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{t) > Co > 0), the operator F defined above is a monotone operator. Indeed, under this condition, for (t) is fort tGG[0,1]. [0,1]. Suppose Supp differentiable •ble on [0,1], we have cp'(t) gardJ(toi 0 0 >(0)>0 (/?(») >0 '(0) ip'(t) == '(*) ^'(0) V'(9) 0, ,/*)= / fvdx+ Jn 0 ¥»(<)* >0. 0, ¥>(*)<« >0, 0 be given and assume that a finite index set of natural numbers, A, is also given. Moreover, let N0(A, e) = {xeX 0 such that \u(x)\ < C almost everywhere on Q, where | • | is the absolute value. Clearly, LP(Q) (1 < p < oo) is a linear space. Let IMIo, P> n= j / Kx)P>dxi ||^||O,CX),Q perties: srties: approximation by by the the operator operator JJ££ defined defined in in (Bl) (Bl) has has the the following following properties: properties: J£ueLp(n)nC°°(RN),
fe=0 fc=0
Hence, we have £(yo) = -e(DnvF(xo n!
+
0h))hn, "
so that n n Hitolly F(x0 + Oh)h I M I r = % o ) < ^i \\D HU-FOro 0ft)ft n\\||yy •.
0
Two remarks are in order. First, if F : G -* Y has continuous nthorder Frechet derivatives, then we have the following Taylor formula with a residual: 1 F{x )h +■■■+ F(x0 + ft) =Fx0 + DF(x0)h+■■+ * ( n - 1)! n 1
Dn-11^*,,)**"-1 F(x0)hn-1 U"-
/ ( l - t ) n - 1 £{l-t) +th)hn
-+T ,^ - T*T T,
n
n
Indeed, by using the following Taylor formula (with a residual, for the function y>(t) = £(F(* 0 +*ft))):
(fc) 1 (B) vM = £ET^ T^lv j k\ (°) + (n - 1)! y0A -*)-V (*)A,
f^k\
(n-l)\J0
and the fact that t € Y* is arbitrary, the conclusion follows immediately. Second, under the above conditions, we have the following estimate: \\F(xo FXQ F(ar0 + ft) - Fx 0 - DF(x0 )h
-r
DnF(x0)hn\\
n! ! II ™ l lly ly {1(1 * (^Ty.Io (^i "-'^[^* ^ H [^*+*> M ** i ** + *> - -J ^™M n n n n < -1, sup \\D | | l ^F(x F (0a H+ , + t f t ) - Dth)-D F ( a ;F(xo)\\-\\h\\ o ) | | - | | f t | &x. n\ o
We next show that when Y = R1, namely, when F is a functional on X, we not only have the Lagrange mean value formula but also have a finite Taylor expansion formula. We first review some useful concepts. Definition 5.5. Let X and Y be Banach spaces, and G C X be an open set on which there defines a functional F. Then the weak differential DF(x0, ft)
Monotone Operator Equations
173
of F at xo G G is also called the variation of F at xo with respect to the increment h £ X, and is denoted by dhF(x0). Also, the derivative DF(XQ) of F at xo G G is also called the gradient of F at xo, and is denoted by gradF(xo). Finally, if every gradient gradF(x) is bounded at x € G, then gradF is an operator mapping from G to the dual space X* of X, and so is called the gradient operator. Theorem 5.4. (The Lagrange Mean Value Formula for Functional) Let X and Y be Banach spaces, and G C X be an open and convex set on which there defines a functional F . If for each x G G, the variation 5/ l F(x) exists, then for any x i , x 2 G G, there is a 0 G (0,1) such that F x 2 - F x i = a ( x 2 _ X l ) F ( x ! + 0(x 2 - x i ) ) . Proof: Let (^(t) = F ( x 1 + t ( x 2 - x 1 ) ) . Then we have
0
Theorem 5.5. (The Finite Taylor Expansion Formula for Functional) Let X and Y be Banach spaces, and G C X be an open and convex set on which there defines a functional F.IfF has nth Frechet derivatives, then for each xo G G and h G X, satisfying xo -f h G G, there is a 0 G (0,1) such that F ( x 0 + h) = F x 0 + DF(x0)h + • • • + , * . ( n - 1J!
Dn-1F{xQ)hn~1
n + ^-D F(x 0 + ^ ) ^ n , n!
where DkF(x0)hk
= DkF(x0)
(fe, • • •, ft) with k variables in ft.
Proof: Let
th)hk.
174
Chapter 5
Consequently, applying the function Taylor formula yields
^1)
=
Erf^ (fc) W
+
^^(n)W'
o<0
so that
F(x0 + h) = Y,l
DkF(x0)hk + - DnF(x0 + 6h)hn .
Q
k=0
5.2 Monotone Operators from a Banach Space to Its Dual Space In this section, we study a special class of operators, the monotone operators, in a Banach space setting. Throughout this section, we let X be a Banach space and X* be its dual space. For any £ e X*, its value at x € X* is denoted as usual by (x, £). 5.2.1 Monotone operators We first introduce the concept of monotone operators. Definition 5.6. Let G C X be an open set and F : G —► X* be an operator. F is called a monotone operator on G if for any xi,X2 € G, (x2 - xuFx2
- Fxt) > 0 .
(5.13)
A monotone operator F is said to be strictly monotone, if the equality in (5.13) holds only when x\ = x%To familiarize the concept of monotone operators, we first show some examples. Example 5.1. Let f(x) be a real-valued non-decreasing function of x G R1. Then / is a monotone operator (monotone function), which is perhaps the simplest example. Example 5.2.
Let F be a linear and positive definite operator satisfying (x,Fx)
> c\\x\\x,
Vx € X ,
for some constant c > 0. Then F is a (linear) monotone operator. As an example, if X = V is a Hilbert space in which there defines a ^-elliptic bilinear form a ( , •), namely, a(v,v)>c\\v\\l,
VveV,
then the induced linear operator F : u € V —► a{u, •) 6 V* is positive definite. This operator was discussed in Chapter 3.
Monotone Operator Equations
175
Example 5.3. Consider the following problem from the study stu of plasticity elasticity twist phenomenon:
!\-IUT,& -£(«?>&)--, K)-*..> -eir"*^ -^rln)Ty < ) ;=»<*■»>• - * \u(x,y)
= 0,
^»'€t
{x,y)edQ,
where SI C R2 is a bounded region, # G L2(ft), <> / is a given function determined by the properties of the material under stress, and
MSD'*®'The corresponding weak form of the problem is to find a u 6 H^{Q) such that a(u v\=
fI f 6(Tu) MTu)
= m,drdu. = jf[ ff[ gvdxdy,
dx7 dx7 Xy
vVv Vn€H£(U). ^«=^Hf^iO)I .
Here, H$(Sl) is the first-order Sobolev space defined in Q with zero bound boundary a n . Note that the left-hand side of the equation actu; actually value conditions on 8Q. defines a nonlinear operator F : H^(Q) -» [H^{Q)]] via t
. _ v
r
(v, Fu) = a{u,v),
+ . _ . -i *
Wv€H^{il),
and the right-hand side is an element Ug 6 [H&(0)]*, ».c, {v, Hg)=
j
I gv dxdy,
Vv €
H£(0).
Hence, the weak form of the problem is equivalent to solving the following operator equation: Fu = = TZg. Ka. Now, we point out that under a certain condition (for instance, when
Chapter 5
176 any Ul,u2 € H^(n) we have ( t X -2 -ui, t i i ,Fu F «2 2-- FFu « i )x) («2
= ^//>TU2)+
[/ao^_-«i) y i
+ -tfTiiO] (T«w22" - T«0 + I\ Ji Ij ^(Tui) hTw2)" ^(Twi)](T Tui)dxdy dxdy
-//J(^)M(^)> >0.
Example 5.4. Consider the gradient operator of the functional defined in a Hilbert space V. For x ^ 0, we have
}{x)-\\x\\v
f(x th)-f{x) ||x _ <X,h) ,. /(x + + th)-/(x) ,. ||g + + tMlv-Hx||^ tfeHy-||xH|r {x,h)vv Vfce V , 1 *™ * " *t-™ ||x||v) £3 t ™, t(||x *(||x + +tfc|| *Mlv l N k~) "||x||v l R i 7' ' v ++
with g r aadd| | x| x| ||v| =v - 7 * r V ,, IFIIV
| | g r a d ( | | x | | vv ) | L |v = l ,
and (
0, x ^# O x X= = 0. 0.
Then for any x l 9 x 2 € V, we have <X x 22--xa ir ,i F, Fxx2 2--FFxx11 > v = ||x2||v + Hxillv - (x <X2,Fxi>v (xi, Fx22)vv 2 ,Fx 1 )v - <xi, > I||x2|k M I v + Hxillv 11*1 Hv -- ||Fxi||v||x ||Fxi||v||x22||v ||v -- ||Fx ||Fx22||v||xi||v ||v||xi||v == 0, 0, showing that F is a monotone operator. We next give some equivalent conditions for monotone operators.
'
Monotone Operator Equations
177
Theorem 5.6. Let G C X be an open convex set, and F : G -+ X* be an operator. Then F is a monotone operator on G if and only if one of the following conditions is satisfied: (i) For any i 6 ( ? and h € X satisfying x -f h G G, the function (fx,h{t) = {h, F(x -f- th)) is nondecreasing as t increases from 0 to 1. (ii) The operator F is locally monotone in the sense that for each x € G there exists a ball of radius 6 > 0 centered at x, denoted U(x,6), such that F is monotone on the set G n C/(x, 6). (iii) Under the condition that F has a derivative on G, (h,DF(x)h)
>0,
VxeG,
VheX.
Proof: Part (i). The necessity follows from the following equality: (t 2 - h) [(pXlh{h) -
-
Fxi)
= (x2 - xu F ( x i + (x 2 - xi)) =
(
fxi7x2—xi (1 j
— (
Fxi)
Pxi,X2— x\ (y) ■
Part (ii). The necessity is obvious. As to the sufficiency, we let #i, x<2 e <2, and then show (x2 — xi, F x 2 — F x i ) > 0. To do so, we only need to show the function ¥?W = (x2 - Xu F(X! + t{x2 ~ Xi))) is nondecreasing as t increases from 0 to 1. By the locally finite covering property [35], we only need to show that for any to € [0,1], the function (fito 4- r ) is nondecreasing in a neighborhood of r = 0. Indeed, by the sufficient condition, there exists a 8 > 0 such that the operator F is monotone in the set G n (/(xo, 6), where xo = x\ + to(x2 — xi). Hence, the function ^(s) = (v - x 0 , F ( x 0 + s(v - x 0 ))) is nondecreasing as s increases from —1 to 1, where 6
V = X0 +
T:
jT- (X 2 ~ X i ) .
||X2 - X i l l x
Chapter I5
178 Since
« - > = ( T i a < « - « ) - F ( - + i i ^ ' * ■ - * ■ >)) = =
8 ( 8s \ — 7 7 ^ ¥» (
f-l^ar that that, t.h* fnnct.ion Vcp(t cn(t, nondecreasintrin theneighborhood it isi clear at the <^(< >(i he function {t0 0n+ +4-rr) r))r^lis isisnondecreasing nondecreasing ininthe tt the neneighborhood \<S/\\x l\\ . \T\<S/\\X \\ . 2 XX -x ^ i l lllx2 XI xPart (iii). an let x € G ) . Necessity. Necessity. Suppose Suppose that that F F is is monotone on on GG, and id fth € X. Thenn for small enough th and andheX. t > > 0, we have i x + tfc eG tteGand and enourfi 0. t f t e i an
xx + F(F(x FF x ^ Q„ ^/ , F Fix ^tlt ) -Fx ++ th)-Fx\
(h^ (h, t {h,
?)>o. ^- ')>o.
Letting etting £ -► -+ -* 00+ (++ gives givesthe the result. result. As Asto tothe the sufficiency, sufficiency, we werecall recall from fro from Theorem Theorem 5.22 (ii) that there is a 09 € (0,1) such that 0h)f), (h, F{x h) - Fx) = (h, F(x + h){h, DF(x + 6h)h), which hich yields the result immediately.
[]
Next, we establish an important result that the gradient o] operator of a convex >nvex lvex functional is a monotone operator. We first recall the cconcept of a convex >nvex lvex functional. Definition efinition finition 5.7. Let G C X be a convex set and J(x) be ia functi. functional denned efined ined on G. J(x) is called a convex functional if for any xxi,X2 x1l; x2 defined € G and v a, b>>>00satisfying satisfying aa+ wehave havethe the inequality inequality a,b>0 ++bb==1,1,we aJ(xi) J(aXl + 6x2). aJ( + bJ{x2) bJ(x2) > J{a Xl) LetGcX Proposition 5.4. Let G C X be an open convex set and J(x) be a functional functionai defined on G.IfJis weakly differentiabJe on G, then either of the following denned conditions is necessary and sufficient for J to be a convex functional: (i) Foranyxux2€G, J(xi) - J(x2) - (xi (x! --x2x,2, gradJ(x 2 )) > 0. (ii) gradJ(x) is monotone on G. » J is convex. Proof: We show that J is convex =* (i) = »* (ii) = ==►
Monotone fonofone Operator Equations
179
J is convex = > (i). Since J is convex, for any xi,X2 G G and t € (0,1], wee have J ( s 2 + t(xx t(gi - x))) ~ J(x2) J(x2) ^ tJ(xx) U(Xl) + (l - t)J(g2) - J(x 2a ) t ~ t = J(xi) - J ( x 2 ) . Letting ->■> 0+ ijerang tz — u-h gives gives (xi (xi -- xx 22 ,, gradJ(x gradJ(x 22 )) )) < < J(xi) J ( x i ) -- JJ (( xx 22 )) .. (i) (i) = => > (ii). (ii). It It follows follows from from (i) (i) that that for for any any xxuuxx222€ €€ G, G, we we have have (xi ( H - x 2 , gradJ(x 2 )) < J(xi) J(X!) - J ( x 2 ) , and
(x ( x2-xi,g™dJ(xi))<J(x , gr ar da Jd( ^x xi2)-J(xi). )O) <^ J (fxo2J) - J (f xo i)).. 22- -xxi ,i g
Adding Adding these these two two inequalities inequalities together together yields yields -(x )-gradJ(xi))<0, -(xo 2d - ( x2-xi,gradJ(x , g.r aeiadJ(xo) J ( x 22 ) - g- r sarda.d7J(f x ,i ^) ) < 00. , 22 --x ixi which implies (ii) > JJ (ii) = = (ii) => > J we define we define
that gardJ(x) is monotone on G. is gradJ(x) is monotone on G, any xi, X2 € G is convex. convex. Since Since G, for for is convex. Since gradJ(x) gradJ(x) is is monotone monotone on on G, for an any xi, X2 € G
p(t) = J(txi + (1 - t)x t)x2)2 ) - tJ(xi) t J(xi) - (1 - t)J(x t) J ( 2x),2 ) ,
t G [0,1].
ihow that
and and
= O. O. yp'(0) ^0) == O.
