. above) is immediately derivable from the introductory formula of Fig. 14. 9.4. The Sheffer Stroke 9.4.1. The executive organ. Similarly, it is possible to construct the entire mechanism starting from the Sheffer organ of Fig. 12. In this case, however, it is simpler not to effect the passage to an (essential) equivalent of the majority organ (as suggested above), but to start de novo. Actually, the same procedure, which was seen above, to work for the majority organ, works mutatis mutandis for the Sheffer organ, too. A brief description of the direct procedure in this case is given in what follows: Again, one begins by constructing a network which will perform the task of the Sheffer organ for bundles of inputs and outputs instead of single lines. This is shown in Fig. 34 for bundles of five wires. (The connections are replaced by suitable markings, as in Figs. 29 and 30.)
FIG. 34
It is intuitively clear that if almost all lines of both input bundles are stimulated, then almost none of the lines of the output bundle will be stimulated. Similarly, if almost none of the lines of one input bundle are stimulated, then almost all lines of the output bundle will be stimulated. In addition to this overall behavior, the following detailed behavior is found (cf. the detailed consideration in 10.4). If the condition of the organ is one of prevalent non-stimulation of the output bundle, and hence is governed by (prevalent stimulation of) both input bundles, then the most probable level of the output error will be (approximately) the sum of the errors in the two governing input bundles; if on the other hand the condition of the organ is one of prevalent stimulation of the output bundle, and hence is governed by (prevalent non-stimulation of) one or of both input bundles, then the output error will be on (approximately) the same level as the input error, if (only) one input bundle is governing (i.e. prevalently non-stimulated), and it will be generally smaller than the input error, if both input bundles were govening (i.e. prevalently non-stimulated). Thus two significant inputs may produce a result lying in the intermediate zone of uncertain information. Hence a restoring organ (for the error level) is again needed, in addition to the executive organ.
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9.4.2. The restoring organ. Again, the above indicates that the restoring organ can be obtained from a special case functioning of the standard executive organ, namely by obtaining all inputs from a single input bundle, and seeing to it that the output bundle has the same size as the original input bundle. The principle is illustrated by Fig. 35. The "black box" U is again supposed to effect a suitable
FIG.
35
permutation of the lines that pass through it, for the same reasons and in the same manner as in the corresponding situation for the majority organ (cf. Fig. 32). That is to say it must have a "randomizing" effect. If <*N of the AT incoming lines are stimulated, then the probability of any Sheffer organ being stimulated (by at least one non-stimulated input) is a + = 1 - a2 = h(a)
(15) +
Thus approximately (i.e. with high probability provided N is large) ~ a N outputs will be excited. Plotting the curve of a + against a discloses some character istic differences against the previous case (that one of the majority organs, i.e. a* = 3a2 — 2a3 = #(a), cf. 9.2.3), which require further discussion. This curve is shown in Fig. 36. Clearly a + is an antimonotone function of a, i.e. instead of
FIG.
36
restoring an excitation level (i.e. bringing it closer to 0 or to 1, respectively), it transforms it into its opposite (i.e. it brings the neighborhood of 0 close to 1, and the neighborhood of 1 close to 0). In addition it produces for a near to 1 an <x+ less near to 0 (about twice farther), but for a near to 0 an a + much nearer to 1 (second order!). All these circumstances suggest, that the operation should be iterated. Let the restoring organ therefore consist of two of the previously pictured organs
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in scries, as shown in Fig. 37. (The "black boxes" Uu U2 play the same role as their analog U plays in Fig. 35.) This organ transforms an input excitation level <xN into an output excitation level of approximately (cf. above) ~ a + + where a + + = 1 - (1 - a 2 ) 2 = h(h(a)) = Jc(a) i.e. a + + = 2a2 - a 4 =/c(a)
(16)
++
This curve of a against a is shown in Fig. 38. This curve is very similar to that one obtained for the majority organ (i.e. a* = 3a2 - 2a3 = g(a), cf. 9.2.3). Indeed: The curve intersects the diagonal a + + = a in the interval 0 ^ a ^ 1 three times: For a = 0, o^, 1, where a0 = ( - 1 + ^/5)/2 = 0.618. (There is a fourth intersection a = - 1 - a0 = -1.618, but this is irrelevant, since it is not in the interval 0 ^ a <; 1.) 0 < a < oc0 implies 0 < a + + < a; a0 < a < 1 implies a < a + + < 1.
FIG.
37
FIG.
38
In other words: The role of the error levels a ~ 0 and a ~ 1 is precisely the same as for the majority organ (cf. 9.2.3), except that the limit between their respective areas of control lies at a = OQ instead of at a = 1/2. That is to say the process a -► a + + brings every a nearer to either 0 or to 1, but the preference to 0 or to 1 is settled at a discrimination level of 61.8 per cent (i.e. <x0) instead of one of 50 per cent (i.e. 1/2). Thus, apart from a certain asymmetric distortion, the organ behaves like its counterpart considered for the majority organ—i.e. it is an effective restoring mechanism. 10. Error in Multiplex Systems 10.1. General Remarks. In section 9 the technique for constructing multiplexed automata was described. However, the role of errors entered at best intuitively and summarily, and therefore it has still not been proved that these systems will do what is claimed for them—namely control error. Section 10 is devoted to a
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sketch of the statistical analysis necessary to show that, by using large enough bundles of lines, any desired degree of accuracy (i.e. as small a probability of mal function of the ultimate output of the network as desired) can be obtained with a multiplexed automaton. For simplicity, we will only consider automata which are constructed from the Sheffer organs. These are easier to analyze since they involve only two inputs. At the same time, the Sheffer organ is (by itself) universal (cf. 4.2.1), hence every automaton is essentially equivalent to a network of Sheffer organs. Errors in the operation of an automaton arise from two sources. First, the individual basic organs can make mistakes. It will be assumed as before, that, under any circumstance, the probability of this happening is just e. Any operation on the bundle can be considered as a random sampling of size TV (N being the size of the bundle). The number of errors committed by the individual basic organs in any operation on the bundle is then a random variable, distributed approximately normally with mean eN and standard deviation ^[£(1 — e)N]. A second source of failures arises because in operating with bundles which are not all in the same state of stimulation or non-stimulation, the possibility of multiplying error by unfortunate combinations of lines into the basic (single line) organs is always present. This interacts with the statistical effects, and in particular with the processes of degeneration and of restoration of which we spoke in 9.2.2, 9.2.3 and 9.4.2. 10.2. The Distribution of the Response Set Size 10.2.1. Exact theory. In order to give a statistical treatment of the problem consider the Fig. 34, showing a network of Sheffer organs, which was discussed in 9:4.1. Again let N be the number of lines in each (input or output) bundle. Let X be the set of those / = 1, . . ., N for which line No. / in thefirstinput bundle is stimulated at time /; let Y be the corresponding set for the second input bundle and time /; and let Z be the corresponding set for the output bundle, assuming the correct functioning of all the Sheffer organs involved, and time / + 1. Let X, Y have £N, r]N elements, respectively, but otherwise be random—i.e. equidistributed over all pairs of sets with these numbers of elements. What can then be said about the number of elements (,N of Z? Clearly <J, rj, (, are the relative levels of excitation of the two input bundles and of the output bundle, respectively, of the network under consideration. The question is then: What is the distribution of the (stochastic) variable ( in terms of the (given) <J, r\ ? Let W be the complementary set of Z. Let p, q, r be the numbers of elements of X, Yy Wy respectively, so that />.= {JV, q = r\Nt r = (1 - QN. Then the problem is to determine the distribution of the (stochastic) variable r in terms of the (given) p, q—i.e. the probability of any given r in combination with any given pt q. W is clearly the intersection of the sets X, Y: W = X- Y. Let U, V be. the (relative) complements of W in Xy Yt respectively: U = X - Wt V = Y - W, and let S be the (absolute, i.e. in the set ( 1 , . . . , N)) complement of the sum of X and Y: S = -(X 4- Y). Then W, U, V, S are pairwise disjoint sets making
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up together precisely the entire set ( 1 , . . . , TV), with r, /? — ryq - r, N — p — q + r elements, respectively. Apart from this they are unrestricted. Thus they offer together N\l[r\(p — r)\(q — r)\(N — p — q + r) ! ] possible choices. Since there are a priori N\/[p \(N — p)\] possible choices of an X with p elements and a priori N! f[q \(N - q)\] possible choices of a y with q elements, this means that the required probability of W having r elements is _ / P
/
N\
~ \r\(p-r)\{q-r)\(N-p-q
AM
AM
X
+ r)\ / p\(N - p)\ q\(N - q)\J p!(N-p)!g!(N-g)! r\(p - r)\(q - r)!(N - p - q + r)\N\
Note, that this formula also shows that p = 0 when r < 0 or p - r < 0 or q — r<0orN — p — q + r<0, i.e. when r violates the conditions Max(0, p + q-N)?Zr^
Min(p, q)
This is clear combinatorially, in view of the meaning of X, Y and W. In terms of f, rjt C the above conditions become 1 - Max(0, { + » | - l ) ^ C ^ l - Min({, r/)
(17)
Returning to the expression for py substituting the <J, rjt £ expressions for pf qy r and using Stirling's formula for the factorials involved, gives
(18
f>~-4hs~°"> 7(271 N)
where =
"
>
«i-{>Ki->») «i-{¥i-i)
0 = (C + i - Dln(C + « - ! ) + « + * - l)ln({ + n - 1) + (1 - C)ln(l - 0 + ( 2 - { - i » - C)ln(2 - « - r, - Q - { In { - (1 - 01n(l - O - i f l n i f - d - »j)ln(l - if) From this <W dC d20
2
n
(C + t - IXC + if - 1) (l - CX2 - C - 1 , - 0 l
+
l
+
l
ac "c + f - i c + »»-i i-c
+
l
2-{-»,-c
Hence 0 = 0, dO/dt; = 0 for C = 1 - ff, and 520/dC2 > 0 for all C (in its entire interval of variability according to (17)). Consequently 0 > 0 for all f / 1 — £i\ (within the interval (17)). This implies, in view of (18) that for all C which are
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significantly # 1 - {*/, p tends to 0 very rapidly as TV gets large. It suffices there fore to evaluate (18) for C ~ 1 - fr. Now a = 1/K(1 - {>/(l - >/)}, d20/dt2 = 1/[{(1 - { M l - >/)] for C = 1 - ft. Hence 1
" ~ «i - (Mi - n) (C-q-fr?)) 2 ~ 2«i - C>KI - tr) for £ ~ 1 — f'/- Therefore
i
r (C —
" ~ 7(2^(1 - mx - nw hm - «wi - «f) J
no,
( }
is an acceptable approximation for p. r is an integer-valued variable, hence { = 1 — r/TV is a rational-valued variable, with the fixed denominator TV. Since TV is assumed to be very large, the range of ( is very dense. It is therefore permissible to replace it by a continuous one, and to describe the distribution of { by a probability-density a. p is the probability of a single value of {, and since the values of { are equidistant, with a separation df = 1/TV, the relation between a and p is best defined by ad{ = p, i.e. a = pN. Therefore (19) becomes
r i/ c-(i-fa) \21 * ~ V ( 2 * V « a - 0»Ki - *)/A0 CXPL 2 V « ( i - {>/(i - n)IN)J J i
70)
This formula means obviously the following: C is approximately normally distributed, with the mean 1 — {*/ and the dis persion yJ[Z(\ - {>/(l - q)/N]. Note, that the rapid decrease of the normal distribution function (i.e. the right hand side of (20)) with TV (which is exponential!) is valid as long as C is near to 1 - {>/, only the coefficient of TV (in the exponent, i.e. - i { K - 0 - £?)]/VK0 - On0 - n)/N]}2 is somewhat altered as { deviates from 1 — {. (This follows from the discussion of 0 given above.) The simple statistical discussion of 9.4 amounted to attributing to f the unique value 1 — {//. We see now that this is approximately true: C = (l - {II) + V[{(i - { M l - !,)/*]*, , S is a stochastic variable, normally distributed, with the mean 0 and the dispersion 1. j
(21)
10.2.2. Theory with errors. We must now pass from r, {, which postulate fault less functioning of all Sheffer organs in the network, to r\ {' which correspond to the actual functioning of all these organs—i.e. to a probability e of error on each functioning. Among the r organs each of which should correctly stimulate its output, each error reduces r' by one unit. The number of errors here is approxi mately normally distributed, with the mean er and the dispersion J[e(\ - e)r] (cf. the remark made in 10.1). Among the TV - «• organs, each of which should
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correctly not stimulate its output, each error increases r' by one unit. The number of errors here is again approximately normally distributed, with the mean e(N — r), and the dispersion yj[e(\ - e)(N - r)]
VWOO - «)r]2 + VWi - <0(N - »-)32} = VOO - «)^] That is to say (approximately) r' = r + 2e(^ - r) + V[e(l - «)N]*' where <5' is normally distributed, with the mean 0 and the dispersion 1. From this C = C + 2e(i - 0 ~ VM1 - s)/N]*\ and then by (21) C = (1 - «if) + 2«(€f| - » + (1 - 2eVK(l - {>K1 - if)/N]* - VW1 - «)/*]*' Clearly (1 - 2)e > /K(l - OfO - *)/#]$ - V[e(l - £)/AT]<5', too, is normally distributed, with the mean 0 and the dispersion V[{(1 - 2£)V[«1 - {>K1 - >/)/N]}2 + {V[ £ (l - e)/N]} 2 ] = V{[(1 - 2£)2{(1 -.{>K1 - if) + £(1 - «)]/N}. Hence (21) becomes at last (we write again ( in place of ('): C - (1 - iff) + 2«CCif - *) + V([(l - 2£)2{(1 - OKI - if) + «(1 - «)]/N}** ] 3* is a stochastic variable, normally distributed, with the mean 0 and the J (22) dispersion 1. j 10.3. The Restoring Organ. This discussion equally covers the situations that are dealt with in Figs. 35 and 37, showing networks of Sheffer organs in 9.4.2. Consider first Fig. 35. We have here a single input bundle of N lines, and an output bundle of N lines. However, the two-way split and the subsequent "ran domizing" permutation produce an input bundle of IN lines and (to the right of U) the even lines of this bundle on one hand, and its odd lines on the other hand, may be viewed as two input bundles of TV lines each. Beyond this point the net work is the same as that one of Fig. 34, discussed in 9.4.1. If the original input bundle had £N stimulated lines, then each one of the two derived input bundles will also have £N stimulated lines. (To be sure of this, it is necessary to choose the "randomizing" permutation U of Fig. 35 in such a manner, that it permutes the even lines among each other, and the odd lines among each other. This is compatible with its "randomizing" the relationship of the family of all even lines to the family of all odd lines. Hence it is reasonable to expect, that this requirement does not conflict with the desired "randomizing" character of the permutation.)
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Let the output bundle have CW stimulated lines. Then we are clearly dealing with the same case as in (22), except that it is specialized to £ = n. Hence (22) becomes: C = (1 - {2) + 2e(e - i ) + V{[(1 - 2e)2(Z(\ - « ) 2 + a(l - s)]/N}<5* \ 3* is a stochastic variable, normally distributed, with the mean 0 and J the dispersion 1. j
(23)
Consider next Fig. 37. Three bundles are relevant here: The input bundle at the extreme left, the intermediate bundle issuing directly from the first tier of Sheffer organs, and the output bundle, issuing directly from the second tier of Sheffer organs, i.e. at the extreme right. Each one of these three bundles consists of TV lines. Let the number of stimulated lines in each bundle be £#, toN, \j/N, respectively. Then (23) above applies, with its {, C replaced first by (, co, and second by co, ip: co = (1 - C2) + 2E(C2 - i) + V{[(1 - 28)2(«1 - 0 ) 2 + «U - e)]IN}6**
)
+ = (1 - co2) + 2E(CO2 - i) + V{(1 - 2E)2[(CO(1 - co))2 + €(1 - e)-]IN}3***
S**y S*** are stochastic variables, independently and normally distributed, j with the mean 0 and the dispersion 1. J 10.4. Qualitative Evaluation of the Results. In what follows, (22) and (24) will be relevant—i.e. the Sheffer organ networks of Figs. 34 and 37. Before going into these considerations, however, we have to make an obser vation concerning (22). (22) shows that the (relative) excitation levels, {, n on the input bundles of its network generate approximately (i.e. for large TV and small e) the (relative) excitation level Co = 1 — £rj on the output bundle of that network. This justifies the statements made in 9.4.1. about the detailed functioning of the network. Indeed: If the two input bundles are both prevalently stimulated, i.e. if C ~ 1, r\ ~ 1 then the distance of Co from 0 is about the sum of the distances of £ and of rj from 1: Co = 0 - {) + f(l - rj). If one of the two input bundles, say the first one, is prevalently non-stimulated, while the other one is prevalently stimulated, i.e. if ^ ~ 0, rj ~ 1, then the distance of C0 from 1 is about the distance of <J from 0: 1 - Co = ff- If both input bundles are prevalently non-stimulated, i.e. if £ ~ 0, r\ ~ 0, then the distance of Co from 1 is small compared to the dis tances of both ^ and r\ from 0: 1 — f0 = {iy. 10.5. Complete Quantitative Theory 10.5.1. General results. We can now pass to the complete statistical analysis of the Sheffer stroke operation on bundles. In order to do this, we must agree on a systematic way to handle this operation by a network. The system to be adopted will be the following: The necessary executive organ will be followed in series by a restoring organ. That is to say the Sheffer organ network of Fig. 34 will be followed in series by the Sheffer organ network of Fig. 37. This means that the formulas of (22) are to be followed by those of (24). Thus {, n are the excitation
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levels of the two input bundles, ^ is the excitation level of the output bundle, and we have: C = (1 - {,,) + 2c(€if - i ) + V{[(i - 2«) 2 «i - £Mi - n) + £(i - «)]/N}a* 2 co = (1 - C ) + 2e(C2 - i ) + + V{[(1 - 2£)2[C(1 - C)]2 + £(1 - «)]/*}*** 4f = (1 - co2) + 2E(CO2 - i ) + + V{[(1 - 2E)2[CO(1 - co)]2 + £(1 -
i
I
(25)
( E)-]IN}6***
S*y <$**, d*** are stochastic variables, independently and normally distributed, with the mean 0 and the dispersion 1.
)
Consider now a given fiduciary level A. Then we need a behavior, like the "correct" one of the Sheffer stroke, with an overwhelming probability. This means: The implication of (// ^ A by c; g 1 — A, rj ^ 1 — A; the implication of $ ^ 1 - A by £ ^ A, rj ;> 1 - A; the implication of ip ^ 1 - A by <; <; A, rj g A. We are, of course, using the symmetry in c;, rj.) This may, of course, only be expected for N sufficiently large and e sufficiently small. In addition, it will be necessary to make an appropriate choice of the fiduciary level A. If N is so large and e is so small, that all terms in (25) containing factors \/y/N and £ can be neglected, then the above desired "overwhelmingly probable" in ferences become even strictly true, if A is small enough. Indeed, then (25) gives C = Co = 1 - ft.co = co0 = I - C2, * = ^o = 1 -
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stated further above. As is to be expected, this estimate is given by an error integral. This is 1 2 -i«2 PCN).= e *' dx> e
7(^)J«
~V(2TI)K
>
where
I
k = 0.0627N
J
(26)
expresses, in a certain sense, the total allowable error divided by a composite standard deviation. The approximation is of course valid only for large N. It can also be written in the form p(N)„
^L
\IN
JQ-8.6N/10,000
(2?)
The following table gives a better idea of the dependency expressed by the formula: N = number of lines in a bundle 1,000 2,000 3,000 5,000 10,000 20,000 25,000
p(N) = probability of malfunction 2.7 X 10"-2 2.6 X 10"-3 2.5 X 10"- 4 4 X 10"- 3 1.6 X 10" 10 2.8 X 10" 19 1.2 X 10" 23
Notice that for as many as 1,000 lines in a bundle, the reliability (about 3 per cent) is rather poor. (Indeed, it is inferior to the e = 0.005, i.e. 1/2 per cent, that we started with.) Nowever, a 25 fold increase in this size gives very good reliability. 10.5.3. Examples 10.53.1. First example. To get an idea of the significance of these sizes and the corresponding approximations, consider the two following examples. Consider first a computing machine with 2,500 vacuum tubes, each of which is actuated on the average once every 5 /isec. Assume that a mean free path of 8 hr between errors is desired. In this period of time there will have been i x 2500 x 8 x 3600 x 106 = 1.4 x 10 13 actuations, hence the above specification calls for S ~ 1/[1.4 x 1013] = 7 x 10" 14 . According to the above table this calls for an N between 10,000 and 20,000—interpolating linearly on -log 10 <5 gives N = 14,000. That is to say, the system should be multiplexed 14,000 times. It is characteristic for the steepness of statistical curves in this domain of large numbers of events, that a 25 per cent increase of TV, i.e. N = 17,500, gives (again by interpolation) S = 4.5 x 10" 1 7 , i.e. a reliability which is 1,600 times better. 10.5.3.2. Second example. Consider second a plausible quantitative picture for the functioning of the human nervous system. The number of neurons involved is
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usually given as 1010, but this number may be somewhat low, also the synaptic end-bulbs and other possible autonomous sub-units may increase it significantly, perhaps a few hundred times. Let us therefore use the figure 1013 for the number of basic organs that are present. A neuron may be actuated up to 200 times per second, but this is an abnormally high rate of actuation. The average neuron will probably be actuated a good deal less frequently, in the absence of better infor mation 10 actuations per second may be taken as an average figure of at least the right order. It is hard to tell what the mean free path between errors should be. Let us take the view that errors properly defined are to be quite serious errors, and since they are not ordinarily observed, let is take a mean free path which is long compared to an ordinary human life—say 10,000 years. This means 1013 x 10,000 x 31,536,000 x 10 = 3.2 x 1025 actuations, hence it calls for S ~ 1/(3.2 x 1025) = 3.2 x 10" 26 . According to the table this lies somewhat beyond N = 25.000— extrapolating linearly on log 10 S gives N = 28,000. Note, that if this interpretation of the functioning of the human nervous system were a valid one (for this cf. the remark of 11.1), the number of basic organs involved would have to be reduced by a factor 28,000. This reduces the number of relevant actuations and increases the value of the necessary 3 by the same factor. That is to say, 3 = 9 x 10~ 22 , and hence N = 23,000. The reduction of N is remarkably small—only 20 per cent! This makes a re-evaluation of the reduced N with the new N9 3 unnecessary: In fact the new factor, i.e. 23,000, gives $ = 7.4 x 10~ 22 and this with the approximation used above, again N = 23,000. (Actually the change of N is ~ 120, i.e. only 1/2 per cent!) Replacing the 10,000 years, used above rather arbitrarily, by 6 months, intro duces another factor 20,000, and therefore a change of about the same size as the above one—now the value is easily seen to be N = 23,000 (uncorrccted) or # = 19,000 (corrected). 10.6. Conclusions. All this shows, that the order of magnitude of N is remark ably insensitive to variations in the requirements, as long as these requirements are rather exacting ones, but not wholly outside the range of our (industrial or natural) experience. Indeed, the N obtained above were all ~ 20,000, to within variations lying between —30 and -1-40 per cent. 10.7. The General Scheme of Multiplexing. This is an opportune place to sum marize our results concerning multiplexing, i.e. the sections 9 and 10. Suppose it is desired to build a machine to perform the logical function f(x, r, . . .) with a given accuracy (probability of malfunction on the final result of the entire opera tion) Y\, using Sheffer neurons whose reliability (or accuracy, i.e. probability of malfunction on a single operation) is s. We assume e = 0.005. The procedure is then as follows. First, design a network R for this function / ( * , > , . . . ) as though the basic (Sheffer) organs had perfect accuracy. Second, estimate the maximum number of single (perfect) Sheffer organ reactions (summed over all successive operations of all the Sheffer organs actually involved) that occur in the network R in evaluating /(*, y> • • •)—say m such reactions. Put 3 = ////w. Third, estimate the bundle size N that is needed to give the multiplexed Sheffer organ like network (cf. 10.5.2) an
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error probability of at most S. Fourth, replace each single line of the network R by a bundle of size N, and each Shefler nueron of the network R by the multi plexed Sheffer organ network that goes with this N (cf. 10.5.1)—this gives a net work R{N). A "yes" will then be transmitted by the stimulation of more than 93 per cent of the strands in a bundle, a "no" by the stimulation of less than 7 per cent, a id intermediate values will signify the occurrence of an essential malfunction of the total system. It should be noticed that this construction multiplies the number of lines by N and the number of basic organs by 37V. (In 10.5.3 we used a uniform factor of multiplication N. In view of the insensitivity of N to moderate changes in <5, that we observed in 10.5.3.2, this difference is irrelevant.) Our above considerations show, that the size of N is ~ 20,000 in all cases that interest us immediately. This implies, that such techniques are impractical for present technologies of com ponentry (although this may perhaps not be true for certain conceivable tech nologies of the future), but they are not necessarily unreasonable (at least not on grounds of size alone) for the micro-componentry of the human nervous system. Note, that the conditions are significantly less favorable for the non-multi plexing procedure to control error described in section 8. That process multiplied the number of basic organs by about 3", \i being the number of consecutive steps (i.e. basic org<*n actuations) from input to output (cf. the end of 8.4). (In this way of counting, iterative processes must be counted as many times as iterations occur.) This for \i — 160, which is not an excessive "logical depth", even for a conventional calculation, 3 1 6 0 ~ 2 x 1076, i.e. somewhat above the putative order of the number of electrons in the universe. For \x — 200 (only 25 per cent more!) then 3 2 0 0 ~ 2.5 x 1095, i.e. 1.2 x 1019 times more—in view of the above this requires no comment. 11. General Comments on Digitalization and Multiplexing 11.1. Plausibility of Various Assumptions Regarding the Digital vs. Analog Character of the Nervous System. We now pass to some remarks of a more general character. The question of the number of basic neurons required to build a multiplexed automaton serves as an introduction for the first remark. The above discussion shows, that the multiplexing technique is impractical on the level of present technology, but quite practical for a perfectly conceivable, more advanced, tech nology, and for the natural relay-organs (neurons). That is to say, it merely calls for microcomponentry which is not at all unnatural as a concept on this level. It is therefore quite reasonable to ask specifically, whether it, or something more or less like it, is a feature of the actually existing human (or rather: animal) nervous system. The answer is not clear cut. The main trouble with the multiplexing systems, as described in the preceding section, is that they follow too slavishly a fixed plan of construction—and specifically one, that is inspired by the conventional pro cedures of mathematics and mathematical logics. It is true, that the animal nervous systems, too, obey some rigid "architectural" patterns in their large-scale
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construction, and that those variations, which make one suspect a merely statistical design, seem to occur only in finer detail and on the micro-level. (It is characteristic of this duality, that most investigators believe in the existence of overall laws of large-scale nerve-stimulation and composite action that have only a statistical character, and yet occasionally a single neuron is known to control a whole reflexarc.) It is true, that our multiplexing scheme, too, is rigid only in its large-scale pattern (the prototype network R, as a pattern, and the general layout of the executive-plus-restoring organ, as discussed in 10.7 and in 10.5.1), while the "random" permutation "black boxes" (cf. the relevant Figs. 32, 35, 37 in 9.2.3 and 9.4.2) are typical of a "merely statistical design". Yet the nervous system seems to be somewhat more flexibly designed. Also, its "digital" (neural) opera tions are rather freely alternating with "analog" (humoral) processes in their complete chains of causation. Finally the whole logical pattern of the nervous system seems to deviate in certain important traits qualitatively and significantly from our ordinary mathematical and mathematical-logical modes of operation: The pulse-trains that carry "quantitative" messages along the nerve fibres do not seem to be coded digital expressions (like a binary or a [Morse or binary coded] decimal digitalization) of a number, but rather "analog" expressions of one, by way of their pulse-density, or something similar—although much more than ordinary care should be exercised in passing judgments in this field, where we have so little factual information. Also, the "logical depth" of our neural opera tions—i.e. the total number of basic operations from (sensory) input to (memory) storage or (motor) output seems to be much less than it would be in any artificial automaton (e.g. a computing machine) dealing with problems of anywhere nearly comparable complexity. Thus deep differences in the basic organizational principles are probably present. Some similarities, in addition to the one referred to above, are nevertheless undeniable. The nerves are bundles of fibres—like our bundles. The nervous system contains numerous "neural pools" whose function may well be that of organs devoted to the restoring of excitation levels. (At least of the two [extreme] levels, e.g. one near to 0 and one near to 1, as in the case discussed in section 9, especially in 9.2.2 and 9.2.3, 9.4.2. Restoring one level only—by exciting or quenching or establishing some intermediate stationary level—destroys rather than restores information, since a system with a single stable state has a memory capacity 0 [cf. the definition given in 5.2]. For systems which can stabilize [i.e. restore] more than two excitation levels, cf. 12.6.) 11.2. Remarks Concerning the Concept of a Random Permutation. The second remark on the subject of multiplexed systems concerns the problem (which was so carefully sidestepped in section 9) of maintaining randomness of stimulation. For all statistical analyses, it is necessary to assume that this randomness exists. In networks which allow feedback, however, when a pulse from an organ gets back to the same organ ai some later time, there is danger of strong statistical correlation. Moreover, without randomness, situations may arise where errors tend to be amplified instead of cancelled out. For example it is possible, that the machine remembers its mistakes, so to speak, and thereafter perpetuates them. A simplified
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example of this effect is furnished by the elementary memory organ of Fig. 16, or by a similar one, based on the Sheffer stroke, shown in Fig. 39. We will discuss the latter. This system, provided it makes no mistakes, fires on alternate moments of time. Thus it has two possible states: Either itfiresat even times or at odd times. (For a quantitative discussion of Fig. 16, cf. 7.1.) However, once the mechanism makes a mistake, i.e. if it fails to fire at the right parity, or if it fires at the wrong parity, that error will be remembered, i.e. the parity is now lastingly altered, until there occurs a new mistake. A single mistake thus destroys the memory of this particular machine for all earlier events. In multiplex systems, single errors are not necessarily disastrous: But without the "random" permutations introduced in section 9, accumulated mistakes can be still dangerous.