V J'(0)
Thus, Thus, by the monotonicity of gradJ(x), for t G (0,1] we have .itj.\ J/J.\ Jia\
= 0)x 9)x = (( xx :: -- xx 22 ,, gradJ(te gradJ(te 11 + + (( (( -- t)x^) t)x^) -- gradJ(9x gradJ(9x11 + + (( (( -- 9): 9)x222)) )) t)x 0)x t)x > (0xi Xi + > _^ L__ (txi (txi + + (1 (1 -- t)x t)x222 -- (^ (0xi + (1 (1 -- 0)x 0)x222))) ,, gradJ(txi gradJ(txi + + (1 (1 -- t)x t)x222)) r — cr v - g rraaddJJ(^0f xex i + (( 1 - ^0^)Xx 2a)^) > ^0.
Chapter 5
180
This implies that tp(t) is nondecreasing on [0,1], which contradicts the fact that (p(0) > 0 and
VxGG,
then FXQ = yo. Proof: It suffices to show that (h, F x o - y o ) = 0 ,
V
heX.
For this purpose, we observe that by the given condition for any h € X we have (th, F(xo + t/i) — yo) > 0, for small enough \t\. Hence, it follows that (th, Fx0 - yo) = (th, Fx0 - F(x0 + th)) + (th, F(x0 + th) - y0) > (th, F x 0 - F(x0 4- t h ) ) . Then, dividing both sides by t ^ 0 gives (h, Fxo-yo)
> -(fc, F ( x 0 - f th) - F x 0 ) ,
t >0,
(h, F x o - y o ) < -(fe, F ( x o - h t h ) - F x o ) ,
t <0,
so that, by letting t —► 0 and using the hemicontinuity of F , (h, F x o - y o ) = 0 ,
\fheX.
0
We recall from Subsection 5.1.1 that the demicontinuity implies both the hemicontinuity and the local boundedness. We now show that for monotone operators, both the hemicontinuity and the local boundedness together imply the demicontinuity in a reflexive Banach space setting.
Monotone Operator Equations
181
Proposition 5.5. Let X be a reflexive Banach space and G C X be an open subset. Then a monotone operator F : G —* X * is demicontinuous if and only if F is both hemicontinuous and locally bounded on G. Proof: According to Propositions 5.1 and 5.2, we only need to verify the sufficiency. For any xo € G and {XJ} C G satisfying Xj —> xo (j -+ oo), the local boundedness of F implies that {FXJ} is bounded in X*. Since X is reflexive, there exists a weak*-convergent subsequence {Fxnj} with a weak*-limit y € X*. In the following inequality (x - xn., Fx - Fxnj)
> 0,
WxeG,
j = 1,2, • • • ,
letting j —► oo gives (x — XQ , Fx — yo)>0,
V x € G.
By Theorem 5.7, we have yo = FXQ] that is, any weak* convergent subse quence of {FXJ} converges to the same limit FXQ. Hence, lim (h,Fxj)
= (h,Fx0),
VheX.
0
j—*oo
We next point out that for an operator defined on an open set, monotonicity implies local boundedness, so that the above proposition implies the equivalence of the hemi- and demi-continuities. To show this, we first need the following lemma. Lemma 5.1. Let X be a Banach space, with {XJ} C X and {yj} C X*, such that XJ-^XQ
and
\\yj\\x* -» oo
(j -> oo).
Then, for any r > 0, there exist an x e X, satisfying \\x\\x < r, and a subsequence {ynj} in X*, such that (xnj - xo - x, yn.) —► - o o
(j -> oo).
(5.14)
Proof: Suppose it is not true. Then there exists an ro > 0 such that for every x € S = {x\x G I , \\%\\X < ^o} there is a constant c(x) that satisfies (XJ -XQ-X,
yj) > c(x),
j = 1, 2, • • • .
(5.15)
Chapter 5
182 For each integer k > 1, set Sk = { x | x € S, (XJ - x0 - x, yj) > -k,
j = 1,2, • • • } .
It is clear that Sk is a closed set and, by (5.15), S = U^=1Sk- Since S is itself complete in metric, it follows from the Baire property of a Banach space [40] (see Appendix A.3.2) that there exists an Sko which contains a closed ball U(x,8) of radius 8 > 0 centered at some x € X, with \\x\\x < ro and 0 < 6 < r0 - \\x\\x, s u c n t h a t Inequality (5.15) implies (2(XJ - x0) + x - x , yj) > -k0
+
c(-x),
VxeU(x,6),
j = l,2,- •,
that is, (2{XJ - x 0 ) + x , %■) > -fc 0 + c ( - x ) ,
V \\x\\x <6,
j = 1,2, ••• .
From this inequality and the fact Xj —> x 0 (j —► oc), it follows that for large enough j , (*,%) > -k0 + c(-x),
\\x\\x < g •
Replacing x by - x , we also have ( x , % ) < A:0 - c ( - x ) ,
||x||x < - .
Thus, by combining these two inequalities, we obtain I (x,Vj) | < | - k0 + c ( - x ) I,
||x||x < - ,
j »
1,
which implies that
11%-llx* <
2| - /c0 + c ( - x ) |
jr-^
,
3» 1 •
This contradicts the assumption that ||s/j||x* —► oo as j —> oc. Proposition 5.6. Let X be a Banach space and G C X be an open set. If F : G —» X* is a monotone operator, then F is locally bounded inside G. Proof: Suppose not. Then there exist an x 0 € G and a sequence {x^} C G such that Xj->
x()
and
\\FXJ\\X*->
oo
(j — ► oo).
[]
Monotone Operator Equations
183
It then follows from Lemma 5.1 that there exist an x € X and a subsequence {xn.} such that x0 + x € G and (xn. - x 0 - x, Fxnj)
—> - o o
(j —► oo).
Since F is monotone, we have (xn. - x 0 - x, Fxnj)
> (xn. - x 0 - x, F(x 0 + x)) .
Letting j —^ oo in the above yields a contradiction: (x, F ( x 0 -fx)) > + o o . Hence, F must be locally bounded on X.
[]
Finally, by combining Propositions 5.5 and 5.6, we arrive at the following conclusion. Proposition 5.7. Let X be a reflexive Banach space and G C X be an open set. Let F : G —> X* be a monotone operator on G. Then F is demicontinuous on G if and only if F is hemicontinuous on G. 5.2.3 Strongly monotone operators Again, we let X be a Banach space and G C X be an open set. Recall from (5.13) that a monotone operator F : G —► X* is strictly monotone on X if (x 2 - xuFx2
- Fxi) > 0,
Vx1,x2€G,
x1 ^ x2 .
Obviously, a strictly monotone operator on X must be one-to-one. However, the operator equation
Fu = f,
feX\
need not have a solution u € G for any / € X*, even if F is a strictly monotone operator. In order to guarantee that for every / € X* the above operator equation has a unique solution, and to ensure the strong solvability of projective approximation schemes, we have to impose stronger monotonicity condition on the operator F (see, for example, [25, 38, 41]). Definition 5.8. An operator F : G —► X* is called a strongly monotone operator on G if for any x\,x a ( | | x 2 - x i | | x ) ,
Chapter 5
184
where a(t) : [0,oo) -> [0,oo) is a strictly monotonically increasing function satisfying o(0) = 0. For a strongly monotone operator defined on the entire space X, we have the following equivalence conditions [42]. Theorem 5.8. For an operator F : X -+ X*, the following conditions are equivalent: (i) F : X -> X* is a strongly monotone operator. (ii) There exists a strictly increasing function r(«) : [0, oo) -» [0, oo) satisfying r(0) = 0 and r{t) - * < » ( « - ♦ oo), such that for all xux2e X, (x2 - xi, X!, Fx2 -- Fxi) FXl) > ||X2 ||x2 - xxxlU i | U • r(||x 2 - *xii|l| U x ))•. (iii) There exists a function v(t) : (0, oo) -+ (0, oo) such that with xx±x2,
forallxux2eX
( x 22 - x 11 , F x 22 - F x 11 ) > ^ ( | | x 22 - x i1 l| U ) . Proof: The implications (ii) =*■ (i) =*> (iii) are obvious. Hence, it suffices to verify the implication (iii) = » (ii). For this purpose, let r(t)=
inf
-- (x2 - Xlxi,, Fx22 - FFx Xlx),),
te(0,oo).
It follows from Condition (iii) that r(t) > 0 for every t > 0. We will show that r(h V tuut2t2 € (0, oo). (5.16) r(t1+t+1 (0,oo). 2) > 2)>r(t 1) r(h) + r(t2), Indeed, for any xux2eX
with ||x 2 -x1\\x=h+12,
we have
—!—(x2-x1,Fx2-Fx1)
'H^k^-^-F''-F{-^kn+rrh^)) +
hXirh^-^F(^h^irh-)-F^
> r ( *t i ) ++r (r(< * 2 2)),, which is (5.16). On the other hand, (5.16) shows that r(t) is strictly increas ing. Finally, repeatedly applying (5.16) yields r(«)>r([t])>[«]r(l) r(t)>r([t})> [*]r(l) — ooo, o,
(t -► oo), (t
where [t] is the largest integer that is less than or equal to the real number * € (0,oo). By defining r(0) = 0 and using the definition of r{t), we obtain («)• []
Monotone Operator Equations
185
5.3 Approximate Solvability of Monotone Operator Equations We are now ready to discuss the monotone operator equations: their unique solvability and protective approximate solutions. 5.3.1 Monotone operator equations In this subsection, we let X be a reflexive and separable Banach space and A : X —► X* be an operator. Consider the following equation: Au = f,
f€X*.
(5.17)
We first establish an important result on the existence of a solution to this operator equation in the finite-dimensional case. Proposition 5.8. Let G c f f 1 b e a nonempty bounded open set with 0 € G, and F : G —» FT1 be a continuous operator. If
(x,Fx)>0,
VxedG,
then the homogeneous operator equation Fu = 0 has at least one solution on G. Proof: Suppose the opposite, namely, Fx ^ 0,
V x e G.
Let Ftx = (1 - t)x + tFx, 0 < t < 1. Then Fox = x^0,
FiX = F x ^ 0 ,
WxedG,
and
(x,Ftx)
=
(l-t)\\x\fx+t(x,Fx)
>(l-*)||x||x,
V*€(0,1),
Vx€#G.
Consequently, we have Ftx^Q,
Vt€[0,l],
xedG.
Thus, it follows from the continuous homotopic invariance of topological de grees that deg(F, G, 0) = deg(F 0 , G, 0) = 1.
186
Chapter 5
According to the Kronecker Principle (Theorem 4.4, Part (i)), we know that Fu = 0 has a solution in G, which contradicts the assumption. \\ Now, observe that X is separable, and so we can choose a sequence of finite-dimensional subspaces of X, { X n } , with Xn C X n +i and X = U^=1Xn. Consider the discretized problem: Find a un € Xn such that (v1Aun)
= (vJ),
V^eXn,
n=l,2,.-..
(5.18)
As usual, let Pn : X —► Xn be a bounded linear projection, and P* : X* —► X* be its dual operator. Then, we have a projective approximation scheme r n = {X n , Pn}, and so obtain a sequence of approximate equations of (5.17) as follows: Anun=P^f, (5.19) where the operator An = ^ n ^ l x • Clearly, no matter how Pn is defined, Equation (5.19) is always equivalent to Equation (5.18). Hence, we will only discuss Equation (5.18) in the following, where as usual we will denote the approximation scheme by Tn = {Xn}. We have not yet specified the operator A in Equations (5.17) and (5.18). We now introduce a new concept of coercive operators. Definition 5.9. An operator A : X —► X* is said to be coercive with respect to / € X*, if there is a constant r > 0 such that (x,Ax-/)>0,
VXGX
with
||x||x=r.
(5.20)
Then, we have the following important result. Theorem 5.9. Let X be a separable reflexive Banach space and A : X —► X* be a hemicontinuous monotone operator. Suppose that A is coercive with re spect to an f e X*, and {Xn} is a sequence of finite-dimensional subspaces in X , satisfying Xn C X n + i and U ^ 1 X n = X. Then Equation (5.17) is weakly approximate-solvable with respect to the approximation scheme Tn — {Xn}, in the sense that for each n= 1,2, • • •, the approximate Equation (5.18) has a solution un e Xn, the sequence {un} has a weakly convergent subsequence, and each of such subsequence converges to the solution of Equation (5.17). Proof: Without loss of generality, let / = 0, dimX n = n, and Xn = span{wi, • • •, Wn}- We first show that there exists a « n G X n , with ||w n ||x < r, such that (wj,Aun)=0, j = l,...,n. (5.21)
Monotone Operator Equations
187
For this purpose, let U n = / ^
'3^3 >
5= 1
and =
C = [ci,---,Cn]
,
I '
X^^'^l
ll i = 1
llx
f-
)
Then consider the operator : G —► i? n defined by
$(c)=[$ 1 (c),... ; $ n (c)] T : where A
(^c3w3jy
W,
*<(c) =
i = 1, • • • , n .
It follows from the given conditions and Proposition 5.7 that 3>: G —* i?71 is a continuous operator, satisfying
(c, ^ ( C ) ) = ( £ C ^ ^ ( E C ^ ) ) ^°>
VcedG.
It then follows from Proposition 5.8 that there exists a c G G such that $(c) = 0 , which is (5.21). Observe, moreover, that {un} is a bounded sequence in a reflexive Banach space, it has a subsequence {unj} such that unj
w
->u0eX,
(j->oo).