FIG.
39
To be more specific: Consider the network shown in Fig. 35, but without the line-permuting "black box" V. If each output line is now fed back into its input line (i.e. into the one with the same number from above), then pulses return to the identical organ from which they started, and so the whole organ is in fact a sum of separate organs according to Fig. 39, and hence it is just as subject to error as a single one of those organs acting independently. However, if a permutation of the bundle is interposed, as shown, in principle, by V in Fig. 35, then the accuracy of the system may be (statistically) improved. This is, of course, the trait which is being looked for by the insertion of £/, i.e. of a "random" permutation in the sense of section 9. But how is it possible to perform a "random" permu tation? The problem is not immediately rigorously defined. It is, however, quite proper to reinterpret it as a proNem that can be stated in a rigorous form, namely: It is desired to find one or more permutations which can be used in the "black boxes" marked with U or Uu U2 in the relevant Figs. 35, 37, so that the essential statistical properties that are asserted there are truly present. Let us consider the simpler one of these two, i.e. the multiplexed version of the simple memory organ of Fig. 39—i.e. a specific embodiment of Fig. 35. The discussion given in 10.3 shows that it is desirable, that the permutation U of Fig. 35 permute the even lines among each other, and the odd lines among each other. A possible rigorous variant of the question that should now be asked is this. Find a fiduciary level A > 0 and a probability £ > 0, such that for any r\ > 0 and any s = 1 , 2 , . . . there exists an N — N(rjy $) and a permutation (/ = UiN\ satisfying the following requirement: Assume that the probability of error in a single operation of any given Sheffer organ is e. Assume that at the time / all lines of the above network are stimulated, or that all are not stimulated. Then the
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number of lines stimulated at the time / + s will be ^ (1 - A)JV or g AN, respectively,with a probability ^ 1 - d. In addition N(rj9 s) £ C \n(s/rf)9 with a constant C (which should not be excessively great). Note, that the results of section 10 make the surmise seem plausible, that A = 0.07, £ = 0.005 and C - 10,000/[8.6 x In 10] - 500 are suitable choices for the above purpose. The following surmise concerning the nature of the permutation UiN) has a certain plausibility: Let N = 2l. Consider the 2l complexes (dl9 dl9..., ,) (dx = 0, 1 for A = 1 , . . . , /). Let these correspond in some one to one way to the 2' integers / = \9.. . 9N: i^(d iT±(dltlydd22y...,dt)
d,)
(28)
Now let the mapping ,,• -- , 'r == (/<">/ c/(JV)i
(29)
be induced, under the correspondence (28), by the mapping (dul,d ,...,d,)-*(d„d ,...,d,. d22,... 9dl)-+(dhdu...19d l-l) l)
(30)
Obviously, the validity of our assertion is independent of the choice of the corres pondence (28). Now (30) does not change the parity of
id, Id, hence the desideratum that U{N\ i.e. (29), should not change the parity of / (cf. above) is certainly fulfilled, if the correspondence (28) is so chosen as to let / have the same parity as
i*>
X=l
This is clearly possible, since on either side each parity occurs precisely 2 / _ 1 times. This U{N) should fulfil the above requirements. 11.3. Remarks Concerning the Simplified Probability Assumption. The third remark on multiplexed automata concerns the assumption made in defining the unreliability of an individual neuron. It was assumed that the probability of the neuron failing to react correctly was a constant e, independent of time and of all previous inputs. This is an unrealistic assumption. For example, the probability of failure for the Sheffer organ of Fig. 12 may well be different when the inputs a and b are both stimulated, from the probability of failure when a and not b is stimulated. In addition, these probabilities may change with previous history, or simply with time and other environmental conditions. Also, they are quite likely to be different from neuron to neuron. Attacking the problem with these more realistic assumptions means finding the domains of operability of individual neurons, finding the intersection of these domains (even when drift with time is allowed) and finally, carrying out the statistical estimates for this far more com plicated situation. This will not be attempted here.
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12. Analog Possibilities 12.1. Further Remarks Concerning Analog Procedures. There is no valid reason for thinking that the system which has been developed in the past pages is the only or the best model of any existing nervous system or of any potential errorsafe computing machine or logical machine. Indeed, the form of our modelsystem is due largely to the influence of the techniques developed for digital computing and to the trends of the last sixty years in mathematical logics. Now, speaking specifically of the human nervous system, this is an enormous mechanism —at least 106 times larger than any artifact with which we are familiar—and its activities are correspondingly varied and complex. Its duties include the inter pretation of external sensory stimuli, of reports of physical and chemical conditions, the control of motor activities and of internal chemical levels, the memory function with its very complicated procedures for the transformation of and the search for information, and of course, the continuous relaying of coded orders and of more or less quantitative messages. It is possible to handle all these processes by digital methods (i.e. by using numbers and expressing them in the binary system—or, with some additional coding tricks, in the decimal or some other system), and to process the digitalized, and usually numericized, information by algebraical (i.e. basically arithmetical) methods. This is probably the way a human designer would at present approach such a problem. It was pointed out in the discussion in 11.1, that the available evidence, though scanty and inadequate, rather tends to indicate that the human nervous system uses different principles and procedures. Thus message pulse trains seem to convey meaning by certain analogic traits (within the pulse notation—i.e. this seems to be a mixed, part digital, part analog system), like the time density of pulses in one line, correlations of the pulse time series between different lines in a bundle, etc. Hence our multiplexed system might come to resemble the basic traits of the human nervous system more closely, if we attenuated its rigidly discrete and digital character in some respects. The simplest step in this direction, which is rather directly suggested by the above remarks about the human nervous system, would seem to be this. 12.2. A Possible Analog Procedure 12.2.1. The set up. In our prototype network R each line carries a "yes" (i.e. stimulation) or a "no" (i.e. non-stimulation) message—these are interpreted as digits 1 and 0, respectively. Correspondingly, in the final (multiplexed) network R(N) (which is derived from R) each bundle carries a "yes" = 1 (i.e. prevalent stimulation) or a "no" = 0 (i.e. prevalent non-stimulation) message. Thus only two meaningful states, i.e. average levels of excitation {, are allowed for a bundleactually for one of these £ ~ 1 and for the other f ~ 0. Now for large bundle sizes N the average excitation level f is an approximately continuous quantity (in the interval 0 ^ { g 1)—the larger N, the better the ap proximation. It is therefore not unreasonable to try to evolve a system in which \ is treated as a continuous quantity in 0 £ ( :g 1. This means an analog pro cedure (or rather, in the sense discussed above, a mixed, part digital, part analog
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procedure). The possibility of developing such a system depends, of course, on finding suitable algebraic procedures that fit into it, and being able to assure its stability in the mathematical sense (i.e. adequate precision) and in the logical sense (i.e. adequate control of errors). To this subject we will now devote a few remarks. 12.2.2. The operations. Consider a multiplex automaton of the type which has just been considered in 12.2.1, with bundle size N. Let <J denote the level of exitation of the bundle at any point, that is, the relative number of excited lines. With this interpretation, the automaton is a mechanism which performs certain numerical operations on a set of numbers to give a new number (or numbers). This method of interpreting a computer has some advantages, as well as some disadvantages in comparison with the digital, "all or nothing", interpretation. The conspicuous advantage is that such an interpretation allows the machine to carry more infor mation with fewer components than a corresponding digital automaton. A second advantage is that it is very easy to construct an automaton which will perform the elementary operations of arithmetics. (Or, to be more precise: An adequate subset of these. Cf. the discussion in 12.3.) For example, given £ and nt it is possible to obtain i(£ + rj) as shown in Fig. 40. Similarly, it is possible to obtain N LINES STIMULATED
N LINES 7}N STIMULATED
FIG. 40
N LINES STIMULATED
N LINES 7}N STIMULATED FIG. 41
otf + (1 - (x)n for any constant a with 0 <; a £ 1. (Of course, there must be a = M/N, M = 0, 1, . . . , Nt but this range for a is the same "approximate con tinuum" as that one for {, hence we may treat the former as a continuum just as properly as the latter.) We need only choose <xN lines from the first bundle ami combine them with (I - <x)N lines from the second. To obtain the quantity 1 - in requires the set-up shown in Fig. 41. Finally we can produce any constant excitation
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level oc(0 ^ a ^ 1), by originating a bundle so that <xN lines come from a live source and (1 — <x)N from ground. 12.3. Discussion of the Algebraical Calculus Resulting from the Above Operation. Thus our present analog system can be used to build up a system of algebra where the fundamental operations are a ac + (1 - <x)n
( (for (for any constant const a ) i n0O^^ aa ^ g l 1), ), ) [1 in
\ (31)
All these are to be viewed as functions of f 2» • • • > £*> tnat t n e functions of (31) generate. That is to say with all functions that can be obtained by any succession of the following processes: (A) In the functions of (31) replace oo to f(£ly. . . , £ t ), then form this J[Zl9... , £k). Note, that in order to have the freedom of operation as expressed by (A), (B), the same "randomness'* conditions must be postulated as in the corresponding parts of sections 9 and 10. Hence "randomizing" permutations U must be inter posed between consecutive executive organs (i.e. those described above and reenumerated in (A)), just as in the sections referred to above. In ordinary algebra the basic functions are different ones, namely: a Z+ V
ft
i (for any constant a \ inOrga^l),
\ /
\ (32)
i
It is easily seen, that the system (31) can be generated (by (A), (B)) from the system (32), while the reverse is not obvious (not even with (C) added). In fact (31) is intrinsically more special than (32), i.e. the functions that (31) generates are fewer than those that (32) generates (this is true for (A), (B), and also for (A), (B), (C))—the former do not even include £ -I- r\. Indeed all functions of (31), i.e. of (A) based on (31), have this property: If all variables lie in the interval 0 ^ ^ ^ 1, then the function, too, lies in that interval. This property is conserved under the applications of (B), (C). On the other hand
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In spite of this limitation, which seems to mark it as essentially narrower than conventional algebra, the system of functions generated (by (A), (B), (C)) from (31) is broad enough for all reasonable purposes. Indeed, it can be shown that the functions so generated comprise precisely the following class of functions: All functions/^!, £2» • • •» £*) which, as long as their variables {,,. . . , £k He in the interval 0 S £ S 1, are continuous and have their value lying in that interval, too. We will not give the proof here, it runs along quite conventional lines. 12.4. Limitations of this System. This result makes it clear, that the above analog system, i.e. the system of (31), guarantees for numbers { with 0 ^ f g 1 (i.e. for the numbers that it deals with, namely excitation levels) the full freedom of algebra and of analysis. In view of these facts, this analog system would seem to have clear superiority over the digital one. Unfortunately, the difficulty of maintaining accuracy levels counterbalances the advantages to a large extent. The accuracy can never be expected to exceed \/N. In other words, there is an intrinsic noise level of the order 1/7V, i.e. for the TV considered in 10.5.2 and 10.5.3 (up to ~ 20,000) at best 10~4. Moreover, in its effects on the operations of (31), this noise level rises from 1/jVto \/y/N. For example for the operation 1 — fy, cf. the result (21) and the argument that leads to it.) With the above assumptions, this is at best ~ 10" 2 , i.e. 1 per cent! Hence after a moderate number of operations, the excitation levels are more likely to resemble a random sampling of numbers than mathematics. It should be emphasized, however, that this is not a conclusive argument that the human nervous system does not utilize the analog system. As was pointed out earlier, it is in fact known for at least some nervous processes that they are of an analog nature, and that the explanation of this may, at least in part, lie in the fact that the "logical depth*' of the nervous network is quite shallow in some relevant places. To be more specific: The number of synapses of neurons from the peripheral sensory organs, down the afferent nerve fibres, through the brain, back through the efferent nerves to the motor system may not be more than ~ 10. Of course the parallel complexity of the network of neurons is indisputable. "Depth" introduced by feedback in the human brain may be overcome by some kind of self-stabilization. At the same time, a good argument can be put up that the animal nervous system uses analog methods (as they are interpreted above) only in the crudest way, accuracy being a very minor consideration. 12.5. A Plausible Analog Mechanism: Density Modulation by Fatigue. Two more remarks should be made at this point. The first one deals with some more specific aspects of the analog element in the organization and functioning of the human nervous system. The second relates to the possibility of stabilizing the precision level of the analog procedure that was outlined above. This is the first remark. As we have mentioned earlier, many neurons of the nervous system transmit intensities (i.e. quantitative data) by analog methods, -but, in a way entirely different from the method described in 12.2, 12.3 and 12.4. Instead of the level of excitation of a nerve (i.e. of a bundle of nerve fibres) varying, as described in 12.2, the single nerve fibres fire repetitiously, but with varying
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frequency in time. For example, the nerves transmitting a pressure stimulus may vary in frequency between, say, 6 firings per second and, say, 60 firings per second. This frequency is a monotone function of the pressure. Another example is the optic nerve, where a certain set of fibres responds in a similar manner to the intensity of the incoming light. This kind of behaviour is explained by the mechanism of neuron operation, and in particular with the phenomena of threshold and of fatigue. With any peripheral neuron at any time can be associated a threshold intensity: A stimulus will make the neuron fire if and only if its magni tude exceeds the threshold intensity. The behavior of the threshold intensity as a function of the time after a typical neuron fires is qualitatively pictured in Fig. 42. After firing, there is an "absolute refractory perkKr of about 5 msec, during which no stimulus can make the neuron fire again. During this period, the threshold value is infinite. Next comes a "relative refractory period" of about 10 msec, during which time the threshold level drops back to its equilibrium value (it may even oscillate about this value a few times at the end). This decrease is for the most part monotonic. Now the nerve will fire again as soon as it is stimulated with an intensity greater than its excitation threshold. Thus if the neuron is subjected to continual excitation of constant intensity (above the equilibrium intensity), it will fire periodically with a period between 5 and 15 msec, depending on the intensity of the stimulus.
NORMAL THRESHOLD LEVEL
RELATIVE ABSOLUTE
NEURON _ FIRES FIG.
REFRACTORY INTERVAL
42
Another interesting example of a nerve network which transmits intensity by this means is the human acoustic system. The ear analyzes a sound wave into its component frequencies. These are transmitted to the brain through different nerve fibres with the intensity variations of the corresponding component represented by the frequency modulation of nerve firing. The chief purpose of all this discussiort of nervous systems is to point up the fact that it is dangerous to identify the real physical (or biological) world with the models which are constructed to explain it. The problem of understanding the animal nervous action is far deeper than the problem of understanding the mechanism of a computing machine. Even plausible explanations of nervous reaction should be taken with a very large grain of salt. 12.6. Stabilization of the Analog System. We now come to the second remark. It was pointed out earlier, that the analog mechanism that we discussed may
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have a way of stabilizing excitation levels to a certain precision for its computing operations. This can be done in the following way. For the digital computer, the problem was to stabilize the excitation level at (or near) the two values 0 and 1. This was accomplished by repeatedly passing the bundle through a simple mechanism which changed an excitation level £ into the level /(£), where the function /({) had the general form shown in Fig. 43. The reason that such a mechanism is a restoring organ for the excitation levels £ ~ 0 and £ ~ 1 (i.e. that it stabilizes at—or near—0 and 1) is that/(£) has this property: For some suitable b(0 ^ b S 1) 0 < £ < b implies 0 (
FIG. 43
FIG. 44
0 = do < bl < alt < . . . < av-t < bv < av = 1, for / = 1 , . . . , v: a,-! < f < bi implies a,_j < / ( { ) < £ Z>f < { < a, implies { < f(£) < ar Here 0o(= 0), a l t . . . , Av_lf a v (= 1) a r e / ( 0 ' s only stable iixpoints, and such a mechanism is a restoring organ for the excitation levels £ ~ a0(= 0\ alt. . ., 0v-i> «»(= 0- Choose, e.g. a, = //v (/ = 0, 1 , . . . , v), with v" 1 < S, or more generally, just at - ai.i < d (/ = 1 , . . . , v) with some suitable v. Then this restoring organ clearly conserves precisions of the order S (with the same prevalent probability with which it restores). 13. Concluding Remark 13.1. A Possible Neurological Interpretation. There remains the question, whether such a mechanism is possible, with the means that we are now envisaging. We have seen further above, that this is the case, if a function /(£) with the properties just described can be generated from (31). Such a function can indeed be so generated. Indeed, this follows immediately from the general characterization of the class of functions that can be generated from (31), discussed in 12.3. How ever, we will not go here into this matter any further.
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It is not inconceivable that some "neural pools" in the human nervous system may be such restoring organs, to maintain accuracy in those parts of the network where the analog principle is used, and where there is enough "logical depth" (cf. 12.4) to make this type of stabilization necessary.
BIBLIOGRAPHY
S. C. KLEENE, Representation of events in nerve nets andfiniteautomata, Automata Studies, edited by C. E. SHANNON and J. Mc CARTHY, Princeton Univ. Press, 1956, pp. 3-42. 2. W. S. MCCULLOCH and W. PITTS, "A logical calculus of the ideas immanent in nervous activity," Bull. Math. Biophys., 5 (1943), pp. 115-133. 3. C. E. SHANNON, "A mathematical theory of communication," Bell Syst. Tech. J., 27 (1948), pp. 379-423. 4. L. SZILARD, "Uber die Entropievermmderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen," Z. Phys., 53 (1929), pp. 840-856. 5. A. M. TURING, "On computable numbers," Proc. Lond. Math. Soc. 2 (42) (1936), pp. 230-265. 1.
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Neumann, in his last years, became a public person, a C^UJOV ISOXITIKOV. He always had an interest in history and events of the world, he was not an introvert mathematician, on the contrary, he, from the very beginning of his intellectual life was an extrovert. His experience of nazi fascism and later of Stalinism has led him to be an active combatant of liberal democracy, con tinuing his family heritage. He fought with his mathematical genius against all those dictatorships and assumed an active role in military efforts during WWII and after, during the cold war. He was not a hawk, fighting with desperate emotions, nor was he a devoted follower of any certain ideology. He remained a rational thinker as he was always in science and this rational way of thinking lent him a far looking, if possible conciliatory, pragmatic at titude, which is an up-to-date message till now. Our selection in this volume concentrates on these.
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of the nature of intellectual work is a difficult task in any field, even in fields which are not so far removed from the central area of our common human intellectual effort as mathematics still is. A discussion of the nature of any intellectual effort is difficult per se—at any rate, more difficult than the mere exercise of that particular intellectual effort. It is harder to understand the mechanism of an airplane, and the theories of the forces which lift and which propel it, than merely to ride in it, to be elevated and transported by it—or even to steer it. It is exceptional that one should be able to acquire the understanding of a process without having previously acquired a deep familiarity with running it, with using it, before one has assimilated it in an instinctive and empirical way. Thus any discussion of the nature of intellectual effort in any field is difficult, unless it presupposes an easy, routine familiarity with that field. In mathematics this limitation becomes very severe, if the discussion is to be kept on a non-mathematical plane. The discussion will then necessarily show some very bad features; points which are made can never be properly documented, and a certain over-all superficiality of the discussion becomes unavoidable. I am very much aware of these shortcomings in what I am going to say, and I apologize in advance. Besides, the views which I am going to express are probably not wholly shared by many other mathematicians—you will get one man's not-toowell systematized impressions and interpretations—and I can give you only very little help in deciding how much they are to the point. In spite of all these hedges, however, I must admit that it is an interesting and challenging task to make the attempt and to talk to you about the nature of intellectual effort in mathematics. I only hope that I will not fail too badly. The most vitally characteristic fact about mathematics is, in my opinion, its quite peculiar relationship to the natural sciences, or, more generally, to any science which interprets experience on a higher than purely descriptive level. Most people, mathematicians and others, will agree that mathematics is not an empirical science, or at least that it is practiced in a manner which differs in several decisive respects from the techniques of the empirical sciences. And, yet, its development is very closely linked with the natural sciences. One of its main branches, geometry, actually started as a natural, empirical science. Some of the 1
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Published in "The Works of the Mind", ed. R. B. Heywood, pp. 180-196, © 1947 University of Chicago Press. Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. I, pp. 1-9.