Thus, for any v € Xk, we have (v - it n , , Av) = (v - unj , At; - Aun.) + (v - wn, , A u n i ) . When n, > A:, v - w ni € X nj ., so that (v - unj, Aun.) = 0. Hence, (v - unj , Av) > 0,
V v e Xk ,
n3>k.
Letting j —► oo gives (v — wo , Av) > 0,
V t; G Xk .
Chapter 5
188
Observe that \J™=1Xn = X, and that the hemi- and demi-continuities are equivalent for a monotone operator. Hence, we actually have (v —
UQ
, Av) > 0,
V v G X.
Thus, it follows from Theorem 5.7 that Auo = 0.
[]
We remark that if A is strictly monotone, then Equation (5.17) is weakly and uniquely approximate-solvable with respect to T n , namely, the approx imate Equation (5.18) has a unique solution un, with un w-> uo as n —» oo, where UQ is the unique solution of Equation (5.17). Corollary 5.2. If the coerciveness condition stated in Theorem 5.9 is re placed by the following general coerciveness condition: lim ^ l = o o , IMIx-oo \\x\\x
(5.22)
then for any f € X*, the conclusion of Theorem 5.9 holds. Moreover, we have the following result. Theorem 5.10. Let X be a reflexive and separable Banach space, and A : X —* X* be a hemicontinuous and strongly monotone operator. Suppose that {Xn} satisfies Xn C Xn+1 and U^Xn = X. Then for any f e X*, Equation (5.17) is uniquely and strongly approximate-solvable with respect to the scheme Tn — { X n } , that is, Equation (5.18) has a unique solution un, satisfying un —► uo as n —» oo, where u$ is the unique solution of Equation (5.17). Proof: The equivalent Condition (ii) of Theorem 5.8 on the strong mono tonicity can be applied to show that the strong monotonicity condition of this theorem implies the general coerciveness condition (5.22). Hence, for any / € X*, Equation (5.17) is weakly and uniquely approximate-solvable with respect to the scheme Tn. What is left is to show that un —► u§ as n —► oo. To do so, we first observe that since {Xn} satisfies Xn C X n + i and is ultimately dense in X, which implies that there exists a Vj € Xj for each j = 1,2, • •, such that *>j -► uo ,
(j ~>
oo).
It then follows from the strong monotonicity of A and Equation (5.18) that when n > j , <x(\\un - Vj\\x) < (un - Vj , Aun - AVJ) = (un -Vj,
f - AVJ) .
Monotone Operator Equations
189
Thus, since un ™—» uo (n —■> oo) and Vj -* no (j -+ oo), it follows from the demicontinuity of operator A that lim j—too
lim
(un —Vj,f
— AvA = 0,
n-+oo
so that lim
lim a( \\un - vA\x) = 0.
j—>-oo n—>-oo
Consequently, for any e > 0, there is a jo > 0 such that lnh~ a(\\un
- vjo\\x)
< a(e/2),
\\vjo-uQ\\
< e/2.
n—>-oo
It then follows that there is an N(> jo) such that oc(\\un -vjo\\x)
< <*(e/2),
n>N.
By the strict increasing property of a(t), we have
IK-^olU <^/2,
n> N.
Hence, when n > N, we have I K - u o | | x < \\v>n - vjo\\x + \\vjo -u0\\x
<e,
which proves un —»> UQ as n —► oo, as expected.
[]
We remark that if Theorem 5.10 applies to linear operators, since a linear operator is always hemicontinuous, we do not need any continuity condition imposed on the operator. Hence, the following conclusion can be drawn. Corollary 5.3. Under the conditions of Theorem 5.10 on the spaces X and {X n }, if A : X —► X* is a positive definite linear operator, then for any f £ X* Equation (5.17) is uniquely and strongly approximate-solvable with respect to the scheme Tn. We should remark that this result improves some results that we ob tained in Chapter 3. More importantly, here we no longer require the uniform boundedness condition for the sequence of projection operators that are used in a general projective approximation scheme: | | P n | | < c for all n = 1,2, • •. As a matter of fact, the Lax-Milgram Theorem (Corollary 3.1) can be considered as a special case of Theorem 5.10 when the operator is linear, and its conditions can be formally weakened. More precisely, we have the following [7].
Chapter 5
190
Corollary 5.4. (Modified Lax-Milgram Theorem) Let V bea separable Hilbert space and o(-, •) bea bilinear functional defined on V x V. Suppose that for every u eV, a(u, v) is a continuous functional ofveV and that a(-, •) is positive definite: a(v,v) > a | M & ,
VveV,
for some constant a > 0. Then for any f € V*, equation a(ti,v) = ( t ; , / ) ,
V v € V\
is uniquely solvable. Proof: It amounts to note that in this case the equation under consideration is equivalent to Au = / , where A is the operator induced by a(-, •), namely, (y, Au) = a{u, v),
V v € V.
Hence, the unique and strong approximate-solvability implies the unique solv ability. [] It should be pointed out that if we only consider the existence of a solu tion but not the approximate solvability of the equation, then the separability of the space is not needed. This can be verified by introducing the so-called finite intersection property and using the compactness theory of a topological space [5]. Note that Theorem 5.10 only points out that the hemi- or demi-continuity is a sufficient condition for the unique and strong approximate-solvability of a strongly monotone operator equation. We next point out that this condition is also necessary. Proposition 5.9. Let X be a reflexive Banach space and A : X —► X* be a strongly monotone operator. If Equation (5.17) is uniquely solvable for any f € X*, then A must be demicontinuous. Proof: Axn
w
Let {xn}
C X such that xn —> x0 as n —► oo. We show that
—+ AXQ as n —> oo.
Since A is monotone, it is locally bounded. Hence, {Axn} is bounded, so that there is a weakly convergent subsequence Axn. w-+ y e X* as j —► oo. According to the assumption of unique solvability of Equation (5.17), there exists an x e X such that Ax = y. Since A is strongly monotone, we have a
( Ikn,- - x\\x)
< (xn. - x, Axn. -
Ax).
Monotone Operator Equations
191
Letting j —> oo yields lim a ( | | x n - -x\\x)
=0.
Furthermore, since a(t) is strictly increasing and a(0) = 0, we have xn. —► x, so x = xo and Axnj. ™—► Axo as j —► oo. This has also verified that every weakly convergent subsequence of {Ax n } converges weakly to AXQ, namely, {Ar n } weakly converges to Axo, which implies that A is demicontinuous. [] We next derive some error bounds, under some conditions on the oper ator A, for the approximate solutions discussed above. Theorem 5.11. Suppose that under the conditions of Theorem 5.10, u and un are solutions of Equations (5.17) and (5.18), respectively. (i) If operator A is bounded, then there exists a constant c > 0 such that r(\\un-u\\x)-\\un-u\\x
inf vexn
{\\u-v\\x},
(5.23)
where r(t) is the function defined in Theorem 5.8, Part (ii), satisfying the strong monotonicity equivalent condition stated therein. If r(t) = r0t for some constant ro > 0, then \\un-u\\x<^/^
{\\u-v\\%2}.
inf UtA
(5.24)
n
(ii) If operator A is Lipschitz continuous, namely, for any given M > 0 there exists a constant CM > 0 such that \\Ax1 - Ax2\\x* < CM • Iki - x2\\x ,
V x l 7 x 2 e X , ||*i||x, \\x2\\x<M, then there is a constant c > 0 such that r(|K-«|U)
inf
{\\u-v\\x}.
(5.25)
Ifr(t) = rot for some constant ro > 0, then
IK-«IU<-
inf {||«-t;||x}.
ro vexn
(5-26)
Chapter 5
192
Proof: Part (i). Since A is strongly monotone, for any v e Xn: we have r(\\un -u\\x)
-|K
-u\\x
< (un - u, Aun - Au) = (y — u, Aun — Au) <\\Aun-Au\\x.\\u-v\\x.
(5.27)
Since {un} is a bounded sequence a n d A is a bounded operator, respectively, there exists a constant c > 0 such t h a t \\Aun — Au\\x* < c. Hence, t h e error estimate (5.23) holds. P a r t (ii). T h e given conditions a n d t h e result (5.27) established above together yields the error estimate (5.25) immediately. []
5.3.2 The perturbation problem In this subsection, we consider the perturbed operator equation Au + Bu = f,
(5.28)
where A : X —► X* is a monotone operator and B : X —► X* is assumed to be completely continuous. Let {Xn} satisfy Xn C X n + i and be ultimately dense in X. Denote by Fn = {Xn} the corresponding approximate scheme as usual, and then consider the approximate equations (v.Atin + Bun) = ( « , / ) ,
VveXn,
u = 1,2, • • • .
(5.29)
We have the following result. Theorem 5.12. Let X be a reflexive and separable Banach space and A : X —* X* be a hemicontinuous monotone operator and B : X —> X* be a completely continuous operator. If for the given f € X* operator A-\- B is coercive, then Equation (5.28) is weakly approximate-solvable with respect to the scheme Tn. Proof: Without loss of generality, let / = 0. Since A + B is demicontinuous and coercive, similar to the proof of Theorem 5.9 we can show that the approximate Equations (5.29) have solutions un € Xn, with ||w n ||x < r f° r some constant r > 0 for all n = 1,2, • • •. It then follows that there exist a subsequence {unj} and a UQ G X such that uUj
w
-> u0,
(j -* oo).
Monotone Operator Equations
193
Thus, for any v € Xk, when nj > k we have (v -unj,
Av +
Bunj)
= (v - unj, Av - Aunj) > (v-
unj, Aun. + Bunj)
+ (v- un., Aunj +
Bun.)
= 0.
Since B is completely continuous, letting j —► oo leads to (v - w0 , Av + Buo) > 0,
Vt/elfc.
Since {X n } is ultimately dense in X and A is demicontinuous, the above in equality holds for all v € X. Hence, according to Theorem 5.7, AUQ + BUO =
o.
D
In the above, we have seen that when a monotone operator has a com pletely continuous perturbation, if the operator after perturbation is still co ercive, then the approximate solvability of the equation remains unchanged before and after the perturbation. In the following, we examine the case where the operator is strongly monotone. Theorem 5.13. Let X be a reflexive and separable Banach space, A : X —» X* be a hemicontinuous and strongly monotone operator, and B : X —► X* be a completely continuous operator. Let {Xn} satisfy Xn C Xn+\ and be ultimately dense in X, with the approximation scheme denoted by Tn = {Xn}. Suppose that for the given f € X* the operator A-\- B is coercive. Then Equation (5.28) is strongly approximate-solvable with respect to the scheme Fn. Proof: Based on Theorem 5.12, we will furthermore prove that unj —► u$ as j —> oo. To do so, observe that {Xn} satisfies Xn C X n + i and is ultimately dense in X, and so there are uk € Xk, k = 1,2, • • •, such that w^ -> u 0 as k —» oo. For any k > 1, when nj > k we have, by the strong monotonicity of A, the following: a
(
ll^n,- - &k\\x)
< {unj
- Uk , Aun.
= (unj -uk,
-
Auk)
f - Auk - Bunj) .
It then follows from the complete continuity of B and the demicontinuity of A that lim lim (un - uk, f - Auk - Bun) = 0, so that lim k-+oo
lim a ( \\un - uk\\x) j—K>O
= 0.
Chapter 5
194
Similar to the proof of Theorem 5.10, we can finally verify that unj —► u 0 as j —> oo. [] 5.3.3 Some remarks on the complex Banach space s e t t i n g When X is a complex Banach space, we can slightly modify the definitions of monotonicity and coerciveness. Definition 5.10. Let X be a complex Banach space and G C X be an open set. An operator F : G —> X* is called a monotone operator on G if for any Xi,X2 E G,
Re (x2 - xi, Fx2 — Fx\) > 0 , where Re(-) is the real part of a complex function (or number). A monotone operator F is said to be strictly monotone, if the above equality holds only when #i = X2. Moreover, F is called a strongly monotone operator on G if for any x\,x a( ||x 2 - x i | | x ) , where a(t) : [0, oo) —► [0, oo) is a strictly monotonically increasing function satisfying a(0) = 0. Definition 5.11. Let X be a complex Banach space. An operator A : X —> X* is said to be coercive with respect to / G X*, if there is a constant r > 0 such that |(x,
A E - / ) | ^ 0 ,
VXGX
with
||x||x=r.
Moreover, A is said to be general coercive, if hm IMIx-oo
,, ,, ||x||x
= oo.
Under these modifications, all results given in Theorems 5.9-5.13 as well as their corollaries still hold true. To verify this, it amounts to modifying their proofs accordingly, by taking into account the following remarks. 1. To prove the corresponding Theorem 5.7, it suffices to replace the lefthand side of the given condition (inequality) by its real part, and then to use it to replace t in the proof, where i = \/-T> since in doing so it follows that the imaginary part of (ft, F x 0 - t/o) equals zero. 2. To prove Proposition 5.7, it suffices to observe that Lemma 5.1 still holds when restricted to the real parts.
Monotone Operator Equations
195
3. To establish the existence of approximate solutions, the following Browder Theorem [3] can be used to replace Proposition 5.8. Theorem 5.14. (The Browder Theorem) Let E be a finite-dimensional Banach space with dimE > 1, and let A : E —> E* be a continuous operator satisfying (x,Ar)^0,
with
VXGE,
||x||£7 = r ,
for some constant r > 0. Then there exists a u G E, with that Au = 0.