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best inspirations of modern mathematics (I believe, the best ones) clearly originated in the natural sciences. The methods of mathematics pervade and dominate the "theoretical" divisions of the natural sciences. In modern empirical sciences it has become more and more a major criterion of success whether they have become accessible to the mathematical method or to the near-mathematical methods of physics. Indeed, throughout the natural sciences an unbroken chain of successive pseudomorphoses, all of them pressing toward mathematics, and almost identified with the idea of scientific progress, has become more and more evident. Biology becomes increasingly pervaded by chemistry and physics, chemistry by experimental and theoretical physics, and physics by very mathematical forms of theoretical physics. There is a quite peculiar duplicity in the nature of mathematics. One has to realize this duplicity, to accept it, and to assimilate it into one's thinking on the subject. This double face is the face of mathematics, and I do not believe that any simplified, Unitarian view of the thing is possible without sacrificing the essence. I will therefore not attempt to present you with a Unitarian version. I will attempt to describe, as best I can, the multiple phenomenon which is mathematics. It is undeniable that some of the best inspirations in mathematics—in those parts of it which are as pure mathematics as one can imagine —have come from the natural sciences. We will mention the two most monumental facts. The first example is, as it should be, geometry. Geometry was the major part of ancient mathematics. It is, with several of its ramifications, still one of the main divisions of modern mathematics. There can be no doubt that its origin in antiquity was empirical and that it began as a discipline not unlike theoretical physics today. Apart from all other evidence, the very name "geometry" indicates this. Euclid's postulational treatment represents a great step away from empiricism, but it is not at all simple to defend the position that this was the decisive and final step, producing an absolute separation. That Euclid's axiomatization does at some minor points not meet the modern requirements of absolute axiomatic rigor is of lesser importance in this respect. What is more essential, is this: other disciplines, which are undoubtedly empirical, like mechanics and thermodynamics, are usually presented in a more or less postulational treatment, which in the presentation of some authors is hardly distinguishable from Euclid's procedure. The classic of theoretical physics in our time, Newton's Principia, was, in literary form as well as in the essence of some of its most critical parts, very much like Euclid. Of course in all these instances there is behind the postulational presentation the physical insight backing the postulates and the experimental verification supporting the theorems. But one might well argue that a similar interpretation of Euclid is possible, especially from the viewpoint of antiquity, before geometry had acquired its present bimillennial stability and authority—an authority which the modern edifice of theoretical physics is clearly lacking. Furthermore, while the de-empirization of geometry has gradually progressed since Euclid, it never became quite complete, not even in modern times. The discussion of non-Euclidean geometry offers a good illustration of this. It also offers an illustration of the ambivalence of mathematical thought. Since most of the discussion took place on a highly abstract plane, it dealt with the purely logical
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problem whether the "fifth postulate" of Euclid was a consequence of the others or not; and the formal conflict was terminated by F. Klein's purely mathematical example, which showed how a piece of a Euclidean plane could be made nonEuclidean by formally redefining certain basic concepts. And yet the empirical stimulus was there from start to finish. The prime reason, why, of all Euclid's postulates, the fifth was questioned, was clearly the unempirical character of the concept of the entire infinite plane which intervenes there, and there only. The idea that in at least one significant sense—and in spite of all mathematico-logical analyses—the'decision for or against Euclid may have to be empirical, was certainly present in the mind of the greatest mathematician, Gauss. And after Bolyai, Lobatschefski, Riemann, and Klein had obtained more abstracto, what we today consider the formal resolution of the original controversy, empirics—or rather physics—nevertheless, had the final say. The discovery of general relativity forced a revision of our views on the relationship of geometry in an entirely new setting and with a quite new distribution of the purely mathematical emphases, too. Finally, one more touch to complete the picture of contrast. This last development took place in the same generation which saw the complete de-empirization and abstraction of Euclid's axiomatic method in the hands of the modern axiomatic-logical mathematicians. And these two seemingly conflicting attitudes are perfectly compatible in one mathematical mind; thus Hilbert made important contributions to both axiomatic geometry and to general relativity. The second example is calculus—or rather all of analysis, which sprang from it. The calculus was the first achievement of modern mathematics, and it is difficult to overestimate its importance. I think it defines more unequivocally than anything else the inception of modern mathematics, and the system of mathematical analysis, which is its logical development, still constitutes the greatest technical advance in exact thinking. The origins of calculus are clearly empirical. Kepler's first attempts at integration were formulated as "dolichometry"—measurement of kegs—that is, volumetry for bodies with curved surfaces. This is geometry, but post-Euclidean, and, at the epoch in question, nonaxiomatic, empirical geometry. Of this, Kepler was fully aware. The main effort and the main discoveries, those of Newton and Leibnitz, were of an explicitly physical origin. Newton invented the calculus " of fluxions" essentially for the purposes of mechanics—in fact, the two disciplines, calculus and mechanics, were developed by him more or less together. The first formulations of the calculus were not even mathematically rigorous. An inexact, semiphysical formulation was the only one available for over a hundred and fifty years after Newton! And yet, some of the most important advances of analysis took place during this period, against this inexact, mathematically inadequate background! Some of the leading mathematical spirits of the period were clearly not rigorous, like Euler; but others, in the main, were, like Gauss or Jacobi. The development was as confused and ambiguous as can be, and its relation to empiricism was certainly not according to our present (or Euclid's) ideas of abstraction and rigor. Yet no mathematician would want to exclude it from the fold—that period produced mathematics as first class as ever existed! And even after the reign of rigor was essentially re-established with Cauchy, a very peculiar relapse into semiphysical methods took place with Riemann. Riemann's scientific personality itself is a most illuminating example of
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the double nature of mathematics, as is the controversy of Riemann and Weierstrass, but it would take me too far into technical matters if I went into specific details. Since Weierstrass, analysis seems to have become completely abstract, rigorous, and unempirical. But even this is not unqualifiedly true. The controversy about the "foundations" of mathematics and logics, which took place during the last two generations, dispelled many illusions on this score. This brings me to the third example which is relevant for the diagnosis. This example, however, deals with the relationship of mathematics with philosophy or epistemology rather than with the natural sciences. It illustrates in a very striking fashion that the very concept of "absolute" mathematical rigor is not immutable. The variability of the concept of rigor shows that something else besides mathematical abstraction must enter into the makeup of mathematics. In analyzing the controversy about the "foundations," I have not been able to convince myself that the verdict must be in favor of the empirical nature of this extra component. The case in favor of such an interpretation is quite strong, at least in some phases of the discussion. But I do not consider it absolutely cogent. Two things, however, are clear. First, that something nonmathematical, somehow connected with the empirical sciences or with philosophy or both, does enter essentially—and its nonempirical character could only be maintained if one assumed that philosophy (or more specifically epistemology) can exist independently of experience. (And this assumption is only necessary but not in itself sufficient). Second, that the empirical origin of mathematics is strongly supported by instances like our two earlier examples (geometry and calculus), irrespective of what the best interpretation of the controversy about the "foundations" may be. In analyzing the variability of the concept of mathematical rigor, I wish to lay the main stress on the "foundations" controversy, as mentioned above. I would, however, like to consider first briefly a secondary aspect of the matter. This aspect also strengthens my argument, but I do consider it as secondary, because it is probably less conclusive than the analysis of the "foundations" controversy. I am referring to the changes of mathematical "style." It is well known that the style in which mathematical proofs are written has undergone considerable fluctuations. It is better to talk of fluctuations than of a trend because in some respects the difference between the present and certain authors of the eighteenth or of the nineteenth centuries is greater than between the present and Euclid. On the other hand, in other respects there has been remarkable constancy. In fields in which differences are present, they are mainly differences in presentation, which can be eliminated without bringing in any new ideas. However, in many cases these differences are so wide that one begins to doubt whether authors who "present their cases" in such divergent ways can have been separated by differences in style, taste, and education only—whether they can really have had the same ideas as to what constitutes mathematical rigor. Finally, in the extreme cases (e.g., in much of the work of the late-eighteenth-century analysis, referred to above), the differences are essential and can be remedied, if at all, only with the help of new and profound theories, which it took up to a hundred years to develop. Some of the mathematicians who worked in such, to us, unrigorous ways (or some of their contemporaries, who criticized them) were well aware of their lack of rigor. Or to be more objective: Their own desires as to what mathematical procedure should be were more in conformity with
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our present views than their actions. But others—the greatest virtuoso of the period, for example, Euler—seem to have acted in perfect good faith and to have been quite satisfied with their own standards. However, I do not want to press this matter further. I will turn instead to a perfectly clear-cut case, the controversy about the "foundations of mathematics." In the late nineteenth and the early twentieth centuries a new branch of abstract mathematics, G. Cantor's theory of sets, led into difficulties. That is, certain reasonings led to contraditions; and, while these reasonings were not in the central and "useful" part of set theory, and always easy to spot by certain formal criteria, it was nevertheless not clear why they should be deemed less set-theoretical than the "successful" parts of the theory. Aside from the ex post insight that they actually led into disaster, it was not clear what a priori motivation, what consistent philosophy of the situation, would permit one to segregate them from those parts of set theory which one wanted to save. A closer study of the merita of the case, undertaken mainly by Russell and Weyl, and concluded by Brouwer, showed that the way in which not only set theory but also most of modern mathematics used the concepts of "general validity" and of "existence" was philosophically objectionable. A system of mathematics which was free of these undesirable traits, "intuitionism," was developed by Brouwer. In this system the difficulties and contradiction of set theory did not arise. However, a good fifty per cent of modern mathematics, in its most vital—and up to then unquestioned—parts, especially in analysis, were also affected by this "purge": they either became invalid or had to be justified by very complicated subsidiary considerations. And in this latter process one usually lost appreciably in generality of validity and elegance of deduction. Nevertheless, Brouwer and Weyl considered it necessary that the concept of mathematical rigor be revised according to these ideas. It is difficult to overestimate the significance of these events. In the third decade of the twentieth century two mathematicians—both of them of the first magnitude, and as deeply and fully conscious of what mathematics is, or is for, or is about, as anybody could be—actually proposed that the concept of mathematical rigor, of what constitutes an exact proof, should be changed! The developments which followed are equally worth noting. 1. Only very few mathematicians were willing to accept the new, exigent standards for their own daily use. Very many, however, admitted that Weyl and Brouwer were prima facie right, but they themselves continued to trespass, that is, to do their own mathematics in the old, "easy" fashion—probably in the hope that somebody else, at some other time, might find the answer to the intuitionistic critique and thereby justify them a posteriori. 2. Hilbert came forward with the following ingenious idea to justify "classical" (i.e., pre-intuitionistic) mathematics: Even in the intuitionistic system it is possible to give a rigorous account of how classical mathematics operate, that is, one can describe how the classical system works, although one cannot justify its workings. It might therefore be possible to demonstrate intuitionistically that classical procedures can never lead into contradictions—into conflicts with each other. It was clear that such a proof would be very difficult, but there were certain indications how it might be attempted. Had this scheme worked, it would have provided a most remarkable justification of classical mathematics on the basis of the opposing intuitionistic system itself! At least, this interpretation would have been legitimate
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in a system of the philosophy of mathematics which most mathematicians were willing to accept. 3. After about a decade of attempts to carry out this program, Godel produced a most remarkable result. This result cannot be stated absolutely precisely without several clauses and caveats which are too technical to be formulated here. Its essential import, however, was this: If a system of mathematics does not lead into contradiction, then this fact cannot be demonstrated with the procedures of that system. Godel's proof satisfied the strictest criterion of mathematical rigor—the intuitionistic one. Its influence on Hilbert's program is somewhat controversial, for reasons which again are too technical for this occasion. My personal opinion, which is shared by many others, is, that Godel has shown that Hilbert's program is essentially hopeless. 4. The main hope of a justification of classical mathematics—in the sense of Hilbert or of Brouwer and Weyl—being gone, most mathematicians decided to use that system anyway. After all, classical mathematics was producing results which were both elegant and useful, and, even though one could never again be absolutely certain of its reliability, it stood on at least as sound a foundation as, for example, the existence of the electron. Hence, if one was willing to accept the sciences, one might as well accept the classical system of mathematics. Such views turned out to be acceptable even to some of the original protagonists of the intuitionistic system. At present the controversy about the "foundations" is certainly not closed, but it seems most unlikely that the classical system should be abandoned by any but a small minority. I have told the story of this controversy in such detail, because I think that it constitutes the best caution against taking the immovable rigor of mathematics too much for granted. This happened in our own lifetime, and I know myself how humiliatingly easily my own views regarding the absolute mathematical truth changed during this episode, and how they changed three times in succession! I hope that the above three examples illustrate one-half of my thesis sufficiently well—that much of the best mathematical inspiration comes from experience and that it is hardly possible to believe in the existence of an absolute, immutable concept of mathematical rigor, dissociated from all human experience. I am trying to take a very low-brow attitude on this matter. Whatever philosophical or epistemological preferences anyone may have in this respect, the mathematical fraternities' actual experiences with its subject give little support to the assumption of the existence of an a priori concept of mathematical rigor. However, my thesis also has a second half, and I am going to turn to this part now. It is very hard for any mathematician to believe that mathematics is a purely empirical science or that all mathematical ideas originate in empirical subjects. Let me consider the second half of the statement first. There are various important parts of modern mathematics in which the empirical origin is untraceable, or, if traceable, so remote that it is clear that the subject has undergone a complete metamorphosis since it was cut off from its empirical roots. The 'symbolism of algebra was invented for domestic, mathematical use, but it may be reasonably asserted that it had strong empirical ties. However, modern, "abstract" algebra has more and more developed into directions which have even fewer empirical
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connections. The same may be said about topology. And in all these fields the mathematician's subjective criterion of success, of the worth-whileness of his effort, is very much self-contained and aesthetical and free (or nearly free) of empirical connections. (I will say more about this further on.) In set theory this is still clearer. The "power" and the "ordering" of an infinite set may be the generalizations of finite numerical concepts, but in their infinite form (especially "power") they have hardly any relation to this world. If I did not wish to avoid technicalities, I could document this with numerous set theoretical examples—the problem of the "axiom of choice," the "comparability" of infinite "powers," the "continuum problem," etc. The same remarks apply to much of real function theory and real point-set theory. Two strange examples are given by differential geometry and by group theory: they were certainly conceived as abstract, nonapplied disciplines and almost always cultivated in this spirit. After a decade in one case, and a century in the other, they turned out to be very useful in physics. And they are still mostly pursued in the indicated, abstract, nonapplied spirit. The examples for all these conditions and their various combinations could be multiplied, but I prefer to turn instead to the first point I indicated above: Is mathematics an empirical science? Or, more precisely: Is mathematics actually practiced in the way in which an empirical science is practiced? Or, more generally: What is the mathematician's normal relationship to his subject? What are his criteria of success, of desirability? What influences, what considerations, control and direct his effort? Let us see, then, in what respects the way in which the mathematician normally works differs from the mode of work in the natural sciences. The difference between these, on one hand, and mathematics, on the other, goes on, clearly increasing as one passes from the theoretical disciplines to the experimental ones and then from the experimental disciplines to the descriptive ones. Let us therefore compare mathematics with the category which lies closest to it—the theoretical disciplines. And let us pick there the one which lies closest to mathematics. I hope that you will not judge me too harshly if I fail to control the mathematical hybris and add: because it is most highly developed among all theoretical sciences—that is, theoretical physics. Mathematics and theoretical physics have actually a good deal in common. As I have pointed out before, Euclid's system of geometry was the prototype of the axiomatic presentation of classical mechanics, and similar treatments dominate phenomenological thermodynamics as well as certain phases of Maxwell's system of electrodynamics and also of special relativity. Furthermore, the attitude that theoretical physics does not explain phenomena, but only classifies and correlates, is today accepted by most theoretical physicists. This means that the criterion of success for such a theory is simply whether it can, by a simple and elegant classifying and correlating scheme, cover very many phenomena, which without this scheme would seem complicated and heterogeneous, and whether the scheme even covers phenomena which were not considered or even not known at the time when the scheme was evolved. (These two latter statements express, of course, the unifying and the predicting power of a theory.) Now this criterion, as set forth here, is clearly to a great extent of an aesthetical nature. For this reason it is very closely akin to the mathematical criteria of success, which, as you shall see, are almost entirely aesthetical. Thus we are now comparing mathematics with the
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empirical science that lies closest to it and with which it has, as I hope I have shown, much in common—with theoretical physics. The differences in the actual modus procedendi are nevertheless great and basic. The aims of theoretical physics are in the main given from the "outside," in most cases by the needs of experimental physics. They almost always originate in the need of resolving a difficulty; the predictive and unifying achievements usually come afterward. It we may be permitted a simile, the advances (predictions and unifications) come during the pursuit, which is necessarily preceded by a battle against some pre-existing difficulty /usually an apparent contradiction within the existing system). Part of the theoretical physicists's work is a search for such obstructions, which promise a possibility for a "break-through." As I mentioned, these difficulties originate usually in experimenta tion, but sometimes they are contradictions between various parts of the accepted body of theory itself. Examples are, of course, numerous. Michelson's experiment leading to special relativity, the difficulties of certain ionization potentials and of certain spectroscopic structures leading to quantum mechanics exemplify the first case; the conflict between special relativity and Newtonian gravitational theory leading to general relativity exemplifies the second, rarer, case. At any rate, the problems of theoretical physics are objectively given; and, while the criteria which govern the exploitation of a success are, as I indicated earlier, mainly aesthetical, yet the portion of the problem, and that which I called above the original "break-through," are hard, objective facts. Accordingly, the subject of theoretical physics was at almost all times enormously concentrated; at almost all times most of the effort of all theoretical physicists was concentrated on no more than one or two very sharply circumscribed fields—quantum theory in the 1920's and early 1930's and elementary particles and structure of nuclei since the mid-1930's are examples. The situation in mathematics is entirely different. Mathematics falls into a great number of subdivisions, differing from one another widely in character, style, aims, and influence. It shows the very opposite of the extreme concentration of theoretical physics. A good theoretical physicist may today still have a working knowledge of more than half of his subject. I doubt that any mathematician now living has much of a relationship to more than a quarter. "Objectively" given, "important" problems may arise after a subdivision of mathematics has evolved relatively far and if it has bogged down seriously before a difficulty. But even then the mathematician is essentially free to take it or leave it and turn to something else, while an "important" problem in theoretical physics is usually a conflict, a contradiction, which "must" be resolved. The mathematician has a wide variety of fields to which he may turn, and he enjoys a very considerable freedom in what he does with them. To come to the decisive point: I think that it is correct to say that his criteria of selection, and also those of success, are mainly aesthetical. I realize that this assertion is controversial and that it is impossible to "prove" it, or indeed to go very far in substantiating it, without analyzing numerous specific, technical instances. This would again require a highly technical type of discussion, for which this is not the proper occasion. Suffice it to say that the aesthetical character is even more prominent than in the instance I mentioned above in the case of theoretical physics. One expects a mathematical theorem or a mathematical theory not only to describe and to classify in a simple and elegant way numerous and a priori disparate special cases. One
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also expects "elegance" in its "architectural," structural makeup. Ease in stating the problem, great difficulty in getting hold of it and in all attempts at approaching it, then again some very surprising twist by which the approach, or some part of the approach, becomes easy, etc. Also, if the deductions are lengthy or complicated, there should be some simple general principle involved, which "explains" the complications and detours, reduces the apparent arbitrariness to a few simple guiding motivations, etc. These criteria are clearly those of any creative art, and the existence of some underlying empirical, worldly motif in the background—often in a very remote background—overgrown by aestheticizing developments and followed into a multitude Of labyrinthine variants—all this is much more akin to the atmosphere of art pure and simple than to that of the empirical sciences. You will note that I have not even mentioned a comparison of mathematics with the experimental or with the descriptive sciences. Here the differences of method and of the general atmosphere are too obvious. I think that it is a relatively good approximation to truth—which is much too complicated to allow anything but approximations—that mathematical ideas originate in empirics, although the genealogy is sometimes long and obscure. But, once they are so conceived, the subject begins to live a peculiar life of its own and is better compared to a creative one, governed by almost entirely aesthetical motivations, than to anything else and, in particular, to an empirical science. There is, however, a further point which, I believe, needs stressing. As a mathematical discipline travels far from its empirical source, or still more, if it is a second and third generation only indirectly inspired by ideas coming from "reality," it is beset with very grave dangers. It becomes more and more purely aestheticizing, mure and more purely Vart pour Part. This need not be bad, if the field is surrounded by correlated subjects, which still have closer empirical connections, or if the discipline is under the influence of men with an exceptionally well-developed taste. But there is a grave danger that the subject will develop along the line of least resistance, that the stream, so far from its source, will separate into a multitude of insignificant branches, and that the discipline will become a disorganized mass of details and complexities. In other words, at a great distance from its empirical source, or after much "abstract" inbreeding, a mathematical subject is in danger of degeneration. At the inception the style is usually classical; when it shows signs of becoming baroque, then the danger signal is up. It would be easy to give examples, to trace specific evolutions into the baroque and the very high baroque, but this, again, would be too technical. In any event, whenever this stage is reached, the only remedy seems to me to be the rejuvenating return to the source: the reinjection of more or less directly empirical ideas. I am convinced that this was a necessary condition to conserve the freshness and the vitality of the subject and that this will remain equally true in the future.
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METHOD IN THE PHYSICAL SCIENCES JOHN VON NEUMANN Professor of Mathematics Institute of Advanced Studies
Emphasis on methodology seems most often to arise when there are symptoms of trouble, when a realization of difficulties makes necessary a re-examination of some position inherited from the past. Because traditional attitudes in the sciences seem to have been firmer and more self-assured than in other disciplines, there has perhaps been less searching of the scientist's conscience and, therefore, less concern with methodology on his part. Yet he has not been without concern, for there have been within the experience of people now living at least three serious crises — or reverberations of earlier crises — which have caused him to reorientate his thinking. We can use these crises as prototypes for reference, and we can calibrate our statements with their help. There have been two such crises in physics — namely, the conceptual soul-searching connected with the discovery of relativity and the conceptual difficulties connected with discoveries in quantum theory. In the case of relativity, the crisis was brief but violent. The second persisted over a longer period, during the almost thirty years in which the quantum theory took shape. The third crisis was in mathematics. It was a very serious conceptual crisis, dealing with rigor and the proper way to carry out a correct mathematical proof. In view of earlier notions of the absolute rigor of mathematics, it is surprising that such a thing could have happened, and even more surprising that it could have happened in these latter days when miracles are not supposed to take place. Yet it did happen. Concerning the crisis in mathematics, Hermann Weyl, who had a much more direct part in it, can speak with more authority than I. Published in "The Unity of Knowledge", ed. L. Leary (1955), pp. 157-164; and also John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 491-498.