\\U\\E
< r, such
5.4 Solvability and Approximate Solutions of K-Monotone Operator Equations In this section, we consider the Hilbert space setting, and study the solvability and approximate solutions of K-monotone operator equations. 5.4.1 K-monotone operator equations Let if be a Hilbert space, with inner product (•, -)H and the induced norm l l l l / / . Let V be another Hilbert space with inner product [•, -] v and induced norm | • \y. For a nonlinear operator A : V(A) C V —> if, where V{A) is a dense set in V, consider the operator equation Au = f,
feH,
(5.30)
and study its approximate solvability problem. We will introduce a bounded linear operator K : V -» H and use it to establish a framework of K-monotone operator equations [10, 12]. We first have the following concept. Definition 5.12. An operator A : V(A) C V —> H is said to be K-monotone if there exist a bounded linear operator K : V —> if, satisfying K(V) = H with respect to the norm || • ||H> such that (Ax2 - Axi, K{x2 -
X1))H
> 0,
V xi, x2 G V(A),
Moreover, operator A is said to be strongly K-monotone if (Ax2 - Axi, K(x2
-XI))H
> <x(\x2-xi\v),
V x i , x 2 G V{A),
for a strictly increasing function a(t) : [0, oo) —► [0, oo) satisfying a(0) = 0. Finally, operator A is said to be K-coercive if hm I*I V ^°° xe-D(A)
| (Ax, ——~
Kx)H\ — = oo . \x\v
Chapter 5
196 Now, let a(u, v) = {Au, a{u, (Au, Kv)H, , f(v) = (f,Kv)H,
uu€G V(A), V{A), vzV.
v€V, v€V,
Clearly, for each u € V{A) and / € H, both a(u, •) and /(•) are continuous linear functional on V. Hence, it follows from the Riesz Representation Theorem that there exist a unique Au € V and a unique Kf €V such that (Au,Kv) {Au,Kv)HH=[Au,v] v,
,
(f,Kv)HB=[Hf,v] =[llf,v]vv,, {f,Kv)
Vv€V, WveV.
Then the following result can be established. Proposition 5.10. Suppose that the operator A introduced above satisfies the following condition: (Hi) For every w € V and every Cauchy sequence {vn} in V{A) V{A) C V, (Avn-Avm,Kw)H-+>
(n,m->oo).
Then the operator A has a demicontinuous extension, A:V-^V. A : V -> V. Proof: We extend the operator A to the entire space V as follows: If v € V{A) then let Av = Av. If v € V\V(A), since V{A) is dense in V, there is a sequence {vn} C P(i4) such that vn -* / 6 V ss - -♦ o.. Thus, ac cording to Condition {Hi), we know {«4»„} C V is a weak Cauchy sequence. Consequently, there is a v G V such that v = (weak) limn-oo Avn. It is clear that v only depends on » but is independent of the choice of {vn}. Hence, we can let Av = v. The above construction shows that A : V -> V ii s demicontinuous operator. 0 Based on this proposition, we can continuously extend the functional a(-, •) to a two-variable functional denned on V x V by a(u,v)=
[Au,v]yv,
u,veV. u,veV.
This continuous extension is obviously unique. Next, we introduce the concept of generalized solution for Equation (5.30) as follows: A u G V is said to be a generalized solution of Equation (5.30) if a{u,v) f(v), VveV, a(u,v) = f(v), \lveV, (5.31)
Monotone Operator Equations
197
namely, [Au,v]v
= [nf,v]v,
VveV,
(5.31')
or equivalently, Au = Kf,
feH.
(5.31")
To find approximate solutions for the above equations, we choose a se quence of finite-dimensional subspaces Vn C V such that Vn C F n + i
and
U~ =1 Vn = V ,
and use the approximate scheme Tn = {Vn}. Under this framework, the approximation problem is to find un G Vn such that a(un,v) = f{v),
VveVn,
(5.32)
namely, [.Atin , v]y = [Kf, v]v yveVn.
(5.320
If we choose Vn C T)(A), then the approximate equation is (Aun ,Kv)H=(f,Kv)H,
VveVn,
(5.32")
where n = 1,2, • • •. We have the following result. Theorem 5.15. Suppose that operator A satisfies Condition (Hi). (i) If operator A is K-monotone and K-coercive, then for any f G H Equa tion (5.30) is (in a generalized sense) weakly approximate-solvable under the scheme Tn, namely, the approximate Equation (5.32) has a solution u>n £ Vn f°r eacn n — 1>2,---, and the sequence {un} has a weakly convergent subsequence, and the limit of any such weakly convergent subsequence is the generalized solution of Equation (5.30). (ii) If operator A is strongly K-monotone, then for any f G H Equation (5.30) is (in a generalized sense) uniquely and strongly approximatesolvable under the scheme Fn, namely, the approximate Equation (5.32) has a unique solution un G Vn for each n — 1, 2, • • •, and the sequence {un} is strongly convergent to the unique generalized solution of Equa tion (5.30).
Proof: According to Proposition 5.10, the extension A of the operator A is a demicontinuous operator from V to V. If A is if-monotone and_/f-coercive, then by going through a limiting process it can be verified that A : V —» V is
Chapter 5
198
monotone and coercive, since V(A) is dense in V and A is demicontinuous. Thus, we have [x2 - X\ , AX2 ~ Axi] and hm |x| v ->oo
> 0,
V Xi, X2 € V ,
_ [ar,Ac] v . . = oo. p|v
Here, the Riesz Representation Theorem enables us to identify V* with V. To this end, Theorem 5.9 and its corollary together imply that Equation (5.30) is (in a generalized sense) weakly approximate-solvable. If A is strongly Kmonotone, then similarly by going through a limiting process we can verify that A : V —> V is strongly monotone: [x2 - x
u
Ax2 - Axi]v
> a(\x2 - x i | v ) ,
Vxi,rc2 € V , x± ^ rc2 ,
where a ( t ) = l i m 3 ^ t a ( g ) is a strictly increasing function from (0, oo) t o (0, oo). It then follows from Theorem 5.10 t h a t Equation (5.30) is (in a gen eralized sense) uniquely a n d strongly approximate-solvable. [] In t h e case t h a t Equation (5.30) is (in a generalized sense) uniquely a n d strongly approximate-solvable, we can estimate t h e error bound of t h e ap proximate solution un as compared t o t h e generalized solution u of Equation (5.30). For this purpose, we need a n additional condition: (H2) For each M > 0, there exists a constant CM > 0 such t h a t | (/ - Ax\, K{x2 -x\))H\
< cM \u - x i | v | x 2 -xi\v
Vxux2eVnr)T)(A),
| x i | v , |x 2 | v
, M
< -
Proposition 5.11. Suppose that A : T>(A) C V —► H is in the following form strongly K-monotone: (Ax2 - Axx, K{x2 -
Xl))H
> a0\x2 - xx\2v ,
V xu x2 e V(A),
(5.33)
for some constant ao > 0. Suppose also that Conditions (Hi) and (H2) are satisfied. Then we have the following error bound: \un-u\v
< f l + — } inf
|ti-t;L.
(5.34)
Monotone Operator Equations
199
Proof: Since V(A) is dense in V and A is demicontinuous, by Conditions (5.33) and (H2) we have [x2 - xi,
Ax2 - Ax\\
> &o\x2 - xi\2v ,
Vxi,x2€V,
(5.35)
and \[x2 -xi,
nf -Axi]v\
< cM\u-xi\v\x2
Vxi,x2GVn,
\xx\v,
-xi\v
,
\x2\v <M.
(5.36)
Consequently, we have a o M v < [un,
Aun-A0]v
= (Xun, / ~ A 0 ) H <||/-^0||-||^||-|un|v. Hence, by letting M 0 = -^ \\f - A0\\ • ||K||, we arrive at \un\v < M0 and |it| v < M 0 . Furthermore, if we set M = 2MQ1 then iox v ^Vn with |v| v > M, we have \u - v\v > \v\v - \u\v > M0> |u| v . Hence, inf
\u-v\v=
inf
\u-v\v.
(5.37)
|V|V<M
Thus, for v eVn with |v| v < M, it follows from (5.35) and (5.36) that \un - v\2 < — [un-v, ao
Aun
-Av]
v
=
[Un ~ V , Hf - Av ] v a0 < — \u-v\v\un -v\v ,
so that \un - u\v < \un - v\v -f \v - u\v <(l
+ ^)-\u-v\v,
VveVn,
\v\v
<M.
This, together with (5.37), imply (5.34).
[]
It should be noted that in many applications, we have the following stronger but more easily verified condition: (Hi2) For any M > 0, there exists a constant CM > 0 such that | (Ax2 - A c i , Ky)H\ \/Xl,x2eV(A),
V y e V,
- Xi\v\y\v
,
| x i | v 1 | x 2 | v , \y\v
<M.
200
Chapter 5
Proposition 5.12. Suppose that operator A has the strong monotonicity as shown in (5.33), and assume that Condition (H12) is satisfied. Then Equation (5.30) is (in a generalized sense) uniquely and strongly approximate-solvable under the scheme Tn, with the error hound given by (5.34). Proof: It suffices to show that Condition (#12) implies both Conditions (Hi) and (H2). First, it is obvious that (#12) implies (Hi). Second, (#12) implies that I [Ax2 -Aci,y]v\
< CM \%2 - xi\v\y\v
V x i , x 2 , 2 / € V\
\xi\v,
i
\x2\v, \y\v < M.
In the above, replace x2 by w, and let y — x2 — xi. Then for large enough M > 0, we obtain I (f -Axi,
K(x2
= I [x2 - x i , An< CM
\U-Xi\v\x2
-xi))H\ Axi]v\ -Xi\v
,
V xux2eV(A),
\xi\v, \x2\v < M,
which gives (H2).
\\
5.4.2 The perturbation problem We now discuss the perturbation problem of the if-monotone operator equa tion: Au + Bu = f, / € H, (5.38) where A : V(A) C V -* H is K-monotone and B : P ( B ) c V -+ H is a nonlinear perturbation operator, with V(A) C T>(B). Let 6(i*, v) = (J5w, Kv)H, ue V(B), v eV. Then by the Riesz Representation Theorem, for each u e T>(B) there exists a unique Bu eV such that (Bu,Kv)H
= [Bu,v]v,
ueV(B),
veV.
We next extend the operator B to the entire space V. For this purpose, we impose the following condition: (Hs) : For any weak Cauchy sequence {vn} C T>(B) C V, we have {Bvn - Bvm , Kw )H —► 0
(n,m -+ 00)
Monotone Operator Equations
201
uniformly with respect to w € {v \ v e V , \v\v = 1}. Then we have the following result. Proposition 5.13. Suppose that Condition (H%) is satisGed. Then operator B has a completely continuous extension, B, from V to V. Proof: For each v G V(B) = V, there is a sequence {vn} C V(B) such that vn w~* v i n F a s n - ^ o o . It then follows from Condition (H$) that I Bvn - Bvm I =
sup I [Bvn - Bvm , w] \ Wv=i = sup I (Bvn — Bvm , Kv)HI —> 0
(n, ra —± 00).
This implies that operator B maps a weak Cauchy sequence {vn} C V(B) to a strong Cauchy sequence {Bvn} C V. Therefore, there exists a unique v eV such that £ = (strong) lim n _,oo^?; n . Obviously, this v depends only on v but is independent of the choice of {vn}. Hence, we can let Bv = v. It is clear from the construction that B is the extension of B, which maps a weakly convergent sequence of V to a strongly convergent sequence, and so is completely continuous. \\ Thus, we have uniquely and continuously extended 6(w, v) to a twovariable functional b(u,v) — [Bu,v]v defined on V x V. Under the Conditions (Hi) and (H2), the perturbation problem (5.38) has a generalized solution given by a u € V satisfying a(u, v) + 6(u, v) = f(v),
Vv e V ,
(5.39)
VveV,
(5.39')
namely, [Au + Bu,v]v=
[Hf,v]v,
or equivalently, Au + Bu = Kf,
feH.
(5.39")
Clearly, its approximation problem is to find un 6 Vn such that a(unyv) + 6(t*n,t;) = f(v),
V.€^n,
(5.40)
which, in the case that Vn C T>(A), becomes (Aun + Bun , ^ ) ^ = (/, Kv)H ,
V t; € Vn ,
(5.40')
Chapter 5 5
202
wheren = 1,2,--• Based on the above discussions, combining Theorems 5.12 and 5.13 yields immediately the following result. Theorem 5.16. Suppose that Conditions (Hi) and (H%) are satisfied. Then (i) If A is K-monoton,, and if A + B is K-coercive, then for any f € H the perturbation problem (5.38) is (in a generalized sense) weakly approximate-solvable. (ii) If A is strongly K-monoton,, and ifA + B is K-coercive, then for any f G H the perturbation problem (5.38) is (in a generalized sense) strongly approximate-solvable. Finally in this section, we remark that when K = I, the identity operator, the above framework reduces to a general problem of finding approximate solutions for a densely defined monotone operator equation and its perturbed equation. In this case, the continuity assumption on operator K is the continuous embedding requirement for K : V -> H. 5.5 Application Examples: Numerical Solutions of Boundary Value Problems In this section, we give some examples to show how monotone and Kmonotone operator equations, as well as their perturbations, can be applied to approximate numerical solutions of nonlinear differential equations. Example 5.5. (The homogeneous Dirichlet problem) Let Q be a region in B? with boundary dtl, and let / € Lq(Q) with p~l + q-1 = I where p > 2. Consider the following boundary value problem:
= /(*). Iu = = 0, [u 0,
x € Q,
x ex€dQ, on,
where V is the gradient operator and || • || is the Euclidean norm. We are looking for a weak solution of the problem. Notice that the corresponding variational problem is to find a u € W^P(Q.) such that 2 \\Vu\r^udVvdx fvdx, I[ \\Vu\r VudVvdx = [[ fvdx,
Jn Jn
Jn Jn
p
V v£W>), Vv€WZ*(tt),
°
;
(5.41)
V
;
where W0' (Q) is the homogeneous Sobolev space, a subspace of the standard Sobolev space W1*^), defined by W1*^)
= {u6 LP(Q) (fi) || v has generalized derivatives (£l), dv/dii€Lp(Q),
i = l,2}
Monotone Operator Equations
203
and W01,p(fi) = C£°(ft), where the closure is with respect to the norm of
W1'P(Q).
In particular, if p = 2, we actually have Wli2(Q) = H1^) and Wo' 2 (^) = 1,p HQ(Q). As usual, the norm of space W (ft) is defined by
Mo,P,n + Mi, P ,nJ
>
where lvlo,p,n
(/j-H-*) 1 ". 2
'
MI,P,H i=i
P
I
\
I/P
ctei
in which | • |i,p>n is indeed an equivalent norm of the W 0 l j , (n) -norm. In the following, to simplify our computation we will use the following norm:
"-a
\
||Vv|| p dx) n /
i/p
Vv^01,p(fl),
,
in which ||Vv|| is the Euclidean norm of Vv e WQ'P(Q). It is easy to verifythat this || • || is a W^P(Q) -norm and is equivalent to the norm | • |i, p ,n defined above. For any fixed u G W 0 , p (fi), by the Holder inequality we have
/
Jn
\\Vu\\p-2Vu-Vvdx ^WuW^Wvl
Vve
W^P(Q).