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Therefore my discussion will be limited to the two crises in physics — and on these I shall be less specific about conceptual revisions because Niels Bohr has already touched upon this subject in his essay. I will further limit myself to saying a few things about procedure and method which will illustrate the general character of method in science. Not only for the sake of argument but also because I really believe it, I shall defend the thesis that the method in question is primarily opportunistic — also that outside the sciences, few people appreciate how utterly opportunistic it is. I To begin, we must emphasize a statement which I am sure you have heard before, but which must be repeated again and again. It is that the sciences do not try to explain, they hardly even try to interpret, they mainly make models. By a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work — that is, correctly to describe phenomena from a reasonably wide area. Furthermore, it must satisfy certain esthetic criteria — that is, in relation to how much it describes, it must be rather simple. I think it is worth while insisting on these vague terms — for instance, on the use of the word rather. One cannot tell exactly how "simple" simple is. Some of the theories that we have adopted, some of the models with which we are very happy and of which we are very proud would probably not impress someone exposed to them for the first time as being particularly simple. Simplicity is largely a matter of historical background, of previous conditioning, of antecedents, of customary procedures, and it is very much a function of what is explained by it. If the amount of material which is unambiguously explained — that is, explained with no added interpretations or commentaries — is extremely extensive, if it is also very heterogeneous, if one has clearly explained a large number of things in very different areas, then one will accept a good deal of complication and a good deal of deviation from stylistic beauty. If, on the other hand, only relatively little has been explained, one will absolutely insist that it should at least be done by very simple and direct means. It must also be said that the criterion, that a lot should be explained, has to be applied with a good deal of sophistication. Indeed, some of the nuances of all
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these requirements can probably only be appreciated intuitively. The ability to describe — or to predict — correctly is important in such a model, but it need not be decisive per se. Also, in scientific prediction it does not matter enormously whether prediction occurs before or after the fact. Of course, it must be correct. However, as I mentioned above, it is considered very important that the material which has been correctly described or predicted should be heterogeneous. Let me analyze this requirement in somewhat more detail. If possible, the confirmation should not all stem from one area alone. In this sense, it is considered particularly significant to find confirmations in areas which were not in the mind of anyone who invented the theory. Thus, if you discover that the theory, which was necessitated by difficulties in one area, describes things correctly in entirely different areas, this is highly significant. It is even more important, if things have not been previously very harmonious in these latter areas and there was no sense of optimism about them. In this regard, the enormous authority of quantum mechanics is typical. It was probably strongly conditioned by the fact that quantum mechanics came into being because of various difficulties in spectroscopy and of various other problems of atoms and molecules which are variously connected with spectroscopy, but that it was then suddenly found capable of describing or predicting correctly various things in chemistry, in solid-state physics, and even to have some bearing on epistemology. These were hardly on anyone's mind at the beginning. Similar considerations apply to Newtonian mechanics and its still more monumental degree of authority. The latter is largely due to the fact that the Newtonian system was introduced in order to describe the behavior of the sun's planets. It then turned out that it also described, with only small and perfectly plausible additions, many things in extensive areas in very varied parts of physics. There are also other aspects of the matter which must be kept in mind. It is important that the phenomena which are correctly described should vary considerably, not only qualitatively, but also in their quantitative aspects. Thus it is one of the most impressive traits of Newtonian theory, the classical theory of gravity, that it explains phenomena on the human scale as well as on the planetary scale. And many outside the sciences are not aware of how limited are the scales on which theories usually work. The ratio of the linear sizes of the largest and the smallest objects that have figured in physical theory — the
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hypothesized universe on the one hand and the smallest particles on the other — is about 1040. In other words, all our physical experience, no matter how recondite, is covered in its linear scale by 40 powers of 10. This amounts to 133 powers of 2-133 octaves. No theory to data has had something valid to say all along the scale. Any theory which can make statements referring to widely separated portions of the scale enjoys very great authority, even if the statements are quite weak. For the Newtonian system, confirmation was developed over 25, or possibly 30 powers of 10 along this scale. For most other existing theories, the area of confirmation in this sense is still more restricted. II In evaluating what these models do, one should also emphasize how little of directly interpretive element need be attached to them. In this respect, it is instructive to look at a classical example. In other areas, even in some which are within science — for instance, biology — it is, or was, considered very important to which one of two major types the view that one takes of the area belongs. Specifically, whether the view is causal or teleological. In using the word causal, I do not have the contrast of causal and statistical in mind, but the other contrast of causal and teleological. Causal means that if you know the state of the system now, then you can use this knowledge to predict its state immediately thereafter. Immediately means a very short time; the prediction may not be exact for any finite time, but the shorter the time, the more exact it gets, and that at an accelerated pace, so that it can be extended by the usual process of integration. Thus, one can extend such a prediction by successive steps to any point in the future with any desired degree of precision. Hence, complete knowledge of the system now permits one to calculate unambiguously everything about it at any time in the future. In most causal systems one can also proceed similarly to any time in the past. This is one of the major ways of looking at nature. Classical Newtonian mechanics is usually quoted as the archetype of this kind of insight and procedure. Under this dispensation, if you know the state of a system now, you can calculate what it will be at any moment thereafter and also, usually at any moment before. One has to be careful, however, in defining the concept of a state. The state is specified if one has a complete description. However, one must consider that this is to a
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certain degree begging the principle, since by a complete description one means one which comprises precisely as much information as is needed in order to perform the causal progression to the future. In classical mechanics one knows how much information such a complete description must contain. One has to know, not only where all parts of the system are (all coordinates), but also how rapidly these are moving (all velocities). Then classical mechanics permits calculations of what positions and velocities it will have at any later time. One needs precisely these positions and these velocities. Nothing less will do, and there is no need for other things that might, a priori, seem equally important, like accelerations. The reason why a state in classical mechanics is described by specifying position and velocity, and not position alone, or not position and velocity and certain accelerations, is of course that the Newtonian system is closed just at this point. It is just this amount of information, position plus velocity, which is hereditary in that theory and which can be propagated into the future by unambiguous calculations. Another aspect is the teleological one. Here one has to take a whole expanse of the history of the system, between two moments which are definitely apart in time, for example, between now and an hour from now, or between now and a trillionth of a second from now, or now and a millennium from now. Taking such a finite stretch of history as the subject of inquiry, a teleological theory asserts that this entire historical process must satisfy certain criteria which are usually stated in terms of optimizing (maximizing) a suitable function of the process. The use of the word optimizing again illustrates the opportunism that even reflects itself in the terminology. By optimizing one only means that one makes some quantity as large as possible. Whether that quantity is particularly desirable or not does not matter. By changing its sign one could transform the criterion in making it as small as possible. Thus, optimizing, maximizing, and minimizing are all neutral mathematical terms, to be substituted for each other on the basis of mathematical convenience and taste. At any rate, by a single optimization, that is, a single maximization, the total history between two points in time is determined. The real course of events turns out to be that one for which the particular quantity referred to above is made as large as possible. In other words, one develops a complete historical evolution in a single act, by a single insertion between the known points at the beginning and at the end. It is
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not developed stepwise, progressing from the beginning forward in time, as it would be in a causal theory. This contrast is very well known from biology. It is also familiar in a number of fields increasingly removed from science. It is usually considered as a very fundamental contrast: the causal and the teleological procedures are viewed as mutually exclusive, as highly antithetical ways of explaining phenomena. It is therefore very important and very characteristic that in science there need not be any meaningful difference between these two descriptions. Indeed, in classical mechanics there are two absolutely equivalent ways to state the same theory, and one of them is causal and the other one is teleological. Both describe the same thing, Newtonian mechanics. Newton's description is causal and d'Alembert's description is teleological. This has been known for well over two hundred years. All the difference between the two is a purely mathematical transformation. In principle such a transformation is no more profound than choosing to say four instead of saying two times two. In other words, by purely mathematical manipulation one can show that each of these two ways gives exactly the same results as the other. Thus whether one chooses to say that classical mechanics is causal or teleological is purely a matter of literary inclination at the moment of talking. This is very important, since it proves, that if one has really technically penetrated a subject, things that previously seemed in complete contrast, might be purely mathematical transformations of each other. Things which appear to represent deep differences of principle and of interpretation, in this way may turn out not to affect any significant statements and any predictions. They mean nothing to the content of the theory. Ill Thus we have an example where alternative interpretations of the same theory are possible, but where the question of whether one uses one or the other is decided in a manner quite different from what is generally believed to be the valid way. Indeed, the criterion is one of mathematical convenience or taste. There is also another example where this is the case, but only up to a certain point: beyond that point serious, substantively relevant differences of interpretation arise. The example is quantum mechanics. I will limit myself to that part of the theory which refers to the electronic
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shells of the atoms. For these a theory is known which seems to be entirely satisfactory at present. This theory can be described in two different ways which differ quite importantly, somewhat in the manner of the causal and teleological interpretations of Newtonian mechanics discussed above, though the difference in this case is not quite as striking and profound as there. The two descriptions are, first, the original procedure of Erwin Schrodinger which describes this part of quantum mechanics by an analogue with optics, and second, the method of Werner Heisenberg which describes this area in completely probabilistic terms. Since these descriptions were first formulated, a great deal of work has been done on both and they have been further elaborated. In the process it was demonstrated that they are mathematically equivalent. The prevalent taste is today, and has been for more than twenty years, rather in favor of one of the two interpretations, namely, the statistical one. (It must be said, however, that there have been in the last few years some interesting attempts to revive the other interpretation.) It was, moreover, quite clear all along, that ultimately the motive for choosing one or the other attitude would be connected with the fact that quantum mechanics, in spite of all its successes, is contiguous with areas in which the theory is not satisfactory, specifically, with the quantum theory of electrodynamics and subsequently with the quantum theory of particles like mesons and their successors. About all of these we know a great deal less than about the original area of quantum mechanics, and we are here in the midst of grave difficulties. The reason for preferring one version of quantum theory over the other has usually been the intuitive hope that one or the other would give better heuristic guidance in extending the theory into those areas which are not yet properly explained or not yet properly theoreticized and controlled. Throughout the last twenty years this has been prevalently believed to be a matter of finding correct formal extensions of the existing theory. If this ultimately proves to be the case, it will determine the final choice. Questions of form, even when the mathematical contexts are equivalent, can therefore have great heuristic and guiding importance, and in the end determine the outcome. There have been some individual exceptions to this rule. Some physicists certainly had definite subjective preferences for one description or the other. However, there can be hardly any doubt that scientific "public opinion" in the end will only accept that variant which succeeds
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in pointing the way to explaining wider areas with greater power. In other words, while there appears to be a serious philosophical controversy between the interpretations of Schrodinger and Heisenberg, it is quite likely that the controversy will be settled in quite an unphilosophical way. The decision is likely to be opportunistic in the end. The theory that lends itself better to formalistic extension towards valid new theories will overcome the other, no matter what our preference up to that point might have been. It must be emphasized that this is not a question of accepting the correct theory and rejecting the false one. It is a matter of accepting that theory which shows greater formal adaptability for a correct extension. This is a formalistic, esthetic criterion, with a highly opportunistic flavor.
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Impact of Atomic Energy on the PHYSICAL and CHEMICAL SCIENCES In the Long
Run, the By~Products
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By JOHN VON NEUMANN In opening the Alumni Day symposium (June 13,1955) on the topic of "The Impact of Atomic Energy on the Physical and Chemical Sciences" Dr. von Neumann spoke extemporaneously', without benefit of prepared manuscript or extensive notes. The following article is a summary which reflects the essence of the address.
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N examining the impact of atomic energy on the physical and chemical sciences, it is well to begin by asking a few pertinent questions. For example, w e may ask ourselves, "What situation are we in as a result of progress in nuclear science and the tech nology which made the large-scale release of atomic energy possible?" Certainly we should seek an answer to the question, "How can we evaluate properly the role of the new process of nuclear fission which mod ern physics has placed at our disposal?" Or, again, we might ask ourselves, "How has progress in nuclear physics affected the development of other, older, fields in the sciences?" Finally, recognizing that nu clear fission has placed the scientists in the position of co-operating closely with administrators and the mili tary, w e might well ask, "How must scientists and engineers adapt themselves to the many new situa tions which have come about by the development of the new nuclear technology?" There is no denying that the process of nuclear fission has become most conspicuous by certain direct effects that it produced, particularly in the military sphere, but it is well to remember that the spectacu lar explosions that w e all remember represent but part of the total effects of nuclear fission — one which may, in the long run, turn out to be the lesser part. TTiere are many indirect, and not easily predicted, effects that also take place, and these are of enormous importance, even though they may not be, immedi ately, so spectacular. In some sense, nuclear fission is not one of those developments in physics which arose logically and systematically in the course of progress. There was a great deal of accident and surprise in the process. Also, the history of physics provides hardly any paral lel to the discovery of nuclear fission, either in the magnitude of the disruptive forces which have been unleashed, or in the magnitude of the social, eco nomic, military, and cultural adjustments w e must
I
make as a result, or finally in the rapidity with which all these effects evolved and made themselves felt. Man had no adequate warning, by which he might have prepared himself, systematically, to accept the full implications of the tremendous release of energy which comes about when matter is converted into work. Of course, we have devised and used other significant forms of energy in the past and, in a way, we might say that ultimately nearly all energy comes from atomic reactions of one kind or another. Never theless, scientists were not prepared to answer the myriads of questions that suddenly came to the fore front with the first nuclear explosion in 1945, and with its successors during the next decade, in their rapidly increasing sizes. Also, it begins to appear that the release of energy is not the most remarkable, or the most dangerous, manifestation of the nuclear reactions that we can now run on a massive scale. The production of radioactivity and of all sorts of nuclear transmutations may prove to be even more significant. Uranium Concentrations We tend to think of atomic energy in terms of uranium — especially uranium 235, which is present in various parts of the world. The concentrations of natural uranium, in the areas in which it is found, vary from a few per cent to a few parts in a million; the concentration of U 235 in it is uniformly two-thirds of 1 per cent. The key to the entire development was U"5; the other important fissionable materials, plutonium and U 288 , can only be produced with the di rect or indirect help of U 235 . Now, the concentration of U 2 " in ordinary uranium is not controlled by any absolute and time-conserved law. Both ordinary uranium (U 238 ) and U 235 undergo radioactive decay, and U 235 decays faster than U 238 . In a universe in which, as w e believe, the heavy elements have been formed about 10 billion years ago, the concentration of the faster-decaying U 285 has by now decreased to the above mentioned two-thirds of 1 per cent in ordi nary uranium. If man and his technology had appeared on the scene several billion years earlier, the concen tration of IT" would have been higher, and its sepa ration easier. If man had appeared later — say 10 bil lion years later — the concentration of U2** would have been so low as to make it practically unusable. In this case, many of the opportunities, as well as the prob-
520 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 520-522.
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PHYSICAL A N D CHEMICAL SCIENCES lems, which surround us now would have been post poned and transformed in a way that is hard to evaluate. The process of fission itself is unusual, and this fact alone has presented scientists with a number of obstacles that are not normally encountered. The chemical elements may be arranged systemati cally in a table according to their atomic weights. This arrangement is known as the "Periodic Table of Mendeleyev." The elements of middle atomic weigiht occupy the center of this periodic table and are the more stable ones. Elements of very small atomic weight, at one end of the periodic table, can usually be combined to produce the heavier medium ele ments, and they release energy in this process (be cause the medium elements are the stabler ones, as mentioned above). On the other hand, the elements of large atomic weight, at the opposite end of the periodic table, can be broken u p into elements of medium weight, and they release energy in this break-up process (again, because the medium ele ments are the stabler ones). Thus, the light elements can be merged — fused — with a gain of energy, to form stabler heavier elements; and the heavy ele ments can be broken down — fissioned — with the release of energy again, to form stabler medium ele ments. These are the two energy-producing nuclear processes: the fusion of the lighter elements, and the fission of the heavier ones. (Actually, the element usually formed in fusion is Helium-4, an excep tionally stable light element, but I need not go into this now.) Fission
and
Fusion
The fusion of the light elements was foreseen in detail for some considerable time. The fission of the heavy elements, known to be a possibility in prin ciple, was, nevertheless, unsuspected as a practical matter prior to 1939. In fact, so little credence was given by physicists to the possibility of fission, that nuclear fission was discovered experimentally five years before it was recognized as such and the ex periments correctly diagnosed. I t was only after every other possibility of explaining the appearance of some unusual disintegration products of t h e bom bardment of natural uranium by neutrons had failed to explain experimental observations — the difficulties were mainly connected with explaining the chemical properties of the nuclear fragments produced — that physicists came to the conclusion that fission had actually taken place. After the developments of the early 194Cs, which m a d e it clear how enormously important uranium was to b e in nuclear technology, geologists and others began an intensified search for uranium deposits. As a result, we now know that uranium is not so rare in t h e strata near the earth's surface as had formerly been thought T h e greater than anticipated availa bility of uranium in itself served as a stimulus to further developments in nuclear technology. T h e underlying nuclear science has also developed at a very accelerated pace. W e know today a great deal more about nuclear reactions in this area and in al lied areas than one might have expected 15 years ago.
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Nuclear
The knowledge, resources, and instrumentalities which have come into being as the result of our study of nuclear fission and other atomic (or rather subatomic) phenomena are being put to good use in the study of many other physical processes. Perhaps this land of by-product is even more important, in the long run, than all the direct knowledge we have gained from the study of the violent fission reactions by which nuclear matters are most popularly known. The great developments of nuclear physics pro ceed in the direction of investigating simple (light) elements and subnuclear particles. Thus, the direct impact of nuclear fission which takes place at the other (heavy) end of the periodic table is less signifi cant than the indirect impact which comes from a better understanding of the nuclear forces and ele mentary particles in nature. Nuclear reactors which have been built in various parts of this country — and in various parts of the world — now make it possible to obtain an ample source of elementary particles and of all nuclear species — by transmutation — which were entirely beyond the scope of the boldest imagi nation of 15 years ago. The availability of ample sources of neutrons is especially important. This is indeed a great step forward because it is largely through the use of uncharged neutrons that we are now able to investigate the inner structure of nuclear particles and to perform the classical purpose of al chemy — massive transmutation of nuclear species, that is, of elements, into each other. Before this, we had only charged pp.rticles to use as projectiles in our efforts at smashing, transforming, or analyzing atoms. The use of such charged particles required very large energies, that is, very high voltages, for their acceleration; and charged particles could not be easily or well aimed to make hits at the deep core of atoms; that is, one had to make use of b r u t e force methods in all these procedures as long as one was limited to the use of charged particles only. Now that there are ample supplies of uncharged neutrons which can penetrate the deepest recesses of an atomic nucleus with hardly any difficulty, physicists have been able to perform breakdowns, transformations, and structure studies with a much greater ease than was previously possible. There is another important by-product of research in atomic physics. By means of techniques developed through nuclear science, and through the instrumen talities of nuclear technology, w e now have the possi bility of effecting many transmutations of elements. W e are also able to make almost any element radio active and, further, have a considerable choice of decay times as w e l l I n this way, w e have access to a wide range of radioactive properties. These may b e used for examining the behavior of many physi ological and industrial processes which could not b e satisfactorily studied by other means. Studies of friction and wearing of metal parts, as in internal combustion engines, or the tracing of metabolic substances through die human body b y means of radioactive tracer elements, as well as many other things in wide ranges of science and technology, may
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be cited as examples of these new and very useful techniques. There are still other interesting results flowing from the recent rapid advances in nuclear matters. Thus, for some time, but especially since the begin ning of World War II, progress in physics has been stimulated by the fact that physicists had frequently worked together in teams, and that such teams often included men from other natural sciences — one field of science cross-fertilizing another. Some of this teamwork was made necessary by the need to bring several different disciplines to bear on a single large problem. But frequently such teamwork was forced upon scientists because the size and cost of the equip ment and apparatus required for modern research made group effort essential. While we have certainly benefited from such co-operative ventures, the cost and complexity of modern research equipment has posed very serious problems, often very unaccus tomed to the workers in these areas. Cost of
Research
Thus, large particle accelerators cost millions of dollars and years to construct, so that we have very few such instruments, as compared to, say, micro scopes. Co-operation is needed in the capitalization, design, construction, use, and maintenance of such large research apparatus. In the construction of a large accelerator, one is faced with the problem of whether it is possible to justify a large expenditure of capital, which, in addition, will only bear fruit half a decade later, at which time both the problems and the available methods may have shifted. Thus one has to ask whether science will not have pro gressed so far by the time the instrument has been built that it might be obsolete and, therefore, a poor investment. The need for raising funds for research facilities certainly is not new. But the need for under writing and obtaining capital funds on as large a scale as is now necessary in some areas for scientific research of significance, and to plan for long periods ahead of time, is new to scientists as well as admin istrators of educational and scientific projects. In this.regard, the developments in nuclear science have had an enormous additional effect on all of us who are involved in these fields. W e have acquired much more routine in evaluating and organizing team-work, in assessing the desirability of large and long-range material commitments, and so on. So far, I have discussed only the effect of nuclear reactions on the professional work of the physicists; but other groups have been influenced with equal intensity. We all know that nuclear fission has al ready revolutionized many military areas of opera tion and that it has necessitated tremendous effort and expense to build up and develop a military or ganization which is able to meet and overcome a modern atomic-powered military machine. However, even greater than its impact on the mili tary organization is the impact which it has had in changing the thinking and lives of the civilian pop ulation. Nuclear science has, in fact, affected greatly our way of thinking about our civilization.
Scientists who made the control and release of atomic energy possible were among the first to feel the changes which this astounding development en tailed. They are no longer free to carry on their re search in isolated "ivory towers" completely free from the need for accounting for the possible uses of their discoveries. They are a very decisive part of our atomic age civilization. For the first time, they are, of necessity, concerned with problems of security and national welfare on a large scale and in a way never before encountered by them. They have to think and be guided in many operations much as military men had to think and be guided in former periods; and they are not accustomed to what seems to them to be undue regimentation. They need to develop, there fore, new habits and techniques. They now have new and vast responsibilities for which they were in no way prepared. Like every radical and unexpected adaptation which, in addition, has to be carried out in a hurry, it is painful, disconcerting, and accompanied by violent emotional fluctuations. But, by and large, the adaptation takes place with an admirable speed, especially if one considers all the factors that inter vene and all the difficulties I have tried to indicate. Scientists
in Other
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Pure science is often abstruse, and yet scientists may today be called upon to fill positions of consid erable responsibility in fields outside their profes sional area of competence. They may become admin istrators, they may have to influence public opinion; all in all, they have great social responsibilities. We must expect that other phases of abstract thinking, other than physics and chemistry, may also ultimately evolve into similar roles; that is, they may assume military, economic, and more generally social roles of equally tempting, compelling, and dangerous as p e c t Science and scientists have become affected with the public interest in a new way and in orders of magnitude that were never imagined a half cen tury ago. Scientists, and physicists in particular, have had to undergo a new kind of adjustment and disci pline. We must develop procedures and institutions to meet the new adjustments with which we are con fronted. The adjustment will be painful in the future, as it has been troublesome and painful in the past. There is no easy way out of this situation, but with intelligence and good will some satisfactory way can and must be found. The social responsibility of scientists has been vastly increased since the first chain reaction was set off in Chicago in 1942. The responsibility of sci entists has grown especially in the field of interna tional relations. We must recognize that the educa tion of the scientist of the future is not complete as long as it is limited to his technical professional sub jects; he must know something of history, law, economics, government, and public opinion. Our task is to make the adjustment to new conditions as satisfactory as possible. We must do this intelligently and promptly. But we must do it without endanger ing the foundations upon which the sciences them selves rest and thrive.
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THE IMPACT OF RECENT DEVELOPMENTS IN SCIENCE ON THE ECONOMY AND ON ECONOMICS By J. VON NEUMANN
Dr. John von Neumann, member of the United States Atomic Energy Commission, was the luncheon speaker at the December 12,1955, Washington D.C. meeting of the National Planning Association. Below is a partial text of Dr. von Neumann's talk: has been a great deal of talk, much of it well founded, that the effect of science on economics and on the economy has not only been very large but that something like a second industrial revolution is impending. Illustrating this are the enormous advances in communications—physical and informational—ad vances in automatization and in the domain of information and control, and finally, atomic energy. Well, it may be that these things will completely revolu tionize our economy, but one must be somewhat sober in evaluating what has already happened. Consideration of what has happened so far indicates a slowing down of evolution. In other words, where the economies of the major industrial countries eight years ago expanded at a rate of seven per cent per annum, economic activity is now measured at a rate more like three to five per cent per annum. We know what the reasons are, roughly. The further we progress, the more difficult further acceleration becomes, but nevertheless, it is true that there has been additional acceleration in certain, particular fields. We can first consider the effect of scientific progress in the field of gathering information. Second, we can observe its effect on decision-making. It is perfectly clear that we can assemble information which is more elaborate than ever before, and in larger quantities. In decision-making, the situation is somewhat different. There have been developed, especially in the last decade, theories of decision-making—the first step in its mechanization. However, the indications are that in this area, the best that mechanization will do for a long time is to supply mechanical aids for decision-making while the process itself must remain human. The human intellect has many qualities for which no automatic approximation exists. The kind of logic involved, usually described by the word "intuitive", is such that we do not even have a decent description of it. The best we can do is to divide all processes into those things which can be better done by machines and those which can be better done by humans and then invent methods by which to pursue the two. We are still at the very beginning of this process. Thus decisions in economic operations are made half by machine and half by a human. The two shares are intermeshed. For trying out new methods in these areas, one may use simpler problems than economic decision-making. So far, the best examples of this have been achieved in military matters—control of large THERE
100 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 100-101.
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numbers of units, control of interception in aerial combat, and the like. I think that in the application of automatic machines, the experience in the mihtary sphere will turn out to be very important. Now let us turn to the uses to which scientific methods can be applied. With regard to the application of the scientific method in economics, it is important to see which difficulties are real and which are only apparent. It is frequently said that economics is not penetrable by rigorous scientific analysis, because one cannot experiment freely. One should remember that the natural sciences originated with astronomy, where the mathematical method was first applied with overwhelming success. Of all the sciences, astronomy is the one in which you can least experiment. So the ability to experiment freely is not an absolute necessity. Experimentation is a convenient tool, but large bodies of science have been developed without it. It is also frequently said that in economics one can never get a statistical sample large enough to build on. Instead, time series are interrupted, altered by gradual or abrupt changes of conditions, etc. However, if one analyzes this carefully, one realizes that in scientific research as well, there is always some heterogeneity in the material and that one can never be quite sure whether this heterogeneity is essential. The decisive insights in astronomy were actually derived from a very small sample: The known planets, the sun, and the moon. What seems to be exceedingly difficult in economics is the definition of cate gories. If you want to know the effects of the production of coal on the general price level, the difficulty is not so much to determine the price level or to determine how much coal has been produced, but to tell how you want to define the level and whether you mean coal, all fuels, or something in between. In other words, it is always in the conceptual area that the lack of exactness lies. Now all science started like this, and economics, as a science, is only a few hundred years old. The natural sciences were more than a millenium old when the first really important progress was made. The chances are that methods in economic science are quite good, and no worse than they were in other fields. But we will still require a great deal of research to develop the essential concepts—the really usable ideas. I think it is in the lack of quite sharply defined concepts that the main difficulty lies, and not in any intrinsic difference between the fields of economics and other sciences.
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T H E ROLE OF MATHEMATICS IN T H E SCIENCES A N D IN SOCIETY A. VON NEUMANN, Professor of Mathematics, The Institute for Advanced Study, Princeton, N J .
DR. JOHN
I should really talk about the probable developments of Mathematics in the not too distant future. During the pres entation of the previous paper I greatly admired and envied Professor Spitzer who in his own field could do this; he could talk about the probable developments in Astronomy to a general scientific and scholarly audience, without getting into things, which have a strong appeal for astronomers, but do not yet have an appeal for the general public. In astronomy this is possible. In mathematics this is very difficult. If one starts to talk about the substantive subject matter of mathematics, quire particularly when speculating about the future, one gets very quickly into things which will evoke response only among mathematicians. I will therefore orient myself differently and talk about the role of mathematics in intellectual life and in society. Right at the beginning one has to answer a question that actually poses itself in all branches of science, and in all branches of scholarship. However, in mathematics it faces you in a particularly definite and extreme form. This is the ques tion as to how useful mathematics is; how useful this useful ness is; how important usefulness is; whether science shall be pursued per se or whether it should be pursued in its relation to use in society. A great deal can be said about this subject. I think that the best that one can do in this regard in ten min utes is to point out how difficult it is, and how dangerous it is, to make snap judgments about it. Let me quote you an epigram of the German poet Schiller. He describes a fictitious conversation between Archimedes and a disciple. The disciple expresses to the Master his ad miration for science and wants to be initiated into "that 477 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 477^90.
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divine science that had just saved the State," meaning the techniques which helped in the siege of Syracuse by the Ro mans. I mean they helped the Syracusan in a siege by a Ro man army. Archimedes thereupon gives a somewhat stuffy speech in which he points out to the admirer that science is divine, but that she was divine before she helped the State; and that she is divine independently of whether she helped the State or not. Now this position is quite important and pertinent. Science is probably not one iota more divine because she helped the State or Society. However, if one subscribes to this position, one should at the same time contemplate the dual proposi tion, that if science is not one iota more divine for helping society, maybe she isn't one iota less divine for harming so ciety. T h e question is not at all trivial. A final point to con sider in this conference is also that science is not one iota less divine, although she absolutely failed to save the State, because Syracuse was in fact taken by the Romans shortly afterwards. So I shall talk on this question of usefulness—in spite of all the difficulties of evaluating in this context the importance of usefulness in every-day life, of usefulness to Society, without discussing where the place of mathematics in Society is, and what effects it has on us in general; and quite particularly, what effects it may have outside the group of professionals. It is also quite interesting to consider what effects it has within the group of professionals. T h e effects within the group of professionals are quite different from what one might think. As far as the general and external effects are concerned, it is perfectly clear that mathematics furnishes something that is quite important, namely that it establishes certain standards of objectivity, certain standards of truth; and it is quite important that it appears to give a means to establish these standards rather independently of everything else, rather independently of emotional, rather independently of moral, questions. It is quite important to achieve this reali zation: That objective criteria of truth are possible, that such an aim is not self-contradictory, not in some sense inhuman.
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This insight is neither obvious nor particularly ancient; and this very prestige of logic per se, of science per se, is probably connected with the role of science in our lives, and with the role of mathematics, in its completely abstract form, in sci ence. Again, the intrinsic truth of these propositions may even be debatable, but it is quite important that the propositions can be made at all, that one can make a precise and detailed picture of their content. This is possible, because one can form, with the help of mathematics, an image of what such a system would have to look like. In other words, quite apart from the question of whether these objective standards of truth given by mathematics are really objective, and whether or not these standards are really true, one can talk much more sense about this subject after one has experienced directly and in vivo what such a system would look like if it existed at all. There are a number of mathematical examples to which we can refer for this purpose. How can these references be specifically implemented? Also: Even if the implementation is not immediately successful, exactly what kind of a system of ideas is it in which such extreme propositions are valid? A great deal more can be said about this subject, and about this role of mathematics in establishing the possibility of ob jective standards. Let me say at once what the objections against this are. T h e objection, that even if absolute standards could be established by mathematics, they could not have absolute validity for the whole world, this has been discussed plenty; and I don't think that I can tell you much new about it. I think we have all faced this problem, and all have various methods to deal with it, whether we are satisfied with them or not. I want to point out, however, and this is a more tech nical matter, that the underlying propositions as to whether the standards of mathematics are truly objective, can also be doubted. In other words it is not necessarily true that the mathematical method is something absolute, which was re vealed from on high, or which somehow, after we got hold of it, was evidently right and has stayed evidently right ever
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since. T o be more precise, maybe it was evidently right after it was revealed, but it certainly didn't stay evidently right ever since. There have been very serious fluctuations in the professional opinion of mathematicians on what mathematical rigor is. T o mention one minor thing: In my own experience, which extends over only some thirty years, it has fluctuated so considerably, that my personal and sincere conviction as to what mathematical rigor is, has changed at least twice. And this in a short time of the life of one individual! If you take the whole period, say from the beginning of the eighteenth century, there have been further serious fluctuations as to what constitutes a strict mathematical proof. The great analyticists of the late eighteenth century ac cepted as mathematical proof things that we would absolutely not accept as such. It is true that they accepted these with a certain sense of guilt; but in many cases the sense of guilt was not overly evident. Also it is certainly true that in the nine teenth century there were bona fide disagreements as to whether a particular proof given by a very great mathema tician, Riemann, was really a proof or not. In my own experience, on two other occasions in the early twentieth century, there were very serious substantive discus sions as to what the fundamental principles of mathematics are; as to whether a large chapter of mathematics is really logically binding or not. And in the nineteen-tens and -twen ties a critique of these questions made it apparent, that it was not at all clear exactly what one means by absolute rigor, and specifically, whether one should limit oneself to use only those parts of mathematics which nobody questioned. Thus, re markably enough, in a large fraction of mathematics there actually existed differences of opinion! Some mathematicians said that one need not question any part of what is in fact being used. There was also a body of opinion, that one should not use more than what the most exacting critics had ap proved. However, there was a further, large body of mathe maticians, who felt that while there was some point in ques tioning certain areas of mathematics, it was all right to use them. This group was quite ready to accept something like
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this: Those portions of mathematics which had been ques tioned and which had been clearly useful, specifically for the internal use of the fraternity—in other words, when very beautiful theories could be obtained in those areas—that those were after all at least as sound as, and probably some what sounder than, the constructions of theoretical physics. And after all, theoretical physics was all right; so why shouldn't such an area, which had possibly even served theo retical physics, even though it did not live up to 100 per cent of the mathematical idea of rigor, why shouldn't this be a legitimate area in mathematics; and why shouldn't it be pur sued? This may sound odd, as well as a bad debasement of standards, but it was believed in by a large group of people for whom I have some sympathy, for I'm one of them. I do not want to go into the details of this critique; it is connected with the very difficult epistemological question as to whether it is legitimate to discuss collectives of entities which are not finite in number; or, if you are dealing with a collective of mathematical concepts which is infinite, exactly what it means to make a general statement about it, exactly what it means to say that you know that something is possible in such a collective. Does it mean that you have an actual ex ample? Does it mean that you have some other methods to show that there is an example? In fact, is there any way to establish the existence of an example without exhibiting it specifically? One of the great surprises to all of us was, that it turned out that the generally accepted methods of mathe matics were in fact such, that there were rather round-about tricks by which you could demonstrate the existence of, with out exhibiting, an example. It is not easy to imagine how this can happen. But in fact it did happen, and it is normal mathe matical practice. So I would like to say that there are some very difficult and delicate questions here, and one cannot evade the con clusion that to some degree they are akin to those affecting the foundations of physics; that one may have a feeling of plausi bility which however is tinged with convenience, and that there is no question of the absolute super-human reliability
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which is supposed to be one of the attributes of mathe matics. So there is a certain area of doubt there; and in evaluating the character and the role of mathematics one must not for get that doubt exists. Let me now speak further of the functions of mathematics specifically in our thinking. It is commonplace that mathe matics is an excellent school of thinking, that it conditions you to logical thinking, that after having experienced it you can somehow think more validly than otherwise. I don't know whether all these statements are true, the first one is prob ably least doubtful. However, I think it has a very great im portance in thinking in an area which is not so precise. I feel that one of the most important contributions of mathematics to our-thinking is, that it has demonstrated, an enormous flexi bility in the formation of concepts, a degree of flexibility to which it is very difficult to arrive in a non-mathematical mode. One sometimes finds somewhat similar situations in philoso phy; but those areas of philosophy usually carry much less conviction. This great flexibility, to which I allude, involves things like this: In normal terminology it is considered a problem, which has occupied philosophers greatly in discussing an area, whether the laws which control this area are of a following nature. Each event determines the event immediately follow ing upon it directly. This is the causal approach. Alterna tively, these laws might be teleological, which means that a single event does not determine the next event, but that some how the whole process must be viewed as a unity, subordinate to a general law so that the whole can only be understood as a whole. If I say that this has beset the philosophers I am understating. This has played a very great role, and is still playing a very great role, for instance in biology. Well, I don't say this is a bad question, or a meaningless question, but it is a great deal more subtle, at any rate, than it sounds; because a good deal of mathematical experience shows that unless you are awfully careful, the question has no meaning.
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T h e classical example, the outstanding example for this, which I think deserves much more appreciation than it usu ally gets, is in an area between theoretical physics and mathe matics, but is really mathematics, namely the mathematical treatment of classical mechanics. Classical mechanics is, of course, in theoretical physics; but once you agree to the prin ciples of mechanics there remains the purely mathematical part of expressing these principles in mathematical terminol ogy, and of investigating mathematically how one finds solu tions, how many solutions there are, etc. Also, how one can state the same substantive principle in various mathematical forms, all of which are equivalent to each other, since they state the same thing, but which formally may look very dif ferent, and therefore give completely different technical approaches to problem-solving. These are then, generally speaking, different aspects by which one can understand the problem. Now one of the simplest facts about mechanics is, that it can be expressed by any one of several equivalent mathe matical forms. One of these is the Newtonian form where the state of the system is not only the position of every one of its parts, but also the velocity of every one of its parts at this moment. T h e state, thus defined, then uniquely determines the acceleration, and therefore the position and the velocity at the next moment. By repetition this can be used to derive the state of the system at any future, and in fact also at any past, moment. In other words this is strictly causal; if you know the system now, this determines it immediately there after, and by repetition also for all future times. A second formulation of mechanics is by the principle of minimum effect, which I will not describe mathematically, but which says this: If you consider the complete history of a system (by a system I mean any mechanical entity, so it can be a planet floating in space, simplified to the extent where it is a point; or a system of a planet and a central body; or something of the complexity of the whole solar system; or of the complexity of a locomotive; or anything else you choose), if you consider its total history between two moments (it may
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be from now to five minutes from now, or between three bil lion years ago and now or any other combination of moments) then the total history permits you to calculate certain things, and specifically the integral of energy times time. And the actual history is that one which makes this quantity as small as possible. This is a clearly teleological principle. Indeed, here the history is not determined by anything that happens at one moment, but you must view the entire thing and mini mize this particular numerical value of an integral extended over all of it. T h e first approach is strictly causal, working from point to point in time. The second is strictly teleological, and defines only the total history by virtue of certain optimal properties, not any part of it. Yet the two are strictly equivalent; the actual history for movements that you derive from one is pre cisely that which you find from the other; and the question as to whether mechanics is causal or teleological (which in any other field would be viewed as an important substantive question calling for a yes or no answer) is manifest nonsense in mechanics, because it depends purely on how you choose to write the equations. I'm not trying to be facetious about the importance of keeping teleological principles in mind when dealing with biology; but I think one hasn't started to understand the problem of their role in biology, until one realizes that in mechanics, if you are just a little bit clever mathematically, your problem disappears and becomes mean ingless. And that it is perfectly possible that if one understood another area the same might happen. This is an insight which would probably never have been obtained without the purely mathematical trickery of trans forming the equations of mechanics; it was purely mathe matical skill and the flexibility characteristics of mathematical formulation and re-formulation, that produced this insight. It is not pure thinking at any abstract level, but is a specifi cally mathematical procedure. Another thing that I would like to mention in this context is this. (I will again mix up theoretical physics with mathe matics, in the same manner as before. T h e example belongs
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in theoretical physics, but the technical treatment which pro duces the results to which I refer is really mathematical ma nipulation. Hence it has something to do with the role of mathematics in insight, and not with the role of theoretical physics in insight, the latter being important enough, but something else than the former.) A statement which is fre quently and freely made, especially before the matter was as well analyzed as it is now, is that there is some contrast be tween things that are subject to strict mathematical treatment, and things which are left to chance. This is a plausible statement, and was very plausible up to about 200 years ago, at which time the theory of probability was discovered, which made possible a strictly mathematical treatment for undetermined and fortuitous events. And again it takes a mathematical treatment to realize that if an event is not determined by strict laws, but left to chance, as long as you have clearly stated what you mean by this (and it can be clearly stated) it is just as amenable to quantitative treat ment as if it were rigorously defined. Of course what a quanti tative treatment will tell you will not be what will happen, since this is not supposed to be possible in this particular case, but it will tell you whether that, for instance, if you try it a million times, how many times you are likely to get a positive result. Also how accurately this likelihood will be strengthened if you increase the number of tries. Also, which combinations of eventualities are those which you can disre gard, which are absurd in spite of the uncertainty of the general laws. The theory of probability furnishes an example for this, but an even more striking example of this is the modern form of quantum mechanics. It turns out that the elementary processes—the processes involving elementary particles, the atoms or possibly sub-atomic particles—are, in spite of every thing known previously, apparently not subject to laws like those of mechanics, and most definitely not, because the laws of mechanics in their causal form tell you that if you know the state of the system now, you can tell exactly the state a short time afterwards, and by repeating this you can tell what
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it will be like at all times afterwards. It turns out that for the elementary processes it doesn't look as if it were this way. The best description one can give today, which may not be the ultimate one (the ultimate one may even revert to the causal form, although most physicists don't think this is likely) but at any rate the best we can tell today, is that you do not have complete determination, and that the state of the system now does not determine at all what it will be immedi ately afterwards or later. Of course, a state now may be in compatible with some further assumptions about what it will be an hour later; or some of them may be extremely im probable. But there will still be left many possibilities; and one might suspect that this is an idea which does not lend itself to description by precise mathematical means. The fact is that this was discovered by the method of theo retical physics, and it was then crystallized, made precise, by mathematical means. In fact very sophisticated mathematical theories had to be applied; and the most peculiar things turned up. For instance: A system, like the one here referred to, is not causally predictable. You cannot calculate from its present state its state at the next moment. There is, however, something else which is causally predictable, namely the socalled wave-function. The evolution of the wave-function can be calculated from one moment to the next, but the effect of the wave-function on observed reality is only probability. That such a combination can at all be worked out, that it can decipher experience, and even be derived from experi ence, is something which again would have been completely impossible if the mathematical method had not existed. And again an enormous contribution of the mathematical method to the evolution of our real thinking is, that it has made such logical cycles possible, and has made them quite specific. It has made it possible to do these things in complete reliability and with complete technical smoothness. Another thing about which we can't tell today as much as we would like, but about which we know a good deal, is that it might have been quite reasonable to expect a vicious cycle when one tries to analyze the substratum which pro-
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duces science, the function of the human intelligence. The whole evidence of exploration in this area is that the system which occurs in intellectual performance, in other words in the human nervous system, can be investigated with physical and mathematical methods. Yet there is probably some kind of contradiction involved in imagining that at any one mo ment, an individual should be completely informed about the state of his nervous apparatus at that particular moment. The chances are that the absolute limitations which exist here can also be expressed in mathematical terms, and only in mathematical terms. We have already had phenomena of this type. Theoretical physics has already indicated two areas in the physical world where absolute limitations to knowledge exist. One is rela tivity and the other is quantum theory. Here, by the best descriptions we can give today, there are absolute limitations to what is knowable. However, they can be expressed mathe matically very precisely, by concepts which would be very puzzling when attempted to be expressed by any other means. Thus, both in relativity and in quantum mechanics the things which cannot be known always exist; but you have a consider able latitude in controlling which ones they are. In quantum mechanics, for instance, the statement is like this: You can never at the same time know what the position and what the velocity of an elementary particle is, but you can suit yourself as to which of these two you can find out. Any information you acquire about one, deteriorates the acquirable informa tion about the other. This is certainly a situation of a degree of sophistication which it would be completely hopeless to develop or to handle by other than mathematical methods, or to talk sense about by other than mathematical methods; and much less to do what also has happened, namely to use it for predictions, with mathematical methods. In coming to the evolution of mathematics I am fearful to be too specific. But I would like to make a few general re marks about it. I think the circumstances of its evolution are probably more instructive to a general scientific audience than the recital of exactly what happened; and even more
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than what anybody thinks is going to happen ten years from now. T h e circumstances of this evolution are very typical and very instructive. Again, regarding the role of science in life or among other sciences, one thing is very conspicuous. There are large areas of mathematics which have been practically very useful. This practicality, however, is sometimes a rather indirect kind of practicality. For instance, a mathematician usually means that a theory is directly useful if it can be used in theoretical physics. After which he still has to say that insight in theoretical physics it self is only useful if it is useful in experimental physics. After which you must say that a concept in experimental physics is, by ordinary criteria, useful if it is useful in engi neering. Even after engineering you can make one more step. So all of these concepts of usefulness are rather limited, and we only mean by them, that each science should have appli cations outside its own area, and that there is some general direction in this sequence of applications towards practical ones for immediate social use. However, if one doesn't quibble about the definition of usefulness, and means, for instance, that by the standards of the mathematician anything is useful which is not mathematics, then one must say that large areas have been useful. Also, very large areas are really directly useful by the sum of all these criteria. Indeed, these things have really made a great difference in the world in which we live, usually somewhat indirectly, usually somewhat after the accession of some other area, but still in such a manner that the mathematical part is obviously quite vital. Now it is very interesting that the majority of these things were developed with very little regard to usefulness, and very often without any suspicion that they might become useful later, for reasons of an entirely different character. It is a very characteristic situation. I might mention certain forms of algebra, in the field of matrices and operators, which were in vented at times when there was no earthly reason to suspect that anywhere from twenty to a hundred years later they would play a role in (not yet existing) quantum mechanics.
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It is equally true for the discoveries in the area of differential geometry, for which there was absolutely no reason to expect that some day there would be a theory of general relativity, and that the theory of general relativity would make use of this type of geometry. Yet these things are quite vital. The examples could be multiplied. I must say, however, there are also examples to the con trary. One very important example is, that the calculus was certainly invented by Newton specifically for a specific pur pose in theoretical physics. But still a large part of mathematics which t>ecame useful developed with absolutely no desire to be useful, and in a situation where nobody could possibly know in what area it would become useful; and there were no general indications that it ever would be so. By and large it is uniformly true in mathematics that there is a time lapse between a mathematical discovery and the moment when it is useful; and that this lapse of time can be anything from thirty to a hundred years, in some cases even more; and that the whole system seems to function without any direction, without any reference to use fulness, and without any desire to do the things which are useful. Of course, one must also consider that this is really true for the entire course of science; in other words, that you should consider by what processes a large part of science got into the place where it impinges on society in everyday life: How most of physical science comes from mechanics, and how the original discoveries in mechanics were mainly connected with astronomy, and were absolutely not connected to the places where the applications today lie. This is true for all of science. Successes were largely due to forgetting completely about what one ultimately wanted, or whether one wanted anything ultimately; in refusing to in vestigate things which profit, and in relying solely on guidance by criteria of intellectual elegance; it was by following this rule that one actually got ahead in the long run, much better than any strictly utilitarian course would have permitted. I think that this phenomenon could be studied very well in
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mathematics; and I think everyone in science is in a very good position to satisfy himself as to the validity of these views. And I think it extremely instructive to watch the role of sci ence in everyday life, and to note how in this area the prin ciple of laissez faire has led to strange and wonderful results.
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STATEMENT OF JOHN VON NEUMANN BEFORE THE SPECIAL SENATE COMMITTEE ON ATOMIC ENERGY* Senator McMahon, Gentlemen: I assume that you wish to know my qualifications. I am a mathematician and a mathematical physicist. I am a member of the Institute for Advanced Study in Princeton, New Jersey. I have been connected with Government work on military matters for nearly ten years: As a consultant of Ballistic Research Laboratory of the Army Ordnance Department since 1937, as a member of its scientific advisory committee since 1940; I have been a member of various divisions of the National Defense Research Committee since 1941; I have been a consultant of the Navy Bureau of Ordnance since 1942. I have been connected with the Manhattan District since 1943 as a consultant of the Los Alamos Laboratory, and I spent a considerable part of 1943-45 there. I greatly appreciate the distinction of appearing before you. I realize the excep tional importance of the subject which you are considering. The developments in the field of subatomic energy release, which took place in the last decades, and culminated in 1939-45, and even more, those developments which are likely to follow in the decade ahead of us, have implications in the international field which are widely appreciated. Since they have been discussed by many others, and since I do not possess any special qualifications with respect to them, I do not think that it would be useful for me to dwell upon them. I would like to emphasize instead another aspect, which is also of very great importance, and which is of a domestic nature—although our present efforts to handle it may well set an example of universal significance. It is for the first time that science has produced results which require an immediate intervention of organized society, of the government. Of course science has produced many results before which were of great importance to society, directly or indirectly. And there have been before scientific processes which required some minor policing measures of the government. But it is for the first time that a vast area of research, right in the central part of the physical sciences, impinges on a broad front on the vital zone of society, and clearly requires rapid and general regulation. It is now that physical science has become "important" in that painful and dangerous sense which causes the state to intervene. Considering the vastness of the ultimate objectives of science, it has been clear for a long time to thoughtful persons that this moment must come, sooner or later. We now know that it has come. * Editorial Note: This article is the statement prepared by von Neumann for presentation to the Special Committee on Atomic Energy, United States Senate. His actual testimony, given on January 31, 1946, is published in the hearings before the committee (Atomic Energy Act of 1946, United States Printing Office) along with a discussion of this testimony with various people at the hearing. A.H.T.
499 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 499-502.
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The legislation on atomic energy represents the first attempt in history to regulate science in this sense. In past wartime or peacetime emergencies, govern ments did influence various phases of the social effort, including science, in order to promote military or economic ends. However, such efforts were always limited in time and in scope, and directed towards some ulterior, independent purpose. It is only now, that science as such and for its own sake, has to be regulated; that science has outgrown the age of independence from society. Many scientists regret this, and I am one of them. Atomic physics in particular is now losing a good deal of its detachment and abstractness, and will probably never again be the same as before 1939. I repeat: From the scientist's special viewpoint this evolution is probably not a desirable one—but nobody can change it, and we must recognize that it is taking place. And there is clearly a need for the government's intervention here and now. The problem is, then, how to effect this regulation without falling into either extreme: Regulation is needed, because nuclear physics, in combination with irresponsible or clumsy politics, could at this very moment inflict terrible wounds on society. And with some more development, which could be effected—and probably will be effected by some country or other—in a moderate number of years, and the main outlines of which are perfectly discernible today to the expert, the same combination of physics and politics could render the surface of the earth uninhabitable. Regulation is thus needed, both in politics and in science, but I will only talk of the latter, for the reasons given earlier. Regulation of science, on the other hand, must not go too far. Indeed, it should not go very far in any event, no matter how great risks are involved. This is the subject about which I would like to speak. In regulating science, it is important to realize that the legislator is touching at a matter of extreme delicacy. Strict regulation, and even the threat or the anticipation of strict regulation, is perfectly able to stop the progress of science in the country where it occurs. The fact that strict or unreasonable regulations may deter mature scientists from pursuing their vocation, or from pursuing it with that degree of enthusiasm which is necessary for success, is in itself important, but it is not the most important fact. What is more fundamental is this: The numbers of new talent which accede in any one year to a given field of science are subject to considerable oscillations. They decrease or increase in response to the emergence of new interests, to changing social valuations, to new developments in the field in question, or in neighboring, scientific or applied fields, etc. I am convinced that seemingly small mistakes in "regulating" science may affect the "reproduction" of scientists catastrophically. Thus, erroneous legislation on this subject may harm science in this country seriously, even irremediably. Great intellectual values could be lost in this manner. Apart from this, damage to fundamental science would, at the present stage of industrial development, soon cause comparable damage in the technological, and then in the economical sphere. Finally, since other countries may not be similarly affected, it would seriously impair the national defense. For all these reasons I am absolutely convinced that it is necessary to maintain
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and to protect the natural modus operandi of fundamental research, and specifically two of its cornerstones: Freedom in selecting the subject of fundamental research, and freedom in publishing its results. Any attempt to subdivide nuclear physics is futile from the start. To make work on the fission of heavy nuclei a preserve for special rules or for secrecy would be vain, since the reactions of light nuclei may later assume an even greater importance. To police all work on transmutations of all atomic species may still prove inadequate: Still other sources of primary energy may exist in processes yet to be discovered. Science, and particularly physics, forms an indivisible unity, and no attempt to compartmentalize it can produce anything but disappointment. And to put all of atomic physics, or all of physics, on the restricted and classified list would clearly kill the physical sciences. It is plausible that potential nuclear explosives and actual or potential radiopoisons should be subject to safety and health regulations, and to the government's police power. This has always been so for dangerous substances produced by the chemical industry, and it should be done even more strictly for those originating in the coming nuclear industry. This can certainly be done, and both the Ball Bill and the MacMahon Bill indicate certain guiding principles. The details will have to be worked out in the administrative practice—as usual. There must, however, be no restriction in principle on research in any part of science, and none in nuclear physics in particular, and absolutely no secrecy or possibility of classification of the results of fundamental research. To come to a different part of the subject: I think that any special legislation against military developments in the atomic field is unjustified at this moment, and would be exceedingly harmful. It is generally admitted that we should have an Army and a Navy and that they should be maintained on a high level of efficiency. It would therefore be inconsistent to forbid them to work on the development of a class of weapons that is likely to be of the greatest importance—the atomic weapons—and to monopolize all atomic weapons developments in the Commission. Our wartime experience produced a system for military technological developments which worked. It had its shortcomings, but it worked at least as well as that of any belligerent—and definitely better than that of some important belligerents. It was based on the coexistence of a large civilian organization, the O.S.R.D., and of the Army and Navy research and development establishments, plus adequate liaison. Just one of these two components, plus any amount of advisers or observers from the other party, would have been inadequate. Besides, I do not believe that the nation would act wisely in attempting to forbid to itself to do certain things. I think that the military uses of atomic energy should be in the province of each; the Commission, the Army, and the Navy. Regarding the makeup of the Commission, I feel somewhat inexperienced and uncertain, but I feel satisfied as to these points: If there is to be an Administrator, he should be elected by and serve at the pleasure of the Commission. Since the Commission is to be policy-making, the Cabinet should be directly represented on it, and its character should be civilian. I do not think that the time is now mature to connect this piece of domestic legislation with anticipated and desirable but, in any case, future developments in
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international politics. This should be done by additional legislation when and as the circumstances justify it. The idea that the Commission should make periodic reports to the President and to Congress seems to me to be a sound one. I doubt, however, that quarterly reports are necessary or desirable. It seems unlikely that every three months will produce enough progress to make such reporting really valuable and, besides, a certain distance from the events to be reported is essential. There is ample experience to support this. I think that yearly reporting would be more nearly right.
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For the kind of explosiveness that man will be able to contrive by 1980, the globe is dangerously small, its political units dangerously unstable.
CAN WE SURVIVE TECHNOLOGY?
by John von Neumann Member, Atomic Energy Commission
"The great globe itself" is in a rapidly maturing crisis —a crisis attributable to the fact that the environment in which technological progress must occur has become both undersized and underorganized. To define the crisis with any accuracy, and to explore possibilities of dealing with it, we must not only look at relevant facts, but also engage in some speculation. The process will illuminate some potential technological developments of the next quarter-century. In the first half of this century the accelerating indus trial revolution encountered an absolute limitation—not on technological progress as such but on an essential safety factor. This safety factor, which had permitted the industrial revolution to roll on from t h e mideighteenth to the early twentieth century, was essentially a matter of geographical and political Lebensraum: an ever broader geographical scope for technological activi504 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 504-519.
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ties, combined with an ever broader political integration of the world. Within this expanding framework it was possible to accommodate the major tensions created by technological progress. Now this safety mechanism is being sharply inhibited; literally and figuratively, we are running out of room. At long last, we begin to feel the effects of the finite, actual size of the earth in a critical way. Thus the crisis does not arise from accidental events or human errors. It is inherent in technology's relation to geography on the one hand and to political organiza tion on the other. The crisis was developing visibly in the 1940's, and some phases can be traced back to 1914. In the years between now and 1980 the crisis will prob ably develop far beyond all earlier patterns. When or how it will end—or to what state of affairs it will yield —nobody can say.