This implies that for any u € W0'P(Q), the integral on the left-hand side of (5.41) is a bounded linear functional on space W 0 1,p (n), which defines an operator A : W01,p(fi) -> [W 0 1,P (n)]* via v , ; 4 u ) = / ||Vu|| p - 2 Vu-V7;dx,
V v e ^ f l ) ,
where, as before, (v, Au) stands for the functional value of Au evaluated at v. Observe that the right-hand side of (5.41) is also a bounded linear functional on space W 0 ' p (fi), and can be rewritten as
/ Jn
fvdx = {v,n,
l.p/ V D G ^ f t ) ,
204
Chapter 5
where / * e [Wr01,P(^)]*- T n u s > Equation (5.41) can be reformulated as the following operator equation: An = r • (5-410 Using the identity ab - cd = - (a - c) (b + d) + - (a + c) (6 - d), for any wi, ^2, v €
WQ'^Q)
we have
(v, Aw2 --Awi) (||V^2ir~2Vw2-Vt;-||Vwi|^-2V^1.Vv)dx
= /
= 11 (iiv^ir^-iiv^ir^v^+^o-v^dx + 5 / (llVual^ + IIVuilp-^V^a-iiiJ-Vvdx.
(5.42)
We next use this identity to show that operator A is strongly monotone (see Part (a) below) and Lipschitz continuous (see Part (b) below). Part (a). Operator A is strongly monotone. We show that there exists a constant ao > 0 such that (u2 - uuAu2
- Am) > a0\\u2 - u ^ ,
V uuu2
€ Wtf'^fi).
(5.43)
To do so, let v = u2 - u\ in Equation (5.42). Thus, the first integral on the right-hand side becomes
\ I {\\^u2\f-2-\\Vu1\r2)V(u2 = \ f (
+
u1)-V(u2-u1)dx
llVualp- 2 - H V t i i i r 2 ) ( IIV^II 2 - | | V ^ | | 2 )dx > 0,
so that (u2 — u\, Au2 — Au{) > | /
( l | V w 2 | r 2 + H V w i i r 2 ) ||V(« 2 -
2 Ul)\\ dx.
Then, we introduce an auxiliary function Mfr*
ii^r 2 +iMr 2
(e
.
r
(5.44)
Monotone Operator Equations
205
77) |£,»? | £, r\ e R2 , £ # where G = {(£, r?) ^ 77}. We next show that inf
(€,V)€G
4>^,r])>0. <£(£,»?) > 0 .
(5.45)
To do so, we first note that hat since 4.(0,77) = = !1,, 4.(0,77)
V rTy7^^#O0 ,
it suffices to verify that lat inf
U,n)ea (f,n)eo
4>(£,77)>0. 4>(£,T?) >0.
(5.46)
We also note that for any ^(t^, try)v) = <£(£,T?). 4.(^,77). Hence, by the the y t > 0, we have <j>{t^t rotational invariance of an m inner product about the original in a Euclidean space, instead of showing (5.46), it suffices to verify that inf
4.(1,77) > 0 , 4.(1,7?) 4-(l,r?)>0,
=( (1,0). I= 1,0).
(5.47)
To do so, we first first point int out that lim 4.(|,77) 4.(1,77) = iJ 22 IMI—00 ^ ' " \ ll IMI—00
2 llfp f p = 2
,. f 11 Ll- s llim i m ^4>{ln) (|,t7)= (\ * = »7->{ »j-»€ [00
i fl pf =P22 , /^ ' if p *> Zl' 22..
'' ii ff pp >> 22 ,
and
These two limits, together with the fact that 4>(l 4>(|, 77) > > 0 for 77 ^ f, imply the Inequality (5.47). Inequalities (5.44) and (5.45) give the expected (5.43), with
^-SttSU*^Part (b). Operator A is Lipschitz continuous. We show that there exists a constant M > 0 such that
2 2 I1(v(v, , AuAu ) I <1 M|| - U2l |-| Wl ( n| K( iHr 2t i +i i|r| W + 2 |ir n2 )r| H) | ,IMI , Am) < MU 3 \\u 22 -AUl
W
+ IWJIMI,
Vuuu«2,v€W^(Q). ,«6^(n). U l l
This implies that A is Lipschitz continuous.
2
(5.48) (5.48)
Chapter 5
206
To show (5.48), we observe that when p = 2, this inequality holds. Hence, suppose p > 2. Thus, applying the Holder inequality to the second integral of (5.42), we obtain I / (||Vti2ir2 + l|Vtii|r2)V(t*2-«i)-Vt;cfe I Jn (p-2)/p
< { £ (iivn 2 ir 2 + nv W l ir 2 ) p/(p - 2) <**}
|T*2 — 1*l|| " | | f |
<(iiU2ir2+iKir2)iK-Wlii.ibii.
(5.49)
Next, in order to estimate the first integral of (5.42), we introduce the following auxiliary function
HCv)
iie-^iKiieii^ + iMip- 2 )'
and then show that sup
(5.50)
rl>(£,ri)
where G is the same as defined above. Similarly, it suffices to show that sup V(&»7)<«>,
£ = (1,0).
(5.51)
It is clear that lim ^>(f, rj) = 1 IMI->oo
and
lim ^(£, v) = V - 2 •
v->£
Then, (5.51) follows from these two limits and the continuity of ip(i,rj). Now, applying the Holder inequality to (5.50) yields I / ( \\VU2\\P-2 I Jn <
sup (£,V)€G ;,»?)€G
<
SUp
- HVtiiir- 2 ) V(t*i + u2)
-Vvdx\ I
^(£,77) / ( | | V W l | r 2 + | | V W 2 | r 2 ) | | V ( W 2 - m ) | | . | | V i ; | | ^ JQ
^,T/)(||til|p-2 + ||tl2|r2)||fl2-t*l||-|H|.
Finally, combining (5.49), (5.52) and (5.42) gives (5.48), with M = - ( l +
sup
iC(&*?)).
(5.52)
Monotone Operator Equations
207
In the above, we have shown that operator A is strongly monotone and demicontinuous. Hence, under a suitable approximation scheme Tn = {Xn}, with Xn C X n + i C W^p(ft) and U™=1Xn = W^P(Q), by Theorem 5.10 we know that the approximate equation {v,Aun) = ( v , / * ) ,
Vv
eXn,
has a unique solution un 6 X n , n = 1,2, • • •. Moreover, the solution sequence {un} strongly converges in WQ'P(Q), with the limit u e WQ'P(Q) being the unique solution of Equation (5.41). Inequality (5.48) implies that operator A is Lipschitz continuous. Ac cording to Theorem 5.11, we have the following error bound: IK-ti||
inf
Wu-vW^^-V.
(5.53)
v€Xn
If ft is a polygonal region, then it is possible to give a more precise es timate. In this case, partition ft by a sequence of triangular subregions Ah such that ft = UxeAhK- Let hx be the minimal diameter of the disk that contains triangle K, and let h = msxKeAh ^K- Then let pK > 0 be the max imal diameter of the disk contained in triangle K, and let p = max^e Ah pK • Suppose that h —► 0 when the above partition becomes dense in 17, and that there exists a constant VQ > 0 such that hK <
»
"OPK
VK
eAh.
For each of such partitions, A&, choose a finite-dimensional subspace of W£'p(tl) as follows: Xh = {wh | wh € C(ft), wh\K is a polynomial of degree one Wfc(&)=o,
v&e^ndft},
where fth is the family of all angular points of triangles K in A&. Then, define an interpolation operator 11^ : w —► n^w € Xn by (nfcti;) (6) = w(b),
V 6 € tlh .
According to the interpolation theory in a Sobolev space, there exists a con stant c such that \w ~ n H i , P , n ^ ch\™kP,n ,
V w e w^p(n)
n
tf^(ft).
Since the norms || • || and | • \i,Pln are equivalent, the above inequality can be rewritten as | \w - Uhw\ | < ch\w\2^n
,
V w € W^p(n) n W ^ f l ) ,
Chapter 5
208
or
inf
||w-i»||
Vffl£<''(fl)n^(l!).
v€Xn
This, together with (5.53), give the following error bound for the approximate solution un: Hue W^'p(n) n W2
IK-«ll
-E^(H^ir 2 £)+Kx,.) = /(x), w = 0,
xefl,
x € dfi.
The weak form of this problem is to find u € W0'P(Q) such that / ||Vix|| p " 2 Vu-Vv Jn = f fv dx,
dx+ / b(sc,iA)v cfc Jn
Vv G^ ( H ) .
(5.54)
Next, we suppose that for a fixed x G fl, b(x,£) is continuous with respect to £ € it, and for a fixed £ € i?, 6(x, £) is measurable with respect to x G f t . Suppose also that there exists a constant c > 0 such that
!&(*,$)i^(I + K P - 1 ) ,
VXGQ,
Then, it is clear that for each fixed u € WQ'P(£1), the integral is a bounded linear functional of v G W0'P(Q), namely, \jb(x,u)v
dx I < c ( l + K ^ n ) | | f ||,
(5.55)
veei?.
J f i b(x,u)vdx
V v € Wo 1,P («).
Thus, it defines an operator B : W01,p(ft) - * [W 0 1,p (n)]* by / b(x, u)v dx = (v, Bu), in
V v € W 0 1,p (ft),
so that Equation (5.54) can be rewritten as Au + Bu = r ,
/ * € [W01,p(fi)] *.
(5.54')
Monotone Operator Equations
209
Now, we show that the operator B introduced above is completely con tinuous. If not, then there would be a sequence {UJ} C W 0 ' p (ft) such that Uj ™—> u e W0 ,P(Q) as j —> oo and \\Buj -Bu\\>e0,
for all j = 1,2, • • • ,
(5.56)
for some €Q > 0. By the compactness of the embedding W0'P(CL) into L p (fi), we know that {UJ} would contain a subsequence {unj} converging strongly to u e LP(Q,). Without loss of generality, let us suppose that {unj} converges to u(x) almost everywhere in ft. Thus, it would follow from the assumption on 6(x, £) and the Lebesgue (Dominated) Convergence Theorem [35] that \\Bunj-Bu\\=
sup
/
.6W 0 l l P (n) \Jnl
6(a;,Mni) -b(x,u)\v
< c < I \ 6(x, unj (x)) - 6(x, u(x)) \ dx>
-* 0
dx\ J
I
(j —> oo),
which contradicts Inequality (5.56). We finally remark that if 6(x, £) is so defined that the operator A + B satisfies the general coercive condition, then by Theorem 5.13 we know that Equation (5.54) is strongly approximate-solvable with respect to the approximation scheme Tn defined above. Example 5.6. Let ft be a bounded region in R2 with boundary dd. Consider the boundary value problem J - Au 4- \u\6u = f(x), x e ft, 1 u(x) = 0, x e dQ,, where 8 > 0 is a constant, and / £ Z^ft). The weak form of this classical problem is to find a u £ HQ (Q) such that I Vu-Vv
dx+
JQ
j \u\6uv dx= JQ
To this end, since f^ fvdx can be rewritten as
V v e H%(Si).
(5.57)
is a bounded linear functional of v G HQ(Q),
[ fvdx = (v,f*), Jn
[ fv dx, Jn
V.G^),
it
Chapter 5
210
>oint out that for any u e H&(il), i # ( n ) , the leftwhere / * e6 [ \Hi(il J # ( n ) ] * . We next point ffoW hand side of Equation (5.57) is alsoo a bounded linear functional of v € H&(0). Equat i(fi) into is continuous, Indeed, since the eembedding of H&(Cl) intoLa(« L2(<5+1+1)(n) )(£2)is continuous,we wehave have fi), and |u|*u € La(n), L2(Q), anc c |IH 2,n = H o i + i ) , Q- ^*-rii,2,n N i i n -• I«*I^ l"o ,lo,2,n ~ rio,2(*+i),o
,r we we obtain the H Holder inequality inequality we obtain obtain Then, usingSthe Holder >dx+ jf \u\ I\ f VuVvdx+ \u\ssuv uv dx\ dx\ Jn \Jo \Jn Jn Jn II ^ Hl i < , 2 ,2n l>v l U i , 2n2,n f l + lNM>,2,nMo,2,n H«No,2,nHo,2,n lluMoAnMo,2,n
<(K^c\u\^)K, 2,a.2,aC|
f \ufuv W
VV«v€e f H^(Cl), fo1^),
where the operator operate A : H^(ft) —* [H&(0)]*. [i/o1 ( f l ) ] \ Thus, Thus, Equation Equation (5.57) (5.57) can can be be rewritten as Au (5.57') i4« = f/ *. . Now, we examine exan the monotonicity 0 nicity of the operator A introduced above. Since \t\H is a mo: monotonically increasing •easing function of* € (-00,00), (-oo, oo), we have fi
tf
(( || ** il || 5 ** il --N N ' ** 2 2 )) (( *' li -- * *<2 22)))>^>0°0,,,
V *t*1!1;,;it22 €e (-00,00). V (( -- 00 00 ,, 00 00 )) ..
Consequently, ently, ({Ul Ul-u22,AUl Ul-Au22) 2 2 s ss - |t*2|*« \u2\ u2)(u -u2)dx u1-\u2\ = dx + fIf ( |KW|l |VV {\ui\ («i u2)dx == /I [V(«i [V(t --u2u)]2)]dx+ 2)(-Ul 1-u2)dx 2) u Jn Jo Jn Jn > « i -- «2li,2,n» « > |l«i V t,1i,u2eH^{Q), i.^eflo1^),
which implies thai ^A is a stronglyy monotone operator. lplies that Next, t, we exa: examine the continuity luity of the operator A. For this purpose, we first point out that there exists ts a constant c > 0 such that
II\Jo// ('|«i|*«i - \u2\ u2) V dx\ Ss
u2) V dx\
S < cc( (|u2| | , li 2,n + |«! < | t t l - ««22|lflf| i2,>>0 Mo oAAnn,, t*2|i,2,n 2o),)°n )|«i V - -t-«2|i,2,n|t;|o,2,n, tW 2 2|i,2,n k 2 , n MMo,2,n, w .. .. .. ^ r r l / v ^ \ ff(j(fi). V ui,u«2,«>€ € Ho{il). 2,v
Monotone Operator Equations
211
To verify this, we observe that if 6 = 0 then the Holder inequality yields immediately the above result. So suppose S 6 > 0. It is easily seen that there are constants a and f30 satisfying a,(3,a8>2
and
| + - + i = 1.
According to the Sobolev Embedding Theorem [1] (see Appendix B.4.4), the embeddings H^{Q)^L H£(Q) <-►aS(Q) LaS{Q)
and
fl^(n) H&(0) «-> <-> 1^(0) L^O)
are both continuous, so that u € / # ( n ) =4> « e L a « ( f i ) n ^ ( Q ) , \u\o,as,n, |«|o,/»,n < c|u|ii |«|o,o«,n, |w|o,a«,n, c|«|i, c|tt| l l2 ,n. s4 Furthermore, observe f^(|t|'«) + 6)\t\ 6)\t\\4e, so that an application of aserve that £(|t| t(\t\ t) *) = (1 +«)|*| the Holder inequality gives
{\ul\6u1-\u2tu2)vdx\
\[ =
/ ( l1++« S)) |«2 |« u2 + + 0(ui |'(«i — -« u«2)» [(1+6) 2 2)) |*(«1 22 ) v« dx\
Iin
M + ul «i i - « 2 | ) aa*S«dfxa } < ( (! 1 +5* ) { / (l«2l
- + ) { X ( + | ~u^
}
x6
I
<11)) ((00 <
|w|«i-ti2|o i tt2| 1j9An,nHo,2,n |v|o 2 n
~ °' ' -
Mo,2,n < (1 + «)(|u «)(|«2|o,a«,n « 2 |20|o,a«,n) ,a«,n) |«i - «2|o,/»,n |»|o,2,n 2 |o,««,n + |«i - M < c( |« 2 | li 2,n + K oAn , |«i - « 2 ||il il2, n )*|«! ) V - ««2li,2 Mo,2,o 2 |i,2,n ln M so that \(v,
Au AUl1-Au2)\
< | tt iiii--««22| |i i, ,2 2l nl nMMi ,u2 , n
+ c( |«2| li 2,n + |«i - «2|i,2,n) { |«i - «2| « 2 | llll2,n |«|i,2,n, Mi,2,n,
w ,u2 e mm,
11 andforallw1,w2€F («), andforallMi,M2€H Ul 0 0 (S2),
4 \\Am« i - Au2\\ < [l + c( |tx2| \u2\1> 2,a + |«i |t*i - ti2| |«i - ««2|i P « 2 |i,2,n) ] l«i 2 | >i 2,n li 2 i n)'] 1?2,n An •
212
Copier Chapter 5
This implies that the operator A is Lipschitz continuous on H&(Q). To this end, under the approximation scheme r „ = {Xn} that satisfies the required conditions, Theorems 5.10 and 5.11 together imply that the approximate equation I/ Vun •Vvdx \sunv dxdx= = f [fvdx, • Vz> dx+ +I / \un|ti„|V,« fvdx, JQ
JQ JCI
VveX \/veX n, n,
JQ. JQ
always has a unique solution un € Xn, n = 1,2, • • •• and the solution sequence {un} strongly converges within the space H^(Sl), whose limit u € H£(Q) is the unique solution of Equation (5.57). Moreover, there is a constant c> 0 such that K - « l i 2 n < c - inf | t t - « | i 2 n ' '' vex vexn n ' ' Example 5.7. We now consider a second-order boundary value problem of a quasi-linear partial differential equation. Let SI C E71 be a bounded region with boundary dSl. Consider the following first kind of homogeneous boundary value problem of an elliptic equation:
- ^ f ^ ^ V ^ +^ ^ V ^ ^ f x ) ,
xx€Q, eQ,
(5.58)
»»=i = i a XaXii
«u(x)= ( x ) = 00,,
(5.59)
x€d£2, x € dSl,
where x = (xi, • ■ •• xnn) V« = (du/dxu • • •• du/dxn), and d / e2(Sl). We have the following assumptions. (i) ^ ( x . t i . p i , • • • ,pn) are eontinuous so SI x Rnn+, with hi(x,0,0) ) €2(Sl) for alH = 1, • • •, n, and there are constants cx and c2 such that
ci
, and
\daAI idot —
kl-
I dai I \dai\ h~H— p —
ij l,---,n. h3 = = 1, •••,«• (ii) There is a constant CQ > 0 such that o
n n
da*
t j ' == l i,3 1
^
E
nn
6& > coE^2. i=l
for all &, i = 1, • • •• n, uniformly on f2 x # " + ^ . (hi) b(x,u,Pu• ■ • ,Pn) is sifferentiable eo nI x Rn+\ , i t h h(x,x,00 ) L2(Sl), and there are constants c3, c4, and c = C(co, 02,04) such that —
< c4
and
0 < cc < ^ < C3, < |— C3 ,
o-
Monotone Operator Equations Equations
213 213
for all j = 1, - , n . (iv) There is a constant c 5 , with 0 < c5 < CQ, such that ^(c2 ^(c2 + c4) c 4 ) 2 -4c(«,-c - 4 c ( c o - c55)<0. )<0. On the other hand, we note that the generalized Dirichlet form of problem (5.58)-(5.59) is to find a u G H$(Q) such that /
/ a^(x, zz,
Jn J n Vfr[ L ^
dx
= fvdx, =f [fvdx,
V.e^O). VveHfcn).
Jn
i #*<
J J (5.60) (5.60)
Under Conditions (i) and (iii), it is easily seen that for each u G H&{tt), the integral on the left-hand side of Equation (5.60) is a bounded linear functional on fl^(n), denoted Au, namely, c r J?-.
(v,Au)= I Jn ./n
fin
i
li^a^w^u)^ h b(x,w,Vu)u\dx, Voj(i)w,Vtt)f-h6(i,w,Vtt)u Lb, Vv€H&(Cl). V«€^(n). Yjr[ oxi J L^ &*i
Similarly, the right-hand side of Equation (5.60) is also a bounded linear functional on H&(il), denoted /*, namely, ((*,/*)= *,/*)= f / f-vdx, fvdx, Jn Jn
( n ) ,, vVv, ^^ ^H£(Q)
Hence, by using these notations Equation (5.60) can be rewritten as
Au = r . To establish the approximate-solvability of Equation (5.60) with respect to an appropriate approximation scheme, we next analyze the continuity and monotonicity of the operator A defined above. First, it follows from Conditions (i) and (iii) that for any uuu2,^ € \(v,AUl-Au2)\ fr fr ,A ,A|0(tii-u |a(«i-«22)|)| \9v\ 1^1
+ c3\Ul-u2\.\v\
+ i=1 i = l
|\
fv, - ,
, 1. \dv\ ^1
ccf]\d{Ul'U2)\.\v\)dx,
CXj OXi
\|
J)
214
Chapter 5
and so there exists a constant M > 0 such that for all u\, 112, v G
HQ(£1),
| (v, Au± - Au2) | < M\ui - U2|i,2,nMi,2,n , which implies that A is Lipschitz continuous. Indeed, we have \\Au! -Au2\\
< M|t*i -t*2|i,2,n,
Vwi,w 2 €
ffo(fl)-
Second, for any wi,^2,vG ifo(fi), (v, Aui - ^4w2)
=/„{ ^
[ai(x,Wi, VlXi) ~ Oi(x,W2, V w 2 ) ] 7T~
• t=l
*
[6(x, wi, Vwi) — b(x, ti2, Vw2)]v >
a(t*i - w2) #"
f
~— ( * , & , » 7 i )
S2 k , • _ ! < % n o
dv
+ ^(a?,6,^2)(wi -W2>
E ^db (*.&,•») d(u\
— U2) 1 ,
dxi
*>*»,
where ik = u2(x) + 0fc[t*i(x) - u2(x)] , r/fc = Vu2{x) + 6>fc[V^i(x) - Vti 2 (x)] O<0fc
k =1,2.
By Conditions (i)-(iii), we have (1*1 -tt 2 ,^4wi - Au 2 ) >
"9(^i - i t 2 )
dxi n (C2 + C 4 ) ^ | W 1 - t * 2
9(^! - u2) -h c(tq — U2)2 > dx. dxi
Monotone Operator Equations
215
It then follows from Condition (iv) that (co - c5)
d(ux
-u2)
dxi
~ (C2 + C 4 ) | ^ i -
U2\
d{u\ — u2) dxi
n so that ( l i l - U2 , Au\
- Au2)
> C5|ui - 1A2|l,2 Q >
which implies that operator A : HQ(Q) —► [ H Q ( Q ) ] * is strongly monotone. Finally, if we choose an appropriate approximation scheme Tn = {X n }, then by Theorems 5.10 and 5.11 the approximate equation /
^
a%(x, un, Vun)—
= I fv dx,
Vv e
+ b(x,un,S7un)v
dx
Xn,
JQ
always has a unique solution un € Xn, and the solution sequence {un} con verges strongly to a limit u € HQ (Q), which is the unique solution of Equation (5.60). Moreover, for the approximate solutions, we have the following error bound: \Un - u\iy2tn <
inf C5
|w-vi,2,n.
v£Xn
Example 5.8. We again consider Example 5.7, but with nonlinear boundary value conditions: - ] T —
x e ft,
(5.61)
t=i
Y^ Oi(x, w, Vw) cos(7, Xi) + a(x)w(x) = 0(x),
x € <9ft ,
(5.62)
where <£ € I/2(Q), cr is a continuous nonnegative function on d£l, cos(7,x^) denotes the ith component of the unit outer normal vector of 7 on dQ, in which dfl is assumed to be piecewise smooth. In addition to the Conditions (i)-(iv) stated in Example 5.7, we strengthen Condition (iv) as (iv') or add Condition (v), as follows: (iv') n(c 2 + c 4 ) 2 - 2c(co - c5) < 0.
Chapter 5
216 (v)
There is a piece dfti C dft with measdfti > 0, such that a > a0 > 0 on dft i for some constant (To > 0. We note that the weak form of problem (5.61)-(5.62) is to find a u G if 1 (ft) such that / y^ai(:r,u, V u ) h 6(x, u, Vu)v \ dx + / cruvds 9x Jn L^zt * J -/an = [ fvdx+ Jn
VveH1^).
[ 4>vds, JdQ
Observe that the embedding H1^) is a constant c > 0 such that
(5.63)
<^-> Z,2(dft) is continuous, namely, there
\ 1/2
an
v2ds)
/
< c|H|i|2fn,
VuGtf^ft).
(5.64)
Similar to the discussions given in Example 5.7, for any u G if 1 (ft) the lefthand side of Equation (5.63) is a bounded linear functional on Hl{Q) and is denoted by Au: r r n f) (v, Au) = / 5 ^ fli(^i u, Vu) + / auvds, Van
h b(x, u, Vw)i; dx
V v G iJ x (ft).
Also, for every / G L 2 (ft) and
VveH1^).
[ <j)vds, Jan
Thus, Equation (5.63) can be rewritten as Au = f*. For an appropriate approximation scheme Tn = {Xn}, the approximate equa tion is p
r
p.
n
-i
/ y^a^(x,un,Vun)\-b(x,un,Vun)v •/ft L i = 1 ^^i =
fvdx+ Jn
\/veXn,
_
\ dx + / aunv ds J Jan n = l,2,-.-.
(5.65)
Monotone Operator Equations
217
To establish the approximate solvability of Equation (5.63) with respect to the approximation scheme T n , we next analyze the monotonicity and con tinuity. For any 1*1,1*2 € if 1 (ft), we have, from the above derivation, (til — U2 , Au\ — AU2)
a
/0ht(3^s2),-c»+«.)ti«.-i+ c(ui
-U2)
d(u\ - U2) dxi
2 dx +- / o~(u\ — U2) ds .
(5.66)
Jdn
If Condition (iv') is satisfied, then the above inequality gives (**i - u2 , Aui - Au2) > c 5 \m - W2|i,2,n + o M
(Ul~
u dx
^ •
Hence, there is a constant ro > 0 such that (5.67)
(u\ - U2 , Au\ - A1L2) > ro\\ui - 1*2111,2n,1•
On the other hand, if Condition (v) is satisfied, it then follows from (5.66) that (ui — 1^2 , Aui — AU2) > C5\Ui - W 2 |i 2 Q + a0
> c5|wi -U2|l,2,n + Let £(v) = J a n
/
(Wl tfo
^2)2^S
n2
r /*
/ (wi - U2)ds meas dft 1 L^aQi vds. Then, by (5.64) we have
(5.68)
\l/2
\l{v)\ < (mess dQ!)1/2(
f
d v2ds^j
V ^ ^ f i ) ,
which implies that £ G [H1 (fi)] . Obviously, for any nonzero polynomial v of degree zero, we have £(v) ^ 0. To this end, we recall the Norm Equivalence Theorem in a Sobolev space, which states that for any ^1, • • •, £n e [Hk(Ct)] and any nonzero polynomial v of degree less than or equal to k — 1, if £i(v), — -,£n(v) are not simultaneously zero, then the norms
Mfc72,Q + X ^ ^ I i=l
and
IMk2,n
Chapter 5
218
are equivalent. Thus, by using the Norm Equivalence Theorem and Inequality (5.68), it can be easily verified that Inequality (5.67) holds as well. Therefore, under either Condition (iv') or Condition (v), the operator A is strongly monotone. As to the continuity of operator A, we observe that for any ui,u2,v G iJ 1 (fi), it follows from the above derivation that
I| (v (v,, Au\ Au\ -- Au Au2)2) | I
*/0h£P^|-|£hS'--'-l&l E
l d(ui - u2) I x, A ,) , V dx ' ' ^' I
+ / cr\u\
1
V Vwi,u U I , U22 Ge JET^fi). H ^).
Then, by Theorems 5.10 and 5.11, for any / e L2(£l) and <j> e L2(£l), Equation (5.65) has a unique solution un e iJ 1 (0); and the solution sequence {un} converges strongly to a unique u e H1^), which is the unique solution of Equation (5.63). Moreover, we have the error bound M I K - uu | | i , 2 , n < — • inf ro vexn
\\u-v\\i \\u-v\\ixn xn.