Dangers—present and coming In all its stages the industrial revolution consisted of making available more and cheaper energy, more and easier controls of human actions and reactions, and more and faster communications. Each development increased the effectiveness of the other two. All three factors in creased the speed of performing large-scale operations —-industrial, mercantile, political, and migratory. But throughout the development, increased speed did not so much shorten time requirements of processes as ex tend the areas of the earth affected by them. The reason is clear. Since most time scales are fixed by human re action times, habits, and other physiological and psycho logical factors, the effect of the increased speed of technological processes was to enlarge the size of units
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— political, organizational, economic, and cultural — affected by technological operations. That is, instead of performing the same operations as before in less time, now larger-scale operations were performed in the same time. This important evolution has a natural limit, that of the earth's actual size. The limit is now being reached, or at least closely approached. Indications of this appeared early and with dramatic force in the military sphere. By 1940 even the larger countries^ of continental Western Europe were inade quate as military units. Only Russia could sustain a major military reverse without collapsing. Since 1945, improved aeronautics and communications alone might have sufficed to make any geographical unit, including Russia, inadequate in a future war. The advent of nuclear weapons merely climaxes the development. Now the effectiveness of offensive weapons is such as to stultify all plausible defensive time scales. As early as World War I, it was observed that the admiral commanding the battle fleet could "lose the British Empire in one afternoon/' Yet navies of that epoch were relatively stable entities, tolerably safe against technological sur prises. Today there is every reason to fear that even minor inventions and feints in the field of nuclear weapons can be decisive in less time than would be re quired to devise specific countermeasures. Soon existing nations will be as unstable in war as a nation the size of Manhattan Island would have been in a contest fought with the weapons of 1900. Such military instability has already found its political expression. Two superpowers, the U.S. and U.S.S.R., represent such enormous destructive potentials as to afford little chance of a purely passive equilibrium. Other countries, including possible "neutrals," are militarily
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defenseless in the ordinary sense. At best they will ac quire destructive capabilities of their own, as Britain is now doing. Consequently, the "concert of powers"— or its equivalent international organization—rests on a basis much more fragile than ever before. The situation is further embroiled by the newly achieved political effectiveness of non-European nationalisms. These factors would "normally"—that is, in any re cent century—have led to war. Will they lead to war before 1980? Or soon thereafter? It would be presump tuous to try to answer such a question firmly. In any case, the present and the near future are both dangerous. While the immediate problem is to cope with the actual danger, it is also essential to envisage how the problem is going to evolve in the 1955-80 period, even assuming that all will go reasonably well for the moment. This does not mean belittling immediate problems of weap onry, of U.S.-U.S.S.R. tensions, of the evolution and revolutions of Asia. These first things must come first. But we must be ready for the follow-up, lest possible immediate successes prove futile. We must think beyond the present forms of problems to those of later decades.
When reactors grow up Technological evolution is still accelerating. Technol ogies are always constructive and beneficial, directly or indirectly. Yet their consequences tend to increase in stability—a point that will get closer attention after we have had a look at certain aspects of continuing tech nological evolution. First of all, there is a rapidly expanding supply of energy. It is generally agreed that even conventional, chemical fuel—coal or oil—will be available in increased
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quantity in the next two decades. Increasing demand tends to keep fuel prices high, yet improvements in methods of generation seem to bring the price of power down. There is little doubt that the most significant event affecting energy is the advent of nuclear power. Its only available controlled source today is the nuclearfission reactor. Reactor techniques appear to be ap proaching a condition in which they will be competitive with conventional (chemical) power sources within the U.S.; however, because of generally higher fuel prices abroad, they could already be more than competitive in many important foreign areas. Yet reactor technology is but a decade and a half old, during most of which period effort has been directed primarily not toward power but toward plutonium production. Given a decade of really large-scale industrial effort, the economic characteristics of reactors will undoubtedly surpass those of the present by far. Moreover, it is not a law of nature that all controlled release of nuclear energy should be tied to fission reac tions as it has been thus far. It is true that nuclearenergy appears to be the primary source of practically all energy now visible in nature. Furthermore, it is not surprising that the first break into the intranuclear do main occurred at the unstable "high end" of the system of nuclei (that is, by fission). Yet fission is not nature's normal way of releasing nuclear energy. In the long run, systematic industrial exploitation of nuclear energy may shift reliance onto other and still more abundant modes. Again, reactors have been bound thus far to the tradi tional heat-steam-generator-electricity cycle, just as automobiles were at first constructed to look like buggies. It is likely that we shall gradually develop procedures more naturally and effectively adjusted to the new source
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of energy, abandoning the conventional kinks and de tours inherited from chemical-fuel processes. Conse quently, a few decades hence energy may be free—just like the unmetered air—with coal and oil used mainly as raw materials for organic chemical synthesis, to which, as experience has shown, their properties are best suited.
"Alchemy" and automation It is worth emphasizing that the main trend will be systematic exploration of nuclear reactions—that is, the transmutation of elements, or alchemy rather than chemistry. The main point in developing the industrial use of nuclear processes is to make them suitable for large-scale exploitation on the relatively small site that is the earth or, rather, any plausible terrestrial indus trial establishment. Nature has, of course, been operat ing nuclear processes all along, well and massively, but her "natural" sites for this industry are entire stars. There is reason to believe that the minimum space re quirements for her way of operating are the minimum sizes of stars. Forced by the limitations of our real estate, we must in this respect do much better than nature. That this may not be impossible has been demon strated in the somewhat extreme and unnatural instance of fission, that remarkable breakthrough of the past decade. What massive transmutation of elements will do to technology in general is hard to imagine, but the effects will be radical indeed. This can already be sensed in related fields. The general revolution clearly under way in the military sphere, and its already realized special aspect, the terrible possibilities of mass destruction,
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should not be viewed as typical of what the nuclear revolution stands for. Yet they may well be typical of how deeply that revolution will transform whatever it touches. And the revolution will probably touch most things technological. Also likely to evolve fast—and quite apart from nu clear evolution—is automation. Interesting analyses of recent developments in this field, and of near-future potentialities, have appeared in the last few years. Auto matic control, of course, is as old as the industrial revolu tion, for the decisive new feature of Watt's steam engine was its automatic valve control, including speed control by a "governor." In our century, however, small electric amplifying and switching devices put automa tion on an entirely new footing. This development began with the electromechanical (telephone) relay, continued and unfolded with the vacuum tube, and appears to ac celerate with various solid-state devices (semi-conductor crystals, ferromagnetic cores, etc.). The last decade or two has also witnessed an increasing ability to control and "discipline" large numbers of such devices within one machine. Even in an airplane the number of vacuum tubes now approaches or exceeds a thousand. Other machines, containing up to 10,000 vacuum tubes, up to five times more crystals, and possibly more than 100,000 cores, now operate faultlessly over long periods, per forming many millions of regulated, preplanned actions per second, with an expectation of only a few errors per day or week. Many such machines have been built to perform com plicated scientific and engineering calculations and largescale accounting and logistical surveys. There is no doubt that they will be used for elaborate industrial process control, logistical, economic, and other planning,
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and many other purposes heretofore lying entirely out side the compass of quantitative and automatic control and preplanning. Thanks to simplified forms of auto matic or semi-automatic control, the efficiency of some important branches of industry has increased consider ably during recent decades. It is therefore to be expected that the considerably elaborated newer forms, now be coming increasingly available, will effect much more along these lines. Fundamentally, improvements in control are really improvements in communicating information within an organization or mechanism. The sum total of progress in this sphere is explosive. Improvements in communica tion in its direct, physical sense—transportation—while less dramatic, have been considerable and steady. If nuclear developments make energy unrestrictedly avail able, transportation developments are likely to accelerate even more. But even "normal" progress in sea, land, and air media is extremely important. Just such "normal" progress molded the world's economic development, pro ducing the present global ideas in politics and economics.
Controlled climate Let us now consider a thoroughly "abnormal" indus try and its potentialities—that is, an industry as yet without a place in any list of major activities: the con trol of weather or, to use a more ambitious but justified term, climate. One phase of this activity that has re ceived a good deal of public attention is "rain making." The present technique assumes extensive rain clouds, and forces precipitation by applying small amounts of chemi cal agents. While it is not easy to evaluate the signifi cance of the efforts made thus far, the evidence seems to indicate that the aim is an attainable one.
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But weather control and climate control are really much broader than rain making. All major weather phenomena, as well as climate as such, are ultimately controlled by the solar energy that falls on the earth. To modify the amount of solar energy, is, of course, beyond human power. But what really matters is not the amount that hits the earth, but the fraction retained by the earth, since that reflected back into space is no more use ful than if it had never arrived. Now, the amount ab sorbed by the solid earth, the sea, or the atmosphere seems to be subject to delicate influences. True, none of these has so far been substantially controlled by human will, but there are strong indications of control possibili ties. The carbon dioxide released into the atmosphere by industry's burning of coal and oil-—more than half of it during the last generation—may have changed the at mosphere's composition sufficiently to account for a general warming of the world by about one degree Fahrenheit. The volcano Krakatao erupted in 1883 and released an amount of energy by no means exorbitant. Had the dust of the eruption stayed in the stratosphere for fifteen years, reflecting sunlight away from the earth, it might have sufficed to lower the world's temperature by six degrees (in fact, it stayed for about three years, and five such eruptions would probably have achieved the result mentioned). This would have been a substan tial cooling; the last Ice Age, when half of North America and all of northern and western Europe were under an ice cap like that of Greenland or Antarctica, was only fifteen degrees colder than the present age. On the other hand, another fifteen degrees of warming would probably melt the ice of Greenland and Antarctica and produce world-wide tropical to semi-tropical climate.
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"Rather fantastic effects" Furthermore, it is known that the persistence of large ice fields is due to the fact that ice both reflects sunlight energy and radiates away terrestrial energy at an even higher rate than ordinary soil. Microscopic layers of col ored matter spread on an icy surface, or in the atmos phere above one, could inhibit the reflection-radiation process, melt the ice, and change the local climate. Meas ures that would effect such changes are technically pos sible, and the amount of investment required would be only of the order of magnitude that sufficed to develop rail systems and other major industries. The main dif ficulty lies in predicting in detail the effects of any such drastic intervention. But our knowledge of the dynamics and the controlling processes in the atmosphere is rapidly approaching a level that would permit such pre diction. Probably intervention in atmospheric and clima tic matters will come in a few decades, and will unfold on a scale difficult to imagine at present. What could be done, of course, is no index to what should be done; to make a new ice age in order to annoy others, or a new tropical, "interglacial" age in order to please everybody, is not necessarily a rational program. In fact, to evaluate the ultimate consequences of either a general cooling or a general heating would be a com plex matter. Changes would affect the level of the seas, and hence the habitability of the continental coastal shelves; the evaporation of the seas, and hence general precipitation and glaciation levels; and so on. What would be harmful and what beneficial—and to which re gions of the earth — is not immediately obvious. But there is little doubt that one could carry out analyses needed to predict results, intervene on any desired scale, and ultimately achieve rather fantastic effects. The
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climate of specific regions and levels of precipitation might be altered. For example, temporary disturbances —including invasions of cold (polar) air that constitute the typical winter of the middle latitudes, and tropical storms (hurricanes) —might be corrected or at least depressed. There is no need to detail what such things would mean to agriculture or, indeed, to all phases of human, animal, and plant ecology. What power over our environ ment, over all nature, is implied! Such actions would be more directly and truly world wide than recent or, presumably, future wars, or than the economy at any time. Extensive human intervention would deeply affect the atmosphere's general circulation, which depends on the earth's rotation and intensive solar heating of the tropics. Measures in the arctic may con trol the weather in temperate regions, or measures in one temperate region critically affect another, onequarter around the globe. All this will merge each na tion's affairs with those of every other, more thoroughly than the threat of a nuclear or any other war may already have done.
The indifferent controls Such developments as free energy, greater automa tion, improved communications, partial or total climate control have common traits deserving special mention. First, though all are intrinsically useful, they can lend themselves to destruction. Even the most formidable tools of nuclear destruction are only extreme members of a genus that includes useful methods of energy release or element t r a n s m u t a t i o n . The most constructive schemes for climate control would have to be based on
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insights and techniques that would also lend themselves to forms of climatic warfare as yet unimagined. Tech nology—like science—is neutral all through, providing only means of control applicable to any purpose, indif ferent to all. Second, there is in most of these developments a trend toward affecting the earth as a whole, or to be more exact, toward producing effects that can be projected from any one to any other point on the earth. There is an intrinsic conflict with geography — and institutions based thereon — as understood today. Of course, any technology interacts with geography, and each imposes its own geographical rules and modalities. The tech nology that is now developing and that will dominate the next decades seems to be in total conflict with traditional and, in the main, momentarily still valid, geographical and political units and concepts. This is the maturing crisis of technology. What kind of action does this situation call for? Whatever one feels inclined to do, one decisive trait must be considered: the very techniques that create the dangers and the instabilities are in themselves useful, or closely related to the useful. In fact, the more useful they could be, the more unstabilizing their effects can also be. It is not a particular perverse destructiveness of one par ticular invention that creates danger. Technological power, technological efficiency as such, is an ambivalent achievement. Its danger is intrinsic.
Science the indivisible In looking for a solution, it is well to exclude one pseudosolution at the start. The crisis will not be re solved by inhibiting this or that apparently particularly
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obnoxious form of technology. For one thing, the parts of technology, as well as of the underlying sciences, are so intertwined that in the long run nothing less than a total elimination of all technological progress would suffice for inhibition. Also, on a more pedestrian and immediate basis, useful and harmful techniques lie everywhere so close together that it is never possible to separate the lions from the lambs. This is known to all who have so laboriously tried to separate secret, "classi fied" science or technology (military) from the "open" kind; success is never more—nor intended to be more— than transient, lasting perhaps half a decade. Similarly, a separation into useful and harmful subjects in any technological sphere would probably diffuse into nothing in a decade. Moreover, in this case successful separation would have to be enduring (unlike the case of military "classi fication," in which even a few years' gain may be im portant) . Also, the proximity of useful techniques to harmful ones, and the possibility of putting the harmful ones to military use, puts a competitive premium on in fringement. Hence the banning of particular technologies would have to be enforced on a worldwide basis. But the only authority that could do this effectively would have to be of such scope and perfection as to signal the resolution of international problems rather than the discovery of a means to resolve them. Finally and, I believe, most importantly, prohibition of technology (invention and development, which are hardly separable from underlying scientific inquiry), is contrary to the whole ethos of the industrial age. It is irreconcilable with a major mode of intellectuality as our age understands it. It is hard to imagine such a re straint successfully imposed in our civilization. Only if
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those disasters that we fear had already occurred, only if humanity were already completely disillusioned about technological civilization, could such a step be taken. But not even the disasters of recent wars have produced that degree of disillusionment, as is proved by the phenomenal resiliency with which the industrial way of life recovered even—or particularly—in the worst-hit areas. The techilological system retains enormous vi tality, probably more than ever before, and the counsel of restraint is unlikely to be heeded.
Survival—a possibility A much more satisfactory solution than technological prohibition would be eliminating war as "a means of national policy." The desire to do this is as old as any part of the ethical system by which we profess to be governed. The intensity of the sentiment fluctuates, in creasing greatly after major wars. How strong is it now and is it on the up or the downgrade? It is certainly strong, for practical as well as for emotional reasons, all quite obvious. At least in individuals, it seems world wide, transcending differences of political systems. Yet in evaluating its durability and effectiveness a certain caution is justified. One can hardly quarrel with the "practical" argu ments against war, but the emotional factors are prob ably less stable. Memories of the 1939-45 war are fresh, but it is not easy to estimate what will happen to popu lar sentiment as they recede. The revulsion that followed 1914-18 did not stand up twenty years later under the strain of a serious political crisis. The elements of a future international conflict are clearly present today and even more explicit than after 1914-18. Whether the
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" p r a c t i c a l " considerations, without the emotional counterpart, will suffice to restrain the human species is dubious since the past record is so spotty. True, "prac tical" reasons are stronger than ever before, since war could be vastly more destructive than formerly. But that very appearance has been observed several times in the past without being decisive. True, this time the danger of destruction seems to be real rather than apparent, but there is no guarantee that a real danger can control human actions better than a convincing appearance of danger. What safeguard remains? Apparently only day-to-day — or perhaps year-to-year — opportunistic measures, a long sequence of small, correct decisions. And this is not surprising. After all, the crisis is due to the rapidity of progress, to the probable further acceleration thereof, and to the reaching of certain critical relationships. Specifically, the effects that we are now beginning to produce are of the same order of magnitude as that of "the great globe itself." Indeed, they affect the earth as an entity. Hence further acceleration can no longer be absorbed as in the past by an extension of the area of operations. Under present conditions it is unreasonable to expect a novel cure-all. For progress there is no cure. Any attempt to find automatically safe channels for the present explosive variety of progress must lead to frustration. The only safety possible is relative, and it lies in an intelligent ex ercise of day-to-day judgment.
Awful and more awful The problems created by the combination of the pre sently possible forms of nuclear warfare and the rather
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unusually unstable international situation are formid able and not to be solved easily. Those of the next de cades are likely to be similarly vexing, "only more so." The U.S.-U.S.S.R. tension is bad, but when other nations begin to make felt their full offensive potential weight, things will not become simpler. Present awful possibilities of nuclear warfare may give way to others even more awful. After global climate control becomes possible, perhaps all our present involve ments will seem simple. We should not deceive ourselves: once such possibilities become actual, they will be ex ploited. It will, therefore, be necessary to develop suit able new political forms and procedures. All experience shows that even smaller technological changes than those now in the cards profoundly transform political and social relationships. Experience also shows that these transformations are not a priori predictable and that most contemporary "first guesses" concerning them are wrong. For all these reasons, one should take neither present difficulties nor presently proposed reforms too seriously. The one solid fact is that the difficulties are due to an evolution that, while useful and constructive, is also dangerous. Can we produce the required adjustments with the necessary speed? The most hopeful answer is that the human species has been subjected to similar tests before and seems to have a congenital ability to come through, after varying amounts of trouble. To ask in advance for a complete recipe would be unreason able. We can specify only the human qualities required: patience, flexibility, intelligence.
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DEFENSE IN ATOMIC WAR It will not be sufficient to know that the enemy has only fifty possible tricks and that we can counter every one of them, but we must be able to counter them almost at the very instant they occur Dr. John von Neumann
T
HE introduction to any and all applied science via the channel of military science, while it was rare in the one or two generations that came before us, is not so paradoxical. Without trying to reminisce about things long past, this particular circum stance has had, since Archimedes and Leonardo da Vinci, a very long pedi gree. I would like nevertheless to reminisce just a little. My particular introduction occurred at the Ballistic Research Labortories in the early years of World War II. It is remarkable to consider today how small in numbers was the manpower trained for this kind of ap plied science, and in particular for mili tary matters. This was especially true in the theoretical field and more especially in my field—mathematics. It was astounding that there were considerable numbers of supposedly very sophisticated specialists in very highly complicated fields of effort, and yet how very little we knew about the matters to which we were to be in troduced. HP HERE the guidance and the ex■*■ ample of somebody who knew what this was all about were tremendously valuable. This whole relationship of being supposedly an expert in one way and yet a complete ignoramus in the way which happened to matter at that time is hard to describe. I assume it is best illustrated by a story which I heard recently about the
listic Research Laboratories, and for years afterward the only ones that could operate on the scale required were avail able there, and only there. It took quite some time before a really high speed machine was developed independently elsewhere. Since then, the complexity and the American Indian who registered at a New York hotel and made two X's for sophistication of the weapons business his name. When asked what this signi has been increasing very rapidly from fied, he"* said that the first X meant year to year. I should like to mention, "Chief Bald Eagle." When asked what as an example of this, the phase of com the second X meant, he said, "Ph.D." puting machines. It is probably true We were all making our X's in this that since 1945 the over-all capacity of fashion! these machines has nearly doubled every The other thing which was very re year. This is astounding because over a markable was how this transformation took place in other fields and speci period of ten years it means a thousand fically how the' institutions expanded fold increase. Yet it is true that the in which were connected with the Ballistic crease that has occurred is a thousand Research Laboratories. fold in certain respects. I know of one The first vista I got of this was at the instance where it actually has been Ballistic Research Laboratories, where, three or four thousandfold since 1946. first under Colonel Zornig and then T is astounding to what extent the under Colonel Simon, and always under use of the computing machine has the guidance of Dr. Kent, the institution expanded fiftyfold. And how the com spread, and in some'fields today it is plexity of what went on grew! very hard to imagine how one would Quite apart from facts referred to, it go on working without such machines. One of them is, of course, ballistics was very remarkable that the laboratory was one of the pioneers in supersonic in the very complicated forms it now wind tunnel building in America. It has assumed. Ballistics has progressed was absolutely the pioneer in the field from the calculation of firing tables for which concerned me very closely after more or less conventional use into the ward—the building of modern elec calculation of firing tables for antiair tronic computing machines. craft artillery, then into the more com The first modern electronic full-scale plicated field of air-to-air firings, and computing machine was built at the now into the peculiar and complicated University of Pennsylvania for the Bal- field of missile-trajectories guidance. Dr. von Neumann is a mem ber of the United States Atomic Energy Commission, Wash ington, D. C.
I
523 Reprinted from John von Neumann Collected Works, ed. A. Taub, Vol. VI, pp. 523-525.
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524 At the present time a high-speed com puting machine based on the principles that were introduced in the middle 1940*5 is an absolutely necessary condi tion for these things. Another field is systems analysis and methods of operational research, the determination of expected characteristics of future weapons, and the determina tion of what the future weapons, on which one still has latitude to choose characteristics, ought to be like in order to be o p t i m u m . T h e sorts of things one can d o in this area now would have baffled the imagination ten or fifteen years ago. T h e m a n n e r in which one now cal culates the performance of a weapon system consists of taking it through a military maneuver, an engagement, or a seric. of engagements on a computing machine. Chance factors are injected and the result calculated. T h e n this is repeated a few ten thousand times and the expectation found. T h i s is done for hundreds of trial computations to discover in which regions one finds the o p t i m u m . All this would have meant large-scale military maneuvers and large-scale operations if done in reality. One could never have varied all the parameters. Many of these techniques originated in the Ballistic Research Laboratories, particularly in those sections of it which owe their existence to the work of D r . Kent.
I
W O U L D like to discuss also the probable impact of the use of atomic weapons on the responsibilities of the field of ordnance and the tactics and strategy of warfare. It is quite clear that the type of system analysis which has been applied to conventional weapons will have to be applied in the field of atomic weapons with even more sophis tication on an even larger scale because the changes which this will bring to military procedures are likely to be even more drastic. Let m e point out a few things which immediately come to mind which show how different not only the situations are in which these things are used but even h o w different the methods m u s t be with which, they are approached. Fundamentally, what is achieved by the use of atomic weaponry is just an increase in firepower. This in itself is not very revolutionary. T h e history of
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all k n o w n warfare and military effort has been nothing but a history of the increase in firepower. It is well k n o w n what the conse quences are. T h e most obvious one is the dilution of armies on the battlefield. It is clear that if you can concentrate a much greater power of destruction on a small area you can afford to keep less people and less e q u i p m e n t in that small area. If you deploy your m a x i m u m effort in people a n d equipment, you will have to cover a greater area.
T
H E increases of firepower which are now before us are considerably greater than any that have occurred be fore. T h i s increase is particularly ob vious if you discuss it not i n terms of firepower per m a n in the field but in terms of the increment of firepower per delivery vehicle in the field and specifi cally per airplane, since delivery by air craft is the one which was utilized first and its applicability was most obvious. However, it was plainly not the only one. T h e entire tonnage of T N T dropped on all battlefields d u r i n g all of W o r l d W a r II by all belligerents was a few million tons. W c delivered more ex plosive power than this in a single atomic blast. Consequently, we can pack in one airplane more firepower than the combined fleets of all the com batants d u r i n g W o r l d War II. T h e Air Force organization which delivered those t w o or three million tons of explosives in W o r l d W a r II
"It is astounding to what ex tent the use of the computing machine has spread, and in some fields today it is very hard to imagine how one would go on wording with out such machines. One of them is, of course, ballistics in the very complicated forms it now has assumed. Ballistics has progressed from the cal culation of firing tables for more or less conventional use into the calculation of firing tables for antiaircraft artillery, then into the more complicated field of air-to-air firings, and now into the peculiar and complicated field of missiletrajectories guidance."
amounted to several million people. Today, the organization which makes one drop in the million-ton range from one airplane may number from a few people to a hundred people, depending on how much of the supporting organi zation you count. In this sense, you can judge what incremental concentration has been achieved. You must consider, however, that the applications in the form of airplane delivery are still relatively primitive. In fact, just because of the overwhelming power involved, they have led to a cer tain de differentiation. At the end of the high-explosive age of aerial war fare there were large numbers of types of bombs—incendiaries, high-explosive, and fragmentation bombs—made in very different ways, arranging their es sential components differently, and really operating on different physical principles.