Example 5.9. Consider the boundary value problem of the following thirdorder ordinary differential equation: - {a(t)u"(t))' (a(t)u"(t))'
+ + b(t,u,u')
u(0)=u'(0) u ( 0 ) = u ' ( 0 ) = uu''((ll))==00..
= f(t), f(t),
tt ee( o(0,1), ,i),
(5.69) (5.70)
We define its corresponding generalized solution to be a function u e V, where V={v\ v€H veH2{0,l), (0,l), v(0) = = v'(0) v'(0) = v'(l) = 0} ,
Monotone Operator Equations
219
that satisfies the following condition: / [a(t)u"v" + b(t,u,u')v,]dt Jo
= [ fv'dt, Jo
VveV.
(5.71)
Suppose that both a : [0,1] —► R and b : [0,1] x R2 —» R are continuous functions, and that there are constants ao > 0 and &o > -7r 2 ao/4 such that a(t) > ao , Kt,&v)v>W,
V t € [0,1], Vt€[0,l],
(C,T7)€fl 2 .
We will then use the framework established in Section 5.4, and define oper ators A, B and K as follows: A:
V(A) = {v e ff3(0,1) | v(0) = v'(0) = v'(l) = 0} — ff = L 2 ( 0 , l ) ,
B: K:
V(B) = V(A) -> P ( K ) = Vr -> # ,
Av = tf,
-(av")'-
flv = 6(t,t;,t/); JRCv = v ' .
Then, it follows from the Hardy inequality that the norms I • b := | • |2,2f(o,i)
and
|| • || 2 := || • lb,2,(o,i)
are equivalent in space V. Observe that for any Cauchy sequence {vn} in V, the sequence {v!^} converges in 1/2(0, !)• Hence, for any w € V, we have {Avn - Avm , Kw)L2
= (av„ - av!^ , w")L^ -> 0,
(n, m -> oo),
that is, Condition ( # i ) stated in Section 5.4 holds. On the other hand, for any weak Cauchy sequence {vn} in V, it follows from the compactness of the embedding F 2 (0,1) <-» C^O, 1] that {vn} strongly converges in C^O, 1], so that \(Bvn-Bvm,Kw)L2\
=
I r1 /
[Kt,vnyn)-b{t,vmym)]w'dt
\Jo
x
< (jf |6(t,i; n ,0-^t; m ,O| 2 *) (n, m —» oo)
l/2
'w||2
II
uniformly with respect to w e V, satisfying HHk = 1- Hence, Condition (Hz) stated in Section 5.4 holds.
220
Chapter 5 Next, we observe that (Ax2 - Axi, K(x2 -
xi))L2
a(t)(x'i-x'{)2dt
= [ Jo i
12
> ao\x2 - xi
,
V x i , x 2 € V,
so that (Ax + 5 x , x)L Fl2
= T^r [
\x\2 JO
\a{x")2 +
b(t,x,x')x']dt
F|2 where rj = min {ao, ao + 46O/TT2} > 0. Hence, the operators A and A 4- B are strongly iif-monotone and if-coercive, respectively. Thus, by Theorem 5.15, when an appropriate approximation scheme T n = {Xn} is given, the approximate equation is /
[ o ( t ) « y + 6(t,un,ri n )v']dt=
[ fvdt,
V v e Vn ,
n = 1,2, • • •. To this end, Equation (5.71) is strongly approximate-solvable with respect to the scheme T n , so that the boundary value problem (5.69)(5.70) has a generalized solution.
Monotone Operator Equations
221 Exercises
5 . 1 . Recall the concepts of monotonicity and coerciveness defined in Sec tion 5.3.3. Show that Theorems 5.9-5.13 hold also for complex Banach spaces. 5.2. Let F b e a real Hilbert space and let T : V —► V be an operator. Define 'A*) = sup and 6{T)
-
ll«--v\\v
<« -v, ,Tu-
Tv)v -Tv\\v -wIMPv
sup u,vev
14-
which has the geometric meaning as the maximum length of stretch and maximum rotation of the operator T, respectively. Let {Vn} be a sequence of finite-dimensional subspaces of V, satisfying Vn C V^ + i and V%LiVn = V. Then, let Pn : V —> Vn be a bounded linear projection operator. Consider the fixed point equation u = Tu
(a)
un = Tnun ,
(6)
and its approximate equations
where Tn = PnT \Vn. Verify the following results: (1) If L(T)9(T) < 1 then Equation (a) is uniquely and strongly approximatesolvable with respect to the scheme Tn = {Vn, Pn}, that is, Equation (b) has a unique solution un e Vn, with un —» u € V, which is the unique solution of Equation (a). (2) If T = A + B with A : V -> V satisfying L{A)0{A) < 1 and B : V —> V being completely continuous and quasi-bounded with a quasi-norm |||J5||| < 1 - L(A)0(A), then Equation (a) is strongly approximate-solvable with respect to the scheme Fn = {Vn, P n } , that is, Equation (b) has a solution un e Vn, where {un} has a strongly convergent subsequence {unj} such that unj —► u € V, which is the solution of Equation (a). Here, operator B is said to be quasi-bounded if
|||£|||:- inf ( sup J I ^ I M 0
< oo,
Chapter 5
222
and |||JB||| is called the quasi-norm of B. We note that (i) when L(T) < 1, i.e., T is a contraction mapping, we have L(T)6{T) < 1, thereby obtain the contraction mapping principle; (ii) if L(T) < 1, i.e., T is a non-expanding mapping, and if 0(T) < 1, then L(T)9(T) < 1 so that 0(T) < 1 is a sufficient condition for the existence and uniqueness of the fixed point of a non-expanding mapping, and also a condition for the projective approximate-solvability of this fixed point equation; (iii) when L(T)6(T) < c, we have (u — v,Tu — Tv)v < c\\u — v\\y, whereas an operator T that satisfies the second inequality is called a semi-bounded operator (in particular, if (u — v,Tu — Tv)v < 0 then T is called an anti-monotome operator). The reader may try to give a sufficient condition for the existence and uniqueness of the fixed point of a semi-bounded operator and its projective approximate-solvability. 5.3. Let X he a separable and reflexive Banach space, and K C X he a closed convex set. An operator A : K —> X* is said to be pseudo-monotone if A is bounded and has the following property: For any un, u G K such that un w—> u as n —> oo, lim (un — u, Aun) < 0 implies lim (un — v , Aun) > (u — v, Au),
Vv e X .
Show that if A : X —> X* is bounded, hemicontinuous, and monotone, then A is pseudo-monotone. 5.4. Let X be a reflexive and separable Banach space, and K C X he a nonempty bounded and closed convex set. Let A : K —» X* be a pseudo-monotone operator and / € X*. Consider the inequality equa tion problem: Find & u e K such that (v - u, Au) > {v - u, / ) ,
\/veK.
(c)
Construct a sequence of closed convex sets, {Kn}, such that Kn C X n , KnCKn+x,
X n is a finite-dimensional subspace of X , 71=1,2,.-.,
U£°=1Kn = K .
To solve the approximate equations of Equation (c) is to find un £ Kn such that (vn - un , Aun) >(vn-unif),
V vneKn.
(d)
Monotone Operator Equations
223
To solve Equations (d), we first introduce an inner product [•, ■] and its induced norm | ■ | into Xn. If £ G X*, then there exists a continuous linear operator r n : X* —► Xn, such that
(v,t) = [v,rne\,
Vvexn.
Hence, Equations (d) is equivalent to [Vn ~ Un , TnAun] > [vn - Un , Tnf] ,
V Vn G Kn ,
or [vn ~ Un , Un] > [vn ~ Un , U n + Tnf
~ TnAun]
,
V Vn G X n •
(^)
(1) Let IIx,, be the best approximate projection of Xn onto if n , namely, for any u G X n , the projection 1 1 ^ u satisfies \u — HKnu I = min \u — v \. v£Kn
Show that problem (df) is equivalent to finding a un G ifn such that Un = UKn (u (2) Let Tn : Kn -+ Kn
/ - TnA7Zn) . + T n n be an operator defined by
Tnv = UKri (v + rnf - rnAv)
,
V v e Kn-
Use the Brouwer Fixed Point Theorem to show that operator Tn has a fixed point un G Kn, and so the approximate Equation (d) is solvable. (3) Show that the solution sequence {un} obtained above has weakly convergent subsequences, and the limit of any such subsequence is a solution of Equation (c). In the following exercises, we address the questions of unique and strong approximate-solvability for initial or boundary value problems of nonlin ear operator equations, their projective approximation schemes, and error bounds.
224
Chapter 5
5.5. Consider the initial value problem of the ordinary differential equation f - (p(t)u'(t)Y
+ q{t)u(t) + r(t, u) = f(t),
t € (0, oo),
( ti(0) = 0 .
Suppose that (i) / ( t ) € L 2 ( 0 , o o ) ; (ii) p(t) is absolutely continuous in any bounded subinterval of [0, oo), p'(t) is bounded on [0, oo), and there exists constants po and p\ such that Pi > p(t) > po > 0 for all t e [0, oo); (iii) q(t) is measurable on [0, oo), and there exist constants qo and q\ such that q\ > q(t) > qo > 0 for all t € [0, oo); and (iv) for any fixed u € R, r(t, u) is measurable with respect to t e [0, oo), with r(t, 0) 6 £2(0,00), and for any fixed t € [0,00), r(t, w) is continuous with respect to u € # ; moreover, there exists a constant Ao < qo such that r(t,6)~r(t,6) ^
x
--A°'
ft-6
and for arbitrary M > 0, there exists a constant if = K{M) > 0 such that |r(i,£i)-r(i,£2)|
Vt€[0,oo),
|&|,|6|<M.
Solve the weak form of the problem: Find a w e V , where y={ti€flrl(0,oo) I
ti(0)=0},
such that /•OO
/ Jo
/.OO
[pwV + gm7 + r(£,w)t>] df = / Jo
fvdt,
VveV.
5.6. Consider the following initial value problem of a fourth-order ordinary differential equation: f «<4>(t) + u(t) + ( K ( t ) f + 1 ) ' = f(t),
t € (0,00),
l « ( 0 ) = «'(0) = 0, where p is a positive even integer and f(t) e £2(0, oo). The weak form of the problem is to find u eV, where V={u<EH2(0,oo)
I u(0) = u'(0) = 0 } ,
Monotone Operator Equations
225
such that /»oo
/ Jo
/»oo
[u"v" + uv-
( u ' ) p + V ] dt=
fvdt,
VveV.
Jo
5.7. Consider the problem of a stationary flow downward along a plain wall of a fluid whose boundary consists of gas. This dynamical system is described by du + b{x)—+c(u,y) = f, (x,y)en=[0,a}x oy du du (a,|/) = 0 , t*(s,0) = ti(0,y) = —(x,(3) = — -Au
[0,/3],
where b(x) represents the velocity of the fluid and / the possible chemical reaction of the components in the liquid. Suppose that (i) & € C [ 0 , a ] , b(x) > 0 ; (ii) c e C(R x [0,/?]) , c(0,y) = 0, with [ c(tt, y) — c(v, y)](u — v)>0,
V u, v e R;
and for any M > 0, there exists a constant r = r(M) > 0 such that
U
N 1/2 1/2
[c(u,y) -c{y,y)]Z [c(u,y)-c(v,y)]
dxdy \>
/Q
VINUxJblU <M,
where ||w||i = ( / n u 2 d x + fQ(u')2dx) ; (iii) / € 1/2(0). The weak form of the above problem is to find a u € V , where V = { « 6 ^ ( f l ) | u(x,0) = «(0,y) = f j | (*,/?) = ^ ( a , y ) = o | , such that f \du dv
L[^^ =
+
fv dxdy,
du dv T/ .du +b{x) v
^d-y
d~y
, , + c{u y)v
'
VvGF.
dxdy
Chapter oaapter o5
226 226
5.8. Consider insider the following boundary value problem of a second-order partial differential fferential equation: I
£ . K ( x ) ^ - j + fc(x)« + c(x,u) c(x,«) = / ( x ) ,
£
{I{
(n{x)
( x ) u ( x )== 000,,, OiAx) cos(7,Xi) xr i^) ++ +( a722{x)u(x) {x)u{x) oy(x) cos(7,xi) aij{x) cosfr.Xi) o«(x) |P-^ cos(7, 005(7,^)
ft, dft xXx €e ^9ft 9ft,
dXj d j dx x
i% ife ifc
x €€€ f ft, t, xX
*
nn n is an open where rC R 7?.n boundlere ft smoot] bound i? where ft C R is an onen open bounded bounded[ set set with with aa sufficiently sufficiently smooth smooth bound y is the ar ary 9ft, 7 unit outer normal vector of the boundary 9ft, and ary 9ft, 7 is the unit outer normal vector of the boundary 9ft, and (7, (7, xxn)tt)) is the angle 7 x^-axis. Xi-axis. between and the Suppose that it; between utiLwet;ii 7y a-nu LIIC x^-axis. x^-cuus. oSuppose u p p u s e that iiifcit is the angle and the (i) i) ay(x) ay(z) aatj = m a^(x) ) is ft. a,, = aa^, a,,, jU and is aa continuously continuously differentiable differentiable function function in in ft, ft, ay (i) ay(x) tj = ajU and there there is is aa constant constant aa > > 00 such such that that
n n
n n
2,J = 1 i,j=l
22=1 i == 1l
22 2 ]X! T M*)&6 a*, - (x)^^- ^ > aaoc Oij(*)&6 £^ C£42C ,,, «ij(^)66 "XIC >
&, ^ ee /?; 6,6 «;J2; , VvV &,fc V 6,6 eR;
(ii) i) 6(x) b(x) iss continuous and nonnegative in ft; ft: (iii) for any fixed x G €e ft, ft, c(x, c(x,«) u) is continuous with respect to u €e R, # , and t. for any fixed u € e R, c(x,u) c{x,u) is measurable with respect to x 101 any nxeu u t n , c^x,u; is nieasuraDie wicn respect to x €t ift, w i t h c ( x , 0 ) € L 2 ( f t ) , and with with c(x,0)eL2(ft), c ( x , 0 ) e L 2 ( n ) , and
[c(x,6)-c(x,£ [[c(x,6) )(6 c (( xx ,, 66))---cc(x,6)] c((axx,r,£,6262))](£i-6)>0, ]]((66--f-66 >o 00, o,, 26))) >
vV 6/?, V xxxe eeff tt ,, 66 &,,,66 &€ /iR, *i , 6 e
and also for■ any M > > 0 there exists a constant r = r(M) r{M) r(M) > 0 sue such that ( r i 1/2 U xxx, ,utu)t ))---cc( (xx, ,ttdx\ ;,)))|| dd xx }}
>
22a
L2u
1 \7 1/.. V u .1)v <e= fUf(0\ ^), Vu,veH\si),
L2
lU IU,IL
l
2 22 2 22 1 1/2 where \\u\h = = ((/ (f/nffuiiw dx) uUdxddx xx ++ / n KJ)nf(u') .here ||u||i d xdx) ) /1/22 ; na(u') r (iv) / € L (ft); i 22(ft); (7x <7i (7 (v) <J ax (72 rxX and
ai(x) + a<7 C7 [(x)+(7 (x) ai(x)+a ><7 <7i(x) +2(x) >cr0 000 > 0 , 1 (x)+(7 222(x) 2(x) >a
V xx ee d 9^ f t .. V
11 The ttie weak form of the above problem is to find a u € H^Sl) ff^ft) ifH (ft) such that hat /. r 72 f/ fFA vA^
9u 1I du 9u dv ,. .,. {,,.x ),u v + c ,( x uNx,),jd ou dv c(x>tt)t B c ' u> Hdx [[ .; 2L. <* )l «H« +++ C0E c(x,u)v\ dx ^ ^_ax7"_^_9x7++ 6+6^((bx)ttt r^
^
yfyfyf/„i [[ ;2L. <<*%' ax" ax- ^ ax"- + + i
i
+ J/
1,3— 1 2,J 1,3 — 1 1,3 — 1
Z2
L
N
w ™ + '^ H dx <**
r\u(s)v(s)ds= «(s)v(s) ^^ru(s)v(s)ds u(s)v(s) ds= ds = j[f ,vdx, ,vdx,
VveV VveV
1 = = HHHx (ft). (£l).