A
N atomic bomb can produce a number of different effects, and the military use of it may emphasize dif ferent effects such as blast or heat or radiation. Nevertheless, the bomb is essentially the same. T h e weapon is not changed very much by the manner in which it is used. It is not at all unlikely that this dedifferentiation will go on and will last w h e n other forms of use are discovered. Yet the obvious thing will probably happen in the end, and if these wea pons become paramount for ground warfare it is very hard to imagine that a considerable differentiation will not have to take place, or rather that the differentiation which already exists will not have to perpetuated. T h e way to fight a tank with atomic energy is not the same as the way to fight a large body of infantry or to at tack a Nrge static fortification. In fighiing l ? ^ e bodies of infantry, the weap ons of aerial delivery probably can be used. It is plain that in fighting an ob ject like a tank the technique is quit.different. All these things will require capons systems of high differentiation, and the methods of operation which were ap plied to high-explosive warfare in the last w a r will have to be redeveloped. In the past, when a weapon system was first developed, if it was used in the proper way with sufficiently high con centration and intensity it was usually
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676 D E F E N S E IN A T O M I C very potent tor a while until countermeasures were developed. Any one w h o had the last move in this game had the advantage for a while thereafter. T h e n w h e n another countermove was made, the advantage shifted. This advantage oscillated to and fro, with the oscillations always decreasing. In the late stages of the use of a weapon at a high level of sophistication the re turn for a new trick was much smaller than in the early stages. There are many examples of this. A particularly interesting one is in the history of submarine mine warfare where this peculiar equilibrium of measure and countermcasure was de veloped to such a degree that after about a year or so the damage actually done by mines to the enemy was smaller than the economic effort the enemy had to exert in order to defend himself against mines.
I
N the end, 1 think we probably harmed the Germans much more by forcing them to divert their rather scarce copper into minesweepers than by the ships we actually sank. I think they did as much harm to us by forcing us into the convoy system or into the use of special shipping lanes as by the ships they actually sank, With the -«to'-.u\ .v:-.■.;;:.;..- there vr" be the follow:-^ oiidi?;-. -':v\ i:. -.%:i; J^.k." a great inte-ieeUiai effort :;::».: some "cry brilliant ide::.-> ,jr.i y.-t heh! |-,y anybody to solve the problem \v- are h'.ced with. This is par::c:.:!:-:r!y clear when -ve cor, sider nuclear weapons in their ex;xvteu most vicious :r,rr.: -:,-; iong-ra.ngc ii:issile delivery. A situation :-::iy r.rise where for a known weajxjn, s::rh as a par ticular type- oi iO::g-r;:p.ge missile, .here is probably a defense against it. But there is also probably ?. counter measure against the ce.'cr-sc. Further more, it is utterly hopeless to produce defenses against ;Al the .■:ou.nie.-::ieasi:res the enemy may uve, not because w t don't know now to counter bui because we can't use all -he to;mtermcasi;rcs at the same time. T'h? enemy br.s the enormous advantage Ir. t'r.vJ he wiii only use one t-lrsc, a:*;: if -ve :-• me. This wai true in -:he u::-,-. W.\[ ::ios* specifically of aeri.-.i ".v.rfare. :1" ihc enemy cai;-e oi-.l v/ith a ■.xirihv.lr.riv brilliant nc;/ trie!:, thr. ; «:rj ~-\iz: t-.:u':
to take your losses until you had de veloped the countcrmeasures, which may have taken weeks or months. T h e period of one m o n t h is probably reason able for a very brilliantly performed counter-countermove. T h i s duration is now much too long, and the losses you may have to take d u r i n g this period may be quite decisive.
I
T H I N K an introduction- of one par ticular radar trick ( w h i c h the Ger mans countered in three or four days), caused them to lose the city of H a m burg. O n the other hand, the introduc tion of very fancy new mines which could be countered only after a few months of work, led to exorbitant losses of shipping only for a limited time, and it soon became possible to reduce these losses to a bearable level. T h e difficulty with atomic weapons, a n d especially w i t h missile-carried atomic weapons, will be that they can decide a war, and d o a good deal more in terms of destruction, in less than a m o n t h or two weeks. Consequently, the nature of technical surprise will be dif ferent from what it was before. It will not be sufficient to know that the enemy has only fifty possible tricks a n d that you can counter every one of them, but you must also invent some Model ballistic rvh
52S
WAE
system of being able to counter t h e m practically at the instant they occur. It is not easy to guess h o w this is going to be done. Some of the tradi tional aspects of the use of the same weapon for several purposes a n d of limiting its use until you need it for defense may have some of the elements of an answer, However, this will probably mean that you will be forced not to " d o your worst" at all times, because then when the enemy does his worst you cannot defend against it, and the one thing you can put on at a n instant's notice, if you are strong enough, is power stepped up to the limits of your capabi lities. Hence, you may have to hold this t r u m p card in reserve. Without going further into the de tails of this matter 1 Just wish to in dicate generally that quite unconven tional methods of systems analysis and of operations analysis will bear fruit in the future, as they did in the past.
T
H I S is, I think, an especially fitting way to close. It brings us back to emphasize the enormous importance of the most powerful weapon of all; namely, the iexible type of h u m a n in telligence which we admire in D r . Robert H . Kent.
•: tested in Aberdeen':; supersonic wind :unr.ei.
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BIBLIOGRAPHY*
1922 1. With M. F E K E T E : Uber die Lage der Nullstellen gewisser Minimumpolynome, Jber. Dtsch. Math. Verein., 31:125-138 [1,2].+ 1923 2. Zur Einfiihrung der transfiniten Zahlen, Ada Szeged, 1:199-208 [1,3]. 1925 3. Eine Axiomatisierung der Mengenlehre, J. /. Math., 154:219-240 [1,4]. 4. Egyenletesen siiru szamsorozatok [Uniformly Dense Number Sequences], Math. Phys. Lapok, 32:32-40 [1,5]. 1926 5. Zur Priiferschen Theorie der idealen Zahlen, Ada Szeged, 2:193-227 [1,6]. 1927 6. With D. HILBERT and L. NORDHEIM: Uber die Grundlagen der Quantenmechanik, Math. Ann., 98:1-30 [1,7]. 7. Zur Theorie der Darstellungen kontinuierlicher Gruppen, Sitzungsber. d. Preufi. Akad. Wiss., 76-90 [1,8]. 8. Mathematische Begriindung der Quantenmechanik, Gott. Nachr., 1-57 [1,9]. 9 Wahrscheinlichkeitstheoretischer Aufbau der Quantenmechanik, Gott. Nachr., 245-272 [1,10]. 10. Thermodynamik quantenmechanischer Gesamtheiten, Gott. Nachr., 273-291 [i,n]. 11. Zur Hilbertschen Beweistheorie, Math. Zschr., 26:1-46 [1,12]. 1928 12. Eigenwertproblem symmetrischer Funktionaloperatoren, Jber. Dtsch. Verein., 37:11-14.
Math.
* The bibliography is confined to works that have appeared in print. Re-editions and trans lations are hsted only if published in the author's lifetime or with his possible participation. The list is presumably incomplete. Anyone who is able to complement it is asked to inform the editors. * Square-bracketed indications ([Volume, Number]) refer to A. H. Taub's edition: "Col lected Works", Pergamon Press, 6 vols., 1961-1963.
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13. Die Zerlegung eines Intervalles in abzahlbar viele kongruente Teilmengen, Fund. Math., 11:230-238 [1,13]. 14. Ein System algebraisch unabhangiger Zahlen, Math. Ann., 99:134-141 [1,14]. 15. Uber die Definition durch transfinite Induktion und verwandte Fragen der all gemeinen Mengenlehre, Math. Ann., 99:373-391 [1,15]. 16. Zur Theorie der Gesellschaftsspiele, Math. Ann., 100:295-320 [VI, 1]. [Trans lated by S. Bargmann: On the Theory of Games of Strategy, Contributions to the Theory of Games, Vol. IV (Ann. Math. Studies, No. 40), Princeton Univer sity Press, 1959, 13-42.] 17. Sur la theorie des jeux, C. R. Acad. Sci., 186:1698-1691. 18. Die Axiomatisierung der Mengenlehre, Math. Zschr., 27:669-752 [1,16]. 19. With E. W I G N E R : Zur Erklarung einiger Eigenschaften der Spektren aus der Quantenmechanik des Drehelektrons, I., Zschr. f. Phys., 47:203-220 [1,18]. 20. Einige Bemerkungen zur Diracschen Theorie des relativistischen Drehelektrons, Zschr. f. Phys., 48:868-881 [1,19]. 21. With E. WiGNER: Zur Erklarung einiger Eigenschaften der Spektren aus der Quantenmechanik des Drehelektrons, II., Zschr. f. Phys., 49:73-94 [1,19]. 22. With E. WiGNER: Zur Erklarung einiger Eigenschaften der Spektren aus der Quantenmechanik des Drehelektrons, III., Zschr. f. Phys., 51:844-858 [1,20]. 1929 23. Uber eine Widerspruchfreiheitsfrage in der axiomatischen Mengenlehre, J. f. Math., 160:227-241 [1,21]. 24. Uber die analytischen Eigenschaften von Gruppen linearer Transformationen und ihrer Darstellungen, Math. Zschr., 30:3-42 [1,22]. 25. With E. WiGNER: Uber merkwiirdige diskrete Eigenwerte, Phys. Zschr., 3 0 : 465-467 [1,23]. 26. With E. W I G N E R : Uber das Verhalten von Eigenwerten bei adiabatischen Prozessen, Phys. Zschr., 30:467-470 [1,24]. 27. Beweis des Ergodensatzes und des H-Theorems in der neuen Mechanik, Zschr. f. Phys., 57:30-70 [1,25]. 28. Zur allgemeinen Theorie des Mafies, Fund. Math., 13:73-116 [1,26]. 29. Zusatz zur Arbeit "Zur allgemeinen Theorie des Mafies", Fund. Math., 13 :333 [1,27]. 30. Allgemeine Eigenwerttheorie Hermitescher Funktionaloperatoren, Math. Ann., 102:49-131 [11,1]. 31. Zur Algebra der Funktionaloperatoren und Theorie der normalen Operatoren, Math. Ann., 102:370-427 [11,2]. 32. Zur Theorie der unbeschrankten Matrizen, J. f. Math., 161:208-236 [11,3]. 1930 33. Uber einen Hilfssatz der Variationsrechnung, Abh. Math. Semin. Hamb., 8: 28-31 [11,4].
Appendix
579 1931
34. Uber Funktionen von Funktionaloperatoren, Ann. Math., 32:191-226 [11,5]. 35. Algebraische Reprasentanten der Funktionen "bis auf eine Menge vom Mafie Null", J. f. Math., 165:109-115 [11,6]. 36. Die Eindeutigkeit der Schrodingerschen Operatoren, Math. Ann., 104:570-578 [11,7]. 37. Bemerkungen zu den Ausfiihrungen von Herrn St. Lesniewski uber meine Arbeit "Zur Hilbertschen Beweistheorie", Fund. Math., 17:331-334 [11,8]. 38. Die formalistische Grundlegung der Mathematik, Congress report, Konigsberg, September 1931, Erkenntnis, 2:116-121 [11,9]. 1932 39. Zum Beweise des Minkowskischen Satzes iiber Linearformen, Math. Zschr., 3 0 : 1-2 [11,10]. 40. Uber adjungierte Funktionaloperatoren, Ann. Math., 33:294-310 [11,11]. 41. Proof of the Quasi-Ergodic Hypothesis, Proc. Nat. Acad. Sci., 18:70-82 [11,12]. 42. Physical Applications of the Ergodic Hypothesis, Proc. Nat. Acad. Sci., 1 8 : 263-266 [11,13]. 43. With B. O. KOOPMAN: Dynamical Systems of Continuous Spectra, Proc. Nat. Acad. Sci., 18:255-263 [11,14]. 44. Uber einen Satz von Herrn M. H. Stone, Ann. Math., 33:567-573 [11,15]. 45. Einige Satze iiber mefibare Abbildungen, Ann. Math., 33:574-586 [11,16]. 46. Zur Operatorenmethode in der klassischen Mechanik, Ann. Math., 33:587-642 [11,17]. 47. Zusatze zur Arbeit "Zur Operatorenmethode...", Ann. Math., 33:789-791 [11,18]. 48. Mathematische Grundlagen der Quantenmechanik, Springer, Berlin. [Transla tions: Dover Publications, 1943; Presses Universitaires de France, 1947; Instituto de Matematicas "Jorge Juan", Madrid, 1949; Princeton University Press, 1955.] 1933 49. Die Einfuhrung analytischer Parameter in topologischen Gruppen, Ann. Math., 34:170-190 [11,19]. 50. A koordinata-meres pontossaganak hatarai az elektron Dirac-fele elmeleteben [Limits of the Accuracy of Coordinate Measurement in Dirac's Theory of Elec tron], Mat. es Termeszettud. Ertesito, 50:366-385 [11,20]. 1934 51. With P . JORDAN and E. W I G N E R : On an Algebraic Generalization of the Quantum Mechanical Formalism, Ann. Math., 35:29-64 [11,21].
Appendix
680
52. Zum Haarschen Mafi in topologischen Gruppen, Compos. Math., 1:106-114 [11,22]. [In Russian: Usp. Mat. Nauk, 1936, 168-176.] 53. Almost Periodic Functions in a Group, I, Bull. Amer. Math. Soc, 40:224. 54. Almost Periodic Functions in a Group, I, Trans. Amer. Math. Soc., 36:445-492 [11,23]. 55. With A. H. TAUB and O. VEBLEN: The Dirac Equation of Projective Relat ivity, Proc. Nat. Acad. Sci., 20:383-388 [11,24]. 1935 56. On Complete Topological Spaces, Bull. Amer. Math. Soc, 4 1 : 3 5 . 57. On Complete Topological Spaces, Trans. Amer. Math. Soc., 37:1-20 [11,25]. 58. With S. BOCHNER: Almost Periodic Functions in Groups, II, Bull. Amer. Math. Soc, 4 1 : 3 5 . 59. With S. BOCHNER: Almost Periodic Functions in Groups, II, Trans. Amer. Math. Soc, 37:21-50 [11,26]. 60. With S. BOCHNER: On Compact Solutions of Operational-Differential Equa tions, I, Ann. Math., 36:255-291 [IV, 1]. 61. Representations and Ray-Representations in Quantum Mechanics, Bull. Amer. Math. Soc, 41:305. 62. Charakterisierung des Spektrums eines Integraloperators, Actualites Scient. et Industr., No. 229; Exposes math., publies a la memorie de J. Herbrand, No. 13, Paris [IV,2]. 63. On Normal Operators, Proc Nat. Acad. Sci., 21:366-369 [IV,3]. 64. With P . JORDAN: On Inner Products in Linear, Metric Spaces, Ann. Math., 36:719-723 [IV,4]. 65. With M. H. STONE: The Determination of Representative Elements in the Residual Classes of a Boolean Algebra, Fund. Math., 25:353-378 [IV,5]. 1936 66. On a Certain Topology for Rings of Operators, Ann. Math., 37:111-115 [111,1]. 67. With F. J. MURRAY: On Rings of Operators, Ann. Math., 37:116-229 [111,2]. 68. On an Algebraic Generalization of the Quantum Mechanical Formalism (Part I), Mat. Shorn., 1:415-484 [111,9]. 69. On the Uniqueness of Invariant Lebesgue Measures, Bull. Amer. Math. Soc, 42 :343. 70. The Uniqueness of Haar's Measure, Mat. Shorn., 1:721-734 [IV,6]. 71. With G. B I R K H O F F : The Logic of Quantum Mechanics, Ann. Math., 3 7 : 8 2 3 843 [IV,7]. 72. Continuous Geometry, Proc. Nat. Acad. Sci., 22:92-100 [IV,8]. [Reprinted in 153.] 73. Examples of Continuous Geometries, Proc. Nat. Acad. Sci., 22:101-108 [IV,9]. [Reprinted in 153.]
Appendix
681
74. On Regular Rings, Proc. Nat. Acad. Sci., 22:707-713 [IV, 10]. [Reprinted in 153.] 75. With I. J. SCHOENBERG: Fourier Integrals and Metric Geometry, Bull. Amer. Math. Soc, 42:632. 76. With F . J. MURRAY: On Rings of Operators, II, Bull. Amer. Math. Soc, 4 2 : 808. 1937 77. With K. KURATOWSKI: On Some Analytic Sets Defined by Transfinite Induc tion, Ann. Math., 38:521-525 [IV, 19]. 78. With I. HALPERIN: On the Transitivity of Perspective Mappings in Comple mented Modular Lattices, Bull. Amer. Math. Soc, 43 :37. 79. With F . J. MURRAY: On Rings of Operators, II, Trans. Amer. Math. Soc, 4 1 : 208-248 [111,3]. 80. Some Matrix-Inequalities and Metrization of Matric-Space, Izv. Tomsk. Gos. Univ., 1:286-300 [IV,20]. 81. Algebraic Theory of Continuous Geometries, Proc. Nat. Acad. Sci., 23:16-22 [IV, 11]. [Reprinted in 153.] 82. Continuous Rings and Their Arithmetics, Proc Nat. Acad. Sci., 23:341-349 [IV, 12]. [Reprinted in 153.] 83. Uber ein okonomisches Gleichungssystem und eine Verallgemeinerung des Brouwerschen Fixpunktsatzes, Erg. eines Math. Coll., Vienna, ed. by K. Menger, 8:73-83. [Translated in 112.] 1938 84. On Infinite Direct Products, Compos. Math., 6:1-77 [111,6]. 1940 85. With I. HALPERIN: On the Transitivity of Perspective Mappings, Ann. Math., 41:87-93 [IV, 13]. 86. With J. F . MURRAY: On Rings of Operators, III, Ann. Math., 41:94-161 [HI,4]. 87. With E. WlGNER: Minimally Almost Periodic Groups, Ann. Math., 41:746750 [IV,21]. 88. With R. H. K E N T : The Estimation of the Probable Error from Successive Differences, Report No. 175, Ballistic Research Laboratory, Aberdeen Proving Ground, Md., February 14. 89. With I. J. SCHOENBERG: Fourier Integrals and Metric Geometry, II, Bull. Amer. Math. Soc, 45 : 79. 1941 90. With R. H. K E N T , H. R. BELLINSON and B. I. HART: The Mean Square Successive Difference, Ann. Math. Stat, 12:153-162 [IV,33].
Appendix
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91. With I. J. SCHOENBERG: Fourier Integrals and Metric Geometry, Trans. Amer. Math. Soc, 50:226-251 [IV,22]. 92. Distribution of the Ratio of the Mean Square Successive Difference to the Vari ance, Ann. Math. Stat, 12:367-395 [IV,34]. 93. Shock Waves Started by an Infinitesimally Short Detonation of Given (Positive and Finite) Energy, Informal Report to the National Defense Research Committee, Div. B, AM-9, June 30. 94. Optimum Aiming at an Imperfectly Located Target, Appendix to Optimum Spacing of Bombs or Shots in the Presence of Systematic Errors, by L. S. Dederick and R. H. Kent, Ballistic Research Laboratory, Report 241, July 3 [IV,37]. 95. With P . R. HALMOS: Operator Methods in Classical Mechanics, II, Bull Math. Soc, 47:696.
Amer.
1942 96. A Further Remark Concerning the Distribution of the Ratio of the Mean Square Successive Difference to the Variance, Ann. Math. Stat, 13:86-88 [IV,35]. 97. With P . R. HALMOS: Operator Methods in Classical Mechanics, II, Ann. Math., 43:332-350 [IV,23]. 98. With S. CHANDRASEKHAR: The Statistics of the Gravitational Field arising from a Random Distribution of Stars, I, Astrophys. J., 95:489-531 [VI, 12]. 99. Note to "Tabulation of the Probabilities for the Ratio of the Mean Square Successive Difference to the Variance" by B. I. Hart, Ann. Math. Stat, 1 3 : 207-214 [IV,36]. 100. Approximative Properties of Matrices of High Finite Order, Portug. Math., 3 : 1-62 [IV,24]. 101. Theory of Detonation Waves, Progress Report to the National Defense Research Committee Div. B, OSRD-549, May 4 [VI,20]. 1943 102. With F . J. [111,5].
MURRAY:
On Rings of Operators, IV, Ann. Math., 44:716-808
103. With S. CHANDRASEKHAR: The Statistics of the Gravitational Field Arising from a Random Distribution of Stars, II, Astrophys. J., 97:1-27 [VI, 13]. 104. On Some Algebraical Properties of Operator Rings, Ann. Math., 44:709-715 [111,8]. 105. With R. J. SEEGER: On Oblique Reflection and Collison of Shock Waves, PB 31918 September 20. 106. Theory of Shock Waves, Progress Report to the National Defense Research Committee, Div. 8, U.S. Dept. Comm. Off. Tech. Serv. PB 32719 [VI, 19]. 107. Oblique Reflection of Shocks, Explosion Research Report No. 12, Navy Dept., Bureau of Ordnance, U.S. Dept. Comm. Off. Tech. Serv. PB 37079, October 12 [VI,22].
Appendix
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1944 108. With O. MORGENSTERN: Theory of Games and Economic Behavior, Princeton University Press, [Subsequent, enlarged editions: 1947, 1953.] [Cf. also 155.] 109. Proposal and Analysis of a New Numerical Method for the Treatment of Hydrodynamical Shock Problems, submitted to the Applied Mathematics Panel, National Defense Research Committee, OSRD-3617, March 20 [VI,27]. 110. Introductory Remarks (Sec. I), Theory of the Spinning Detonation (Sec. XII), Theory of the Intermediate Product (Sec. XIII), Report of the Informal Technical Conference on the Mechanism of Detonation, AM-570, April 10. 111. Riemann Method; Shock Waves and Discontinuities (one-dimensional), Two-Di mensional Hydrodynamics, Shock Hydrodynamics and Blast Waves, by H. A. Bethe, K. Fuchs, J. von Neumann, R. Peierls and W. G. Penney, Notes by J. O. Hirschfelder, AECD-2860, October 28. 1945 112. A Model of General Economic Equilibrium, Rev. Econ. Studies, 13:1-9 [VI,3]. [Translation of 83 by O. Morgenstern.] 113. Refraction, Intersection and Reflection of Shock Waves,Conference on Supersonic Flow and Shock Waves, held March 15, Navy Bureau of Ordnance, NAVORD Report 203, AM-1663, July 16, 4-12 [VI,23]. 114. With A. H. TAUB: Flying Wind Tunnel Experiments, PB 33263, November 5. 115. With S. M. ULAM: Random Ergodic Theorems, Bull. Amer. Math. Soc, 5 1 : 660. 116. First Draft of a Report on the EDVAC, Report prepared for the U.S. Army Ordnance Department and the University of Pennsylvania, under Contract W670-ORD-4926, June 30, Summary Report No. 2, ed. by J. P. Eckert, J. W. Mauchly and S. R. Warren, July 10 [The typescript original of this report has been re-edited by M. D. Godfrey: IEEE Ann. Hist. Comp., Vol. 15, No. 4, 1993, 27-75.] 1946 117. With V. BARGMANN and D. MONTGOMERY: Solution of Linear Systems of High Order, Report prepared for the Navy Bureau of Ordnance, under Contract NORD-9596, October 25 [V,13]. 118. With A. W. BURKS and H. H. GOLDSTINE: Preliminary Discussion of the Logical Design of an Electronic Computing Instrument, Part I, Vol. I, Report pre pared for U.S. Army Ord. Dept. under Contract W-36-034-ORD-7481 [V,2]. [Second ed.: 1947.] 119. With R. SCHATTEN: The Cross-Space of Linear Transformations, II, Bull. Amer. Math. Soc, 52:67. 120. With R. SCHATTEN: The Cross-Space of Linear Transformations, II, Ann. Math., 47:608-630 [IV,29].
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1947 121. The Mathematician, The Works of the Mind, ed. by R. B. Heywood, University of Chicago Press, 180-196 [1,1]. 122. The Future Role of Rapid Computing, Meteorology, Aeronautical Engineering Review, 6, 4:30. 123. With H. H. GOLDSTINE: Numerical Inverting of Matrices of High Order, Bull. Amer. Math. Soc, 53:1021-1099 [V,14]. 124. With H. H. GOLDSTINE: Planning and Coding of Problems for an Electronic Computing Instrument, Part II, Vol. 1, Report prepared for U.S. Army Ord. Dept. under Contract W-36-034-ORD-7481 [V,3]. 125. With R. D. RICHTMYER: Statistical Methods in Neutron Diffusion, Los Alamos Sci. Lab. Rept. LAMS-551, April 9 [V,21]. 126. The Point Source Solution, Chapt. 2 of Blast Wave, Los Alamos Sci. Lab. Tech Series, Vol. VII Pt. II, LA-2000, ed. by H. Bethe, August 13, 27-55 [VI,21]. 127. With F. REINES: The Mach Effect and the Height of Burst, [declassified] part of Chap. 10 of Blast Wave, LA-2000, ed. by H. Bethe, August 13, X-ll-X-84 [VI, 24]. 128. With R. D. RICHTMYER: On the Numerical Solution of Partial Differential Equations of Parabolic Type, LA-657, December 25 [V,18]. 129. With E. R. LORCH: On the Euclidean Character of the Perpendicularity Re lation, Bull. Amer. Math. Soc, 53:489. 130. With S. ULAM: On the Group of Homeomorphisms of the Surface of the Sphere, Bull. Amer. Math. Soc, 53:506. 131. On Combination of Stochastic and Deterministic Processes, Bull. Amer. Math. Soc, 53:1120. 132. With H. H. GOLDSTINE: Some Estimates on the Numerical Stability of the Elimination Method for Inverting Matrices of High Order, Bull. Amer. Math. Soc, 53:1123. 1948 133. With H. H. GOLDSTINE: Planning and Coding of Problems for an Electronic Computing Instrument, Part II, Vol. 2, Report prepared for U.S. Army Ord. Dept. under Contract W-36-034-ORD-7481 [V,4]. 134. With H. H. GOLDSTINE: Planning and Coding of Problems for an Electronic Computing Instrument, Part II, Vol. 3, Report prepared for U.S. Army Ord. Dept. under Contract W-36-034-ORD-7481 [V,5]. 135. On the Theory of Stationary Detonation Waves, File No. X122, Ballistic Re search Laboratory, Aberdeen Proving Ground, Md., September 20. 136. With R. SCHATTEN: The Cross-Space of Linear Transformations, III, Bull Amer. Math. Soc, 54 : 637. 137. With R. SCHATTEN: The Cross-Space of Linear Transformations, III, Ann. Math., 49:557-582 [IV,30].
Appendix
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1949 138. N. Wiener's "Cybernetics", Review, Physics Today, 2:33-34. 139. On Rings of Operators. Reduction Theory, Ann. Math., 50:401-485 [111,7]. 1950 140. With R. D. RICHTMYER: A Method for the Numerical Calculation of Hydrodynamic Shocks, J. Appl. Phys., 21:232-237 [VI,28]. 141. Functional Operators, Vol. I: Measures and Integrals, Vol. II: The Geometry of Orthogonal Spaces (Ann. Math. Studies, Nos. 21 and 22), Princeton University Press. 142. With G. W. BROWN: Solutions of Games by Differential Equations, Contributions to the Theory of Games, (Ann. Math. Studies, No. 24), Princeton Uni versity Press, 73-79 [VI, 4]. 143. With N. C. METROPOLIS and G. REITWIESNER: Statistical Treatment of Val ues of First 2000 Decimal Digits of e and of n Calculated on the ENIAC, Math. Tables Aids Comput., 4:109-111 [V,22]. 144. With J. G. CHARNEY and R. F J O R T O F T : Numerical Integration of the Barotropic Vorticity Equation, Tellus, 2:237-254 [VI,30]. 145. With I. E. SEGAL: A Theorem on Unitary Representations of Semisimple Lie Groups, Ann. Math., 52:509-517 [IV,25]. 1951 146. Eine Spektraltheorie fur allgemeine Operatoren eines unitaren Raumes, Math. Nachr., 4:258-281 [IV,26]. 147. The Future of High-Speed Computing, Digest of an address at the IBM Seminar on Scientific Computation, November 1949, Proc. Comp. Sem., IBM, 13 [V,6]. 148. Discussion on the Existence and Uniqueness or Multiplicity of Solutions of the Aerodynamical Equations, Chapter 10 of Problems of Cosmical Aerodynamics, Proceedings of the Symposium on the Motion of Gaseous Masses of Cosmical Dimensions held at Paris, August 16-19, 1949, Central Air Doc. Office, 75-84 [VI,25]. 149. With H. H. GOLDSTINE: Numerical Inverting of Matrices of High Order, II, Amer. Math. Soc. Proc, 2:188-202 [V,15]. 150. Various Techniques Used in Connection with Random Digits, Chapter 13 of "Proceedings of Symposium on 'Monte Carlo Method'", held June-July 1949 in Los Angeles, Summary written by G. E. Forsythe, J. Res. Nat. Bur. Stand., Appl. Math. Series, 3:36-38 [V,23]. 151. The General and Logical Theory of Automata, Cerebral Mechanisms in Behavior — The Hixon Symposium, September 20, 1948, Pasadena, ed. by L. A. Jeffress, John Wiley, 1-31 [V,9]. 1952 152. Shape of Metal Grains, Discussion contribution concerning "Grain Shapes and Other Metallurgical Applications of Topology" by C. S. Smith, Metal Interfaces, Amer. Soc. for Metals, Cleveland, Ohio, 108-110 [VI,41].
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153. Five Notes on Continiuous Geometry, prepared by W. Givens, Univ. of Tenn. [Contains 72, 73, 74, 81 and 82.] 1953 154. A Certain Zero-Sum Two-Person Game Equivalent to the Optimal Assignment Problem, Seminar talk, October 26, 1951, Notes by H. Rogers, Jr., Contributions to the Theory of Games, Vol. II (Ann. Math. Studies, No. 28), Princeton University Press, 5-12 [VI,5]. 155. With D. B. GILLES and J. P . MAYBERRY: TWO Variants of Poker, Contributions to the Theory of Games, Vol. II (Ann. Math. Studies, No. 28), Princeton University Press, 13-50 [VI,6]. [Supplement to 108.] 156. With H. H. GOLDSTINE: A Numerical Study of a Conjecture of Kummer, Math. Tables Aids Comput., 7:133-134 [V,24]. 157. Communication on the Borel Notes, Econometr., 21:124-125 [VI,2]. 158. With E. F E R M I : Taylor Instability at the Boundary of Two Incompressible Liquids, Los Alamos Sci. Lab. Rept. AECU-2979, Part II, August 19, 7-13 [VI,31]. 1954 159. With E. P . WlGNER: Significance of Loewner's Theorem in the Quantum The ory of Collisions, Ann. Math., 59:418-433 [IV,27]. 160. The Role of Mathematics in the Sciences and in Society. Address at J^th Conference of Association of Princeton Graduate Alumni, June, 16-29 [VI,35]. 161. A Numerical Method to Determine Optimum Strategy, Naval Res. Logistics Quart, 1:109-115 [VI,7]. 162. The NORC and Problems in High Speed Computing, Address on the occasion of the first public showing of the IBM Naval Ordnance Research Calculator, December 2 [V,7]. 163. Entwicklung und Ausnutzung neuerer mathematischer Maschinen, Arbeitsgemeinschaft fur Forschung des Landes Nordrhein- Westfalen, Fasc. 45, Diisseldorf [V,8]. 1955 164. With B. TUCKERMAN: Continued Fraction Expansion of 2*, Math. Tables Aids Comput, 9:23-24 [V,25]. 165. With A. DEVINATZ and A. E. NUSSBAUM: On the Permutability of SelfAdjoint Operators, Ann. Math., 62:199-203 [IV,28]. 166. With H. H. GOLDSTINE: Blast Wave Calculation, Comm. Pure Appl. Math., 8:327-353 [VI,29]. 167. Method in the Physical Sciences, The Unity of Knowledge, ed. by L. Leary, Doubleday, 157-164 [VI,36]. 168. Can We Survive Technology? Fortune, June [VI,38].
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169. Impact of Atomic Energy on the Physical and Chemical Sciences, Speech at M.I.T. Alumni Day Symposium, June 13, Summary, Tech. Rev., 15-17 [VI,39]. 170. Defense in Atomic War, Paper delivered at a symposium in honor of Dr. R. H. Kent, December 7, 1955, The Scientific Bases of Weapons, Journ. Am. Ordnance Assoc, 21-23 [VI,40]. 1956 171. Probabilistic Logics and the Synthesis of Reliable Organisms from Unreli able Components, January 1952, Calif. Inst. of Tech., Lecture notes taken by R. S. Pierce and revised by the author, Automata Studies, ed. by C. E. Shannon and J. McCarthy, Princeton University Press, 43-98 [V,10]. 172. The Impact of Recent Developments in Science on the Economy and on Eco nomics, Partial text of a talk at the National Planning Assoc, Washington, D.C., December 12, 1955, Looking Ahead, 4:11 [VI,11]. 1957 173. With S. RUSHTON: Some Applications of Time Series Analysis to Atmospheric Turbulence and Oceanography, J. Roy. Statist. Soc, Ser. A, 120:409-439. 1958 174. The Computer and the Brain, Silliman Lectures, Yale University Press. 175. The Non-Isomorphism of Certain Continuous Rings (with introduction by I. Kaplansky), Ann. Math., 67:485-496 [IV, 14]. 1959 176. With H. H. GOLDSTINE and F. J. MURRAY: The Jacobi Method for Real Symmetric Matrices, Revised version of a lecture presented August 1951 on a Los Angeles Symposium at the National Bureau of Standards, J. Assoc. Computing Machinery, 6 : 59-96 [V, 16]. 177. With A. BLAIR, N. METROPOLIS, A. H. TAUB and M. TSINGOU: A Study of a Numerical Solution to a Two-Dimensional Hydrodynamical Problem, Con densation of Los Alamos Sci. Lab. Rept. LA-2165, Math. Tables Aids Comput., 13:145-184 [V,17]. 1960 178. Continuous Geometry, with an introduction by I. Halperin, Princeton Univer sity Press. 1961 179. Comparison of Cells, Manuscript, reviewed by G. Hunt, Collected Works, I I : 558 [11,27]. 180. Characterization of Factors of Type Hi, Draft manuscript, reviewed by I. Kaplansky, Collected Works, 111:562-563 [111,10].
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1962 181. Independence of Foo from the Sequence v. Manuscript, reviewed by I. Halperin, Collected Works, I V : 189-190 [IV,15]. 182. Continuous Geometries with a Transition Probability, Manuscript, 1937, re viewed by I. Halperin, Collected Works, I V : 191-194 [IV, 16]. 183. Quantum Logics (Strict- and Probability-Logics), Manuscript, unfinished, ca. 1937, reviewed by A. H. Taub, Collected Works, I V : 195-197 [IV, 17]. 184. Lattice Abelian Groups, Manuscript, 1940, reviewed by G. Birkhoff, Collected Works, I V : 198-199 [IV, 18]. 185. Measure in Functional Spaces, Manuscript, prob. 1934-35, reviewed by I. Halperin, Collected Works, IV:435-438 [IV,31]. 186. Representation of Certain Linear Groups by Unitary Operators in Hilbert Space, Manuscript, 1939, reviewed by G. W. Mackey, Collected Works, I V : 439-441 [IV,32]. 1963 187. With H. H. GOLDSTINE: On the Principles of Large Scale Computing Machines, Lecture manuscript, prior to May 15, 1946, Collected Works, V : l - 3 3 [ V , l ] . 188. Non-Linear Capacitance or Inductance Switching, Amplifying and Memory De vices, Basic paper for Patent 2,815,488, filed April 28, 1954, granted December 3, 1957, assigned to IBM, Collected Works, V:379-419 [ V , l l ] . 189. Notes on the Photon-Disequilibrium-Amplification Scheme, Manuscript, Sep tember 16, 1953, reviewed by J. Bardeen, Collected Works, V : 420 [V,12]. 190. First Report on the Numerical Calculation of Flow Problems, prepared for Standard Oil Development Company, June 22 - July 6, 1948, Collected Works, V:664-712, [V,19]. 191. Second Report on the Numerical Calculation of Flow Problems, prepared for Standard Oil Development Company, July 25-August 22, 1948, Collected Works, V : 713-750, [V,20]. 192. Discussion of a Maximum Problem, Typescript, November 15-16, 1947, ed. by H. W. Kuhn and A. W. Tucker, Collected Works, VI:89-95 [VI,8]. 193. A Numerical Method for Determination of the Value and the Best Strate gies of a Zero-Sum Two-Person Game with Large Numbers of Strategies, Manuscript/Mimeograph, 1948, reviewed by H. W. Kuhn and A. W. Tucker, Collected Works, VI: 96-97 [VI,9]. 194. Symmetric Solutions of Some General TV Person Games, Manuscript, 1946, reviewed by D. B. Gillies, Collected Works, VI:98-99 [VI, 10]. 195. Static Solutions of Einstein Field Equations for Perfect Fluid with Tg = 0, Manuscript, 1935, reviewed by A. H. Taub, Collected Works, V I : 172 [VI, 14]. 196. On Relativistic Gas-Degeneracy and the Collapsed Configurations of Stars, Notes, 1935, reviewed by A. H. Taub, Collected Works, V I : 173-174 [VI, 15]. 197. The Point-Source Model, Manuscript, reviewed by A. H. Taub, Collected Works, V I : 175 [VI, 16],
Appendix
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198. The Point-Source Solution, assuming a Degeneracy of the Semi-Relativistic Type, p = Kp4/3, over the Entire Star, Manuscript, reviewed by A. H. Taub, Collected Works, V I : 176 [VI,17]. 199. Discussion of De Sitter's Space and of Dirac's Equation in it, Manuscript, 1940, reviewed by A. H. Taub, Collected Works, V I : 177 [VI, 18]. 200. Use of Variational Methods in Hydrodynamics, Memorandum to O. Veblen, March 26, 1945, Collected Works, VI:357-360 [VI,26]. 201. The Taylor Instability Problem, Manuscript, ca. 1953, reviewed by H. H. Goldstine, Collected Works, VI:435-436 [VI,32]. 202. Recent Theories of Turbulence, Report to the Office of Naval Research, 1949, Collected Works, VI:437-472 [VI,33]. 203. Description of the Conformal Mapping Method for the Integration of Partial Differential Equation Systems with 1-1-2 Independent Variables, Manuscript, December 16, 1950, - January 8, 1951, reviewed by A. H. Taub, Collected Works, VI:473-476 [VI,34]. 204. Statement before the Special Senate Committee on Atomic Energy, Manuscript, prepared prior to the January 31, 1946, hearing, Collected Works, V I : 499-502 [VI,37]. [For minutes of the actual testimony cf. Atomic Energy Act of 1946, U.S. Printing Office.] 1966 205. Theory of Self-Reproducing Automata, edited and completed by A. W. Burks, University of Illinois Press, Urbana. 1990 206. With H. H. GOLDSTINE: On the Principles of Large Scale Computing Ma chines, Manuscript, 1946, The Legacy of John von Neumann, ed. by J. Glimm, J. Impagliazzo and I. Singer, Amer. Math. Soc, Providence, RI, 179-184.
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C U R R I C U L U M VITAE*
Undersigned Dr. Johann Ludwig von Neumann, I was born on 28 Decem ber 1903 in Budapest (Hungary), son of the banker Dr. Max von Neumann and his wife Gitta (nee Kann). Attended primary and secondary schools during the years 1909-1921 in Budapest, the latter at the Evangelical Gymnasium [grammar school]. From autumn 1921 studied mathematics, physics and chemistry at the following Colleges: winter term 1921 - summer term 1923 at Berlin Univer sity, winter term 1923 - summer term 1926 at the Eidg[enossische] Techn[ische] Hochschule Zurich [Zurich Confederate College for Technics]. At the latter, passed the examination for the diploma in chemistry in October 1926. Be sides, in the period winter term 1921 - summer term 1925, was registered at the Budapest University and received a doctorate in mathematics in March 1926. Stayed in the winter term 1926 at Gottingen with a scholarship granted by the International Education Board. My mathematical publications until now are as follows: 1. Uber die Nullstellen gewisser Minimumpolynome. (With M. Fekete, Jahresber. d. Deut. Math. Verein., 1921.) 2. Zur Einfiihrung der transfiniten Zahlen. (Acta lit. ac sc. Univ. Franc. Jos., Szeged, 1923.) 3. Eine Axiomatisierung der Mengenlehre. (Journal f. reine u. angew. Math., 1924.) 4. Uniformly dense number sequences. (Hungarian, Comm. of the Hung. Acad. of Sci., 1926.) 5. Zur Priiferschen Theorie der idealen Zahlen. (Acta lit. ac sc. Univ. Franc. Jos., Szeged, 1926.) 6. Zur Hilbertschen Beweistheorie. (Math. Zeitschr., 1927.) 7. Zur Theorie der Darstellungen kontinuierlicher Gruppen. (Mitt, der preufi. Akad., in print.) 8. Die analytischen Eigenschaften von Gruppen linearer Transformationen und ihrer Darstellungen. (Math. Zeitschr., accepted.) * Submitted to Berlin (then: Friedrich Wilhelm) University in 1927. Referents were E. Schmidt and Schur, the committee were Bieberbach, von Mises, Planck, von Laue, Schottky, Nernst, Kopff, Kohlschiitter; decision: admitted.
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9. Die Axiomatisierung der Mengenlehre. (Math. Zeitschr., accepted.) 10. Ein System algebraisch unabhangiger Zahlen. (Math. Annalen, accepted.) 11. Uber die Theorie der Ordnungszahlen und verwandte Fragen der allgemeinen Mengenlehre. (Math. Annalen, accepted.) 12. Zur Jordanschen Quantenmechanik. (With Hilbert and L. Nordheim, Math. Annalen, in print.) The enclosures to my application contain offprints, resp. proofsheets, of items 1-7, item 9 is my Habilitationsschrift [dissertation submitted to obtain the venia legendi at the university]. Respectfully yours, Dr. Johann von Neumann Budapest Vilmos csaszar lit [Kaiser Wilhelm Street] 62.
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A LETTER TO L. FEJER
Berlin, 7.12.1929 Honored Professor, I have had several conversations with Leo Szilard about the schoolchildren's competitions of the math. phys. society, and about the fact that the first-ranking placeholders in these competitions virtually coincide with the set of those mathematicians and physicists that proved able afterwards. Whereas, considering the overall bad renown of exams, it's a big thing even if a selection like this gets it 50% right. Szilard is very interested in the applicability of this procedure under German conditions, also a subject of a lot of chat among us. Since it's first of all the reliable statistical facts we wish to get to know, we are approaching you, Professor, with the following request. We would like very much to get acquainted with 1.) the list of names of those placed first and second in the schoolchildren's competitions, 2.) an indication of those among them who proved able scientifically or otherwise, 3.) your opinion, Professor, as to what extent prizewinners and talented peo ple are identical and, e.g., what proportion of the former would deserve state support to enable their studying. I apologize for asking you, Professor, a favor so tiresome, still, we would be greatly indebted if there were any possibility to obtain the information inquired—or a hint as to how to get at the material mentioned. I am staying here until the 17th. Thanking you, Professor, in anticipation, I remain your grateful student, Neumann Jancsi Berlin, Kurfurstendamm 233, c/o Goldschmidt
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A N INTERVIEW FOR "VOICE OF AMERICA"*
HALASZ Dear Listeners, the simply but elegantly furnished office where Professor John von Neumann is sitting with me in front of the microphone of the Voice of Free Hungary is located in the Washington bureau of the United States Atomic Energy Commission, the headquarters of a new era. In October of last year Professor Neumann was appointed to this five-member committee and his appointment was unanimously confirmed by the American Senate a month ago. Thus the Professor, both in his quality as an official and as a scientist—belongs to that restricted and most important group that in the long run directs the most radical new developments of world history. Professor Neumann is a Hungarian. This fact fills all of us with just pride, and I am sure that the Professor understands my feelings and the feelings of those who at this moment listen to our broadcast. PROF. NEUMANN I am very glad that you point this out. HALASZ I would like to describe Professor Neumann in a few words to our listeners. He is around fifty, has glittering brown eyes and a face always ready for a smile. I hope you don't mind my saying so, Professor, but I have found during our conversation that nothing is easier than to make you smile. After this introduction I would like to talk about Professor Neumann's scientific background—an impressive subject indeed, dear Listeners. Still, I would like to ask you briefly to tell us where and what you studied and when you left Hungary. Would you, Professor Neumann, tell us in a few words about this... PROF. NEUMANN I was born in Budapest in 1903 and attended high school there, graduating in 1921. Subsequently I attended the universities resp. the polytechnics of Berlin and Zurich and obtained my doctorate in math ematics, or rather philosophy, in Budapest in 1925. I graduated as a chemical engineer in Zurich in 1926 and mostly lived in Germany until 1930. I was an assistant professor of mathematics at the University of Berlin. I came to America in 1930, notably to Princeton University... * Given in Hungarian for the program "Voice of Free Hungary", April 13, 1955; the inter viewer was Louis Halasz. The text is "Voice of America" 's own English translation of the interview, translated by H. Zerkowitz and revised by von Neumann; Manuscript Division, Library of Congress.
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696 HALASZ
Were you invited there?
PROF. NEUMANN Yes. HALASZ How did this invitation come about, Professor? PROF. NEUMANN My colleague of those days and today, Professor Veblen, was a professor at Princeton at the time. He invited me. I met him in 1928 at an international conference in Bologna. HALASZ And then what happened? PROF. NEUMANN I was permanently established in Princeton since 1933 when I was appointed to a newly organized research institute called the Institute for Advanced Study. I am one of the professors attached to the Institute. HALASZ I understand that the Institute is one of the most advanced of its kind in the whole world? PROF. NEUMANN It conducts research work and post-doctoral work. Those who come to the Institute—a yearly average of 200—have completed their university studies and come for post-doctoral studies and research work. HALASZ You, Professor von Neumann, were one of the first to be appointed to this newly organized institute... PROF. NEUMANN Mine was the third or fourth appointment. The first was Prof. Einstein. HALASZ This fact in itself indicates Professor NeumannJs importance in American scientific life. I would like to ask you whether you still remembered the old times in Budapest, some of the professors maybe with whom you worked or who used to teach you. PROF. NEUMANN Oh, I remember very well, most vividly, especially Lipot Fejer and Frigyes Riesz who, I believe, are still in Budapest, then Alfred Haar who, alas, died in the early thirties. HALASZ
They were...
PROF. NEUMANN I owe a lot to all of them, they had great influence on me. HALASZ Relatively many Hungarians are active in the atomic research of the United States. Could you perhaps tell us something about these Hungarian colleagues of yours? PROF. NEUMANN Many Hungarians played important roles in this research, much more important than I. I think Leo Szilard must be mentioned in the first place, then Jeno Wigner and Ede Teller.
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HALASZ / know that you are a modest man, Professor, but I want to point out here that Ede Teller, who is considered the father of the hydrogen bomb by the press and the public, has the greatest admiration for you and has declared that without your work it would have been impossible to achieve the atomic fusion at this early date. PROF. NEUMANN In this field the bulk of my work was connected with the extremely fast computers introduced in America during those years. I have done quite a lot of work in this field, and we have built a few huge and extremely fast computers that have considerably speeded up every type of calculation in the field of physics or applied mathematics, and generally replaced random experimentation with more carefully planned and selected experiments. There is no doubt about it that all research work would be slower, more difficult, more expensive and less bold with out this type of machinery. HALASZ How does such a large computer work? PROF. NEUMANN Actually it doesn't do anything that a man couldn't do, it merely does it much faster. A really modern big machine for example easily does the work of about 10 000 men. And these figures are even higher today. Actually, the important thing is not fastness but the fact that if these calculations were slower one would simply omit them and guess. HALASZ And I believe that guessing in these new fields is pretty expensive and takes up much precious time. PROF. NEUMANN Yes, guessing is expensive and takes up much time, but also, if one is reduced to guessing, it is much harder to make up one's mind to venture into new and unknown fields, to try out new ideas and generally one is less inclined to exploit and experiment with new ideas. HALASZ How come that you as a mathematician have come into such close contact with atomic research? PROF. NEUMANN There are two categories of mathematicians: the so-called pure and the so-called applied mathematicians. This borderline however, as usual, is not too clearly defined and it happens many times that the same man works in both fields. I suppose I could call myself a pure mathematician, but I had a lot to do with applied mathematics too, especially with the quantum theory or atom physics and with hydrody namics, which is the theory of the movement of liquids and gasses. The transition from these fields is close at hand. HALASZ Did you, Professor Neumann, collaborate with Professor Einstein?
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698 PROF. NEUMANN
I did.
HALASZ / believe this in itself must have directed your interest toward the quantum theory and through it, atomic research. PROF. NEUMANN
Of course.
HALASZ Which is very fortunate, since this is how it happened that you, Professor Neumann, became one of the foremost champions of this modern science... I would like to ask you now, Professor Neumann—since one of your main problems here at the Atomic Energy commission is the peaceful use of atomic energy—what it would mean to Hungary if it would be possible and permitted to really freely and seriously deal with these modern problems there; what it would mean to Hungary if you for example and other Hungarian scientists were allowed to use their knowledge in this field in the interest of Hungary and the Hungarian people? NEUMANN At least two aspects of the peaceful use of atomic energyare especially important. No one, of course, can know whether there will be many more aspects in the future. Of obvious practical importance today is the fact that it is now possible to produce artificial radioactive elements in considerable quantities and at a much lower cost than in the past; also, that energy can be produced by entirely new methods and without practically any fuel. The first fact means that radio-active elements may be used in medical science, physiology, agriculture and in various branches of industry like metallurgy, etc., and all this will operate more smoothly and effectively than before. The changes in the field of energy production are even more obvious. The fact is that it will be an important thing even in America where energy is extremely cheap and is consumed in great quantities, because even though energy is cheap as it is, the huge consumption makes every further price reduction significant. On the other hand in countries like, I think, Hungary for example, where energy is relatively expensive and the per capita energy consumption is lower, the fact that a considerably cheaper energy source will be opened will bring substantial changes and render a higher per capita energy consumption possible. There is little doubt about it that in the past every industrialization and industrial development critically depended on cheaper energy and it is equally without doubt that this will have a great qualitative effect in countries where the coal and hydraulic resources are scarce.
PROF.
HALASZ / believe we can truly say that the use of atomic energy—though still in its early stages—will open up an entirely new era before mankind, an era of abundance unparalleled in history...
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PROF. NEUMANN Undoubtedly, this is the beginning of a new industrial revolution which is at least as important as the introduction of electricity, and today it is impossible as yet to predict its possible consequences and all the things it will affect. HALASZ And in order to benefit from all these it would be necessary that Hungary, too, be allowed to participate in this progress... PROF. NEUMANN I believe that it will be the absolute and vital interest of all countries and positively of Hungary too, to take part in the indus trial development resulting from this, and not be handicapped by being excluded from it or else participating in it only slowly and to a lesser degree. HALASZ One more question, Professor Neumann, which I could almost say, logically follows all that we have talked about, namely: if it were possible would you be willing to take part in the work aiming to further the use of atomic energy in Hungary? PROF. NEUMANN
That would, no doubt, be a very tempting opportunity...
HALASZ Do you think that other Hungarians working in this field would also be willing to use their knowledge in the interest of Hungary? PROF. NEUMANN
I am sure of it.
HALASZ Dear Listeners, I think the Professor's time has run out and we are forced to take leave from him. In the name of our Hungarian listeners I want to thank you very much for your cooperation, Professor. Dear Listeners, you have just heard Professor John von Neumann, a member of a small and select group of American atom scientists. Our conversation took place in the Washington headquarters of the U.S. Atomic Energy Commission, to which Professor Neumann was appointed some time ago by President Eisenhower.