CHAPTER
6
Operator Evolution Equations and Their Projective Approximate Solutions
Under an appropriate framework established on some function spaces, many diffusion and wave equations can be reformulated as the following operator evolution equation: -
d
^ at
=
A(tHt),
=
A(t)u(t),
or --^
L r
where A(t) is an operator of one parameter, the time t > 0 in general, together with some necessary initial conditions. The above two types of equations are classified as first and second order evolution equations. Various methods of the integral type for linear and nonlinear evolution equations, such as semigroup integral methods and accretive operator methods, have been well developed since 1950s. There is also a huge volume of literature devoted to numerical approximation methods for solutions of differential evolution equations, including some well-known finite difference methods, semi- and completely discretized Galerkin methods, and collocation methods. In this chapter, two general frameworks are established for approximate solutions of abstract evolution equations, and their applications are discussed by using concrete examples.
227
Chapter 6
228 6.1 Preliminaries
In the discussion of solvability of evolution equations, it is necessary to use functions that are defined on the real line and assume values in a Hilbert (or Banach) space. Hence, we first need to briefly introduce such abstract functions, their integrations, derivatives, and linear spaces. More details about this notion can be found in [1, 30, 40, 41]. 6.1.1 Strongly and weakly measurable functions Let H be a Hilbert space with inner product (-,•)« and norm || • ||#, respec tively. As usual, a function of the form N
u(t) = Y,xEj(t)aj1
teR,
(6.1)
j=i
is called a simple function, where {Ej}jL1 are disjoint measurable subsets of the real line R, with finite measure fJ>(Ej) < oo, xE- 1S ^ n e characteristic function of Ej, and ctj G H, j = 1, • • •, N. Definition 6.1. Let E C R be a measurable set and u(t) be a function defined almost everywhere on E which assumes values in H. If there is a sequence of simple functions {^(t)}, with Uj(t) = 0 for t G R\E, j = 1,2, • • •, such that lim \\uj(t)-u(t)\\H=0, (6.2) J—KX3
almost everywhere on E, then u(t) is said to be strongly measurable on E. If, for every v G H, the numerical function (u(t),v)H is measurable on E, then u(t) is said to be weakly measurable on E. Obviously, a strongly measurable function must be weakly measurable. Moreover, its range must be almost separable, namely, there exists a subset of zero-measure, E0 C E, such that {u(t)\ t G E\E0} C H is separable. Conversely, a weakly measurable function with a separable range must be strongly measurable. In addition, if u(t) is strongly measurable on E then ||u(t)||ff is measurable on E. In contrast to the common numerical measurable functions, the (strongly and weakly) measurable functions, which assume values in the space H rather than in the real line i?, will be named abstract functions in the following.
Operator Evolution Equations
229
6.1.2 Bochner integrals The integral of the simple function in the form (6.1) is defined by
L
N
u{t)dt = Y<^E3)<*3-
(6.3)
It is clear that f u(t)dt\\ \JR
< f \\u(t)\\Hdt. \\H
(6.4)
JR
Definition 6.2. Let u(t) be a function defined on a measurable set E C R which assumes values in H. If there exists a sequence of simple functions, {v>j(t)}, as defined in Definition 6.1, such that lim / 11 uAt) - u{t) 11 „
(6.5)
then u(t) is said to be Bochner integrable, or simply B-integrable. If u(t) is B-integrable on E, then { JRUj(t)dt} is a Cauchy sequence in H, and its limit is independent of the choice of {uj(t)}. For this reason, we can define its limit as the Bochner integral of u(t) on the set E, and denote it by I u(t)dt:= lim / u3{t)dt. (6.6) JE J'-*00 JR Similarly to the well-known Lebesgue integrals, the Bochner integral is also absolutely integrable; namely, a measurable function u(t) on E is Bintegrable if and only if ||II(£)||JJ is Lebesgue-integrable and II f u(t)dt\\ \\JE
< f ||ti(t)|| H A . \\H
(6.7)
JE
6.1.3 Abstract functions on the Lp space The familiar C-spaces can be easily extended to abstract functions, such as spaces C^ija, 6]; H) and C™([a, b];H). We mainly discuss the Lp spaces of abstract functions. Let —oo < a < b < oo and 1 < p < oo. Let LP{(a, &);#) = { W W |
W
M strongly measurable on (a, b),
\\u(t)\\H e
Lp(a,b)}
230
Chapter 6
and introduce into it a norm || • || p := || • ||Lp((a,6);H): I" \\u(t)\\pH dt\
,
l<j>
NIP=<
ess sup
||tt(t)||i/,
p = oo.
a
The space Lp((a,b);H)
defined above has the following properties.
(a) Lp((a,b);H), 1 < p < oo, is a Banach space when equipped with the above norm; in particular, when p = 2, it is a Hilbert space with inner product ^)L 2 ((a,6);if) = / (u(t),v{t))^t Ja
.
(b) If # is a separable Hilbert space, then L p ((a, &);#) (1 < p < oo) is separable, and Co ((a, 6); # ) is dense within it, where Co ((a, b); H) = \ u(t) |
u(t) is continuous on (a, b), supp{w(t)} CC (a, 6) | .
Here and throughout, S CC (a, b) means S C < bounded subsets of (a, b) \ . and supp{ii(t)} in (a, b) is the closure of the set [t e (a, 6) | u(t) ^ 0 } . (c) Let p~l + q _ 1 = 1 for 1 < p < oo. For each fixed v(t) G Lq((a,b); if), the following integral t(u)=
f
^€Lp((a,6);F),
(6.8)
is a bounded linear functional on L p ((a, 6); H ) , with norm
||*|| = I M I , .
(6.9)
Conversely, any bounded linear functional C(u) on Lp((a,b)\H) (1 < p < oo) can be expressed by an integral in the form of (6.8) for a unique v(t) € Lq((a,b);H) satisfying (6.9). Properties (a)—(c) together imply that the space Lp((a,b)]H) has all the basic properties of a standard Lp space. Thus, the following result can be easily verified by using Property (c).
Operator Evolution Equations
231
To introduce the next result, we first recall that a subset 5 in a Banach space X is said to be weak- (or weak*-) relatively sequentially compact if every sequence in S contains a weak- (or weak*-) convergent subsequence. Proposition 6.1. (i) Lp((a, b); H), 1 < p < oo, is a reflexive Banach space, and so is weaklycomplete, namely, if {VJ} C L p ((a,6);ff) is a weak Cauchy sequence, namely,
1^(0-^)1-0
(t,j-oo),
V*€[Lp((a,6);ff)]*,
then {UJ} converges weakly in Lp((a,b);H). Moreover, if H is sepa rable, then every set in Lp[(a,b)]H), 1 < p < oo, is weak-relatively sequentially compact if and only if the norm of the set is bounded. (ii) IfH is a separable Hilbert space, then every bounded set in L^ ((a, b); H) is weak*-relatively sequentially compact, namely, there is always a sub sequence {vnj(t)} such that pb
lim
/
rb
(u(t),vnj(t))Hdt=
j—»oo Ja
(u(t),v(t))dt, Ja
Vu(t)€Li((a,k);H), where v(t) G Loo ((a, b);H). 6.1 A Smoothing operator and smooth approximation In this subsection, we let j(t) G C^(R) be a nonnegative function satisfying (a) j (t) = 0 for \t\ > 1; and (b) fRj(t)dt
= l.
Then, we define the smoothing operator J£ by (J£u)(t) = [ j£(t - s)u(s) ds,
(6.10)
JR
where j£(t) = e~lj (t/e) with e > 0. Similarly for standard numerical functions, the following result can be easily verified. Proposition 6.2. Suppose that H is a Hilbert space and u(t) : (a, b) —> H is an abstract function. Define u(t) = 0 G H for t tf. (a, 6).
232
Chapter 6
(i) Ifu(t) e L p ((o,6);ff), 1
and
(Jeu) (t) = 0,
V t € JB,
dist(i, supp{w}) > 5,
where Coc(R\ H) =
\ differentiable arbitrarily many times | .
where
C({ay 6); H) = { t;(t) |
v(t) : (a, b)-+H
continuous } ,
then for any [c, d] C (a, 6), lim \\(J£u)(t)-u(t)\\H
=0
uniformly with respect tote [c, d\. (iii) If u{t) € L p ((a,6); if), 1 < p < oo, then lim | | j e t i - t i | | p = 0 .
Corollary 6.1. The space Cg°((a, 6); # ) is dense in Lp((a, b);H)7 I < p < oo, where c
o*((a> 6); # ) = { v(t) |
v(t) :R-+H
differentiable arbitrarily
many times, supp{w(t)} CC (a, 6) \ . Corollary 6.2. Ifu(t)
€ L p ((a, 6); H), 1 < p < oo, and
I
V^(t)€Cg°((a,6)),
then w(t) = 0 almost everywhere in (a, 6). We remark that Condition (6.11) can be replaced by / m)Mt))Hdt Ja
= 0,
V
(6.11)
Operator Operator Evolution Evolution Equations Equations
233 233
6.1.5 Generalized derivatives of abstract functions and the if Hm space In ±11 this U l l l O subsection, O U U O t 3 l * l j l * J l . l , we W C let ICIJ l cc L ° ((a, ((a,6);H) { u(t) I u(t) € Lp({c,d); ((c,d);if)if) for any [c,d] [c,d] /4° ((a, 6); if) H) = {u(t) [c,d] C ((a, b) 6) } .
Definition 6.3. Let m > 1 be an integer and u(t) u{t) G L[°c((a, ((a, b);H). If the there c f(t) e L[° ((a, b); H) such that is an f{t) m) -- lim)rm [\ /b(m) ^m(t)u(t)dt, Ht)u(t)dt, [/\p(t)f(t)dt /
or
V Vip{t) (t) €e CS»((a,6)) Cg°((a,6)) , '
Am/(.».*-(-i>-/7^W>)-, /«<>./<<».--<-ir/*(^W>)«.
-'a Ja
-'a Ja
\\
a t az
/if IH
V0(t)€Cg°((o,fc);ff), \/<j>{t)€CZ°((a,b);H), V0(t)€Cg°((o,fc);ff), \/<j>{t)€CZ°((a,b);H), then u(t) is said to have an mth-order generalized derivative dmmu(t)/dtmm m then f(t.\. u(t) then u(t) is is said said to to have have an an mth-order mth-order generalized generalized derivative derivative d du(t)/dt u(t)/d
= =
Many results on generalized derivatives of numerical functions (see Appendix) can be transferred without significant modifications for generalized derivatives abstract functions derivatives of of abstract functions defined defined above. above. Recall from Chapter 1 that we have introduced the first-order (Exam (Example 2 22 1.2) and second-order Sobolev spaces H^b) H^o.ft) and ifH (a,6), er (Section 1.5) Sobolev (a, whichLare following, we generalize this conc concept areboth bothSobolev Sobolev spaces. InInthe follow )lev spaces. to higher-order if ;her-order and1 abstract abstract function functi function spaces. spaces spaces. Let Let H if be be aa Hilbert Hilbert space sp iand similarly irly define
L| u{t)(\ t ) |I ^^^ff^*)€L ((< ^^ p€ L 2€( L( 2a2a((a,b);H), ((a,6);if), ,6);if), Hm™((a,fc);ff) ((a,b);H) = == lu(t)\ {«(<)
•1 j j j = 0,1, • •• •• •m
over, introduce Moreover, :e the inner proc product W
b
- f /d?u{t) /diu(t) —^ ' ) H » ( ( . . « i H- ,V - i S i //"V o \ 3 = "maa'byH)~jr'Ja
\ d
.
<0v(t)\ d*«(*)\ .+, ;ff«. d<j
m Vu(t),v(t)eH \/u(t),v(t)€H Vu(t)^(*)eif ((a,b);H), ((a,6);if), Vu(*),«(*)€
into the H) ifHmm((a ((a, 6);. b); H), -he space H if m ((a, a, 6); b); Jf) if) defined defin. above. Then this space, H is alsoo a Hilbert space. i ace. ce.
Chapter 6
234
, &);#), Proposition 6.3. For any zu(t)^ €i ^H1a((a, b);H), /* dti(s)
J a -h /I — — ds, u(t) = a+ —7-^ds,
almost everywhere on (a, b),
wherec € (a, 6) and a e H. Proof: Let
v(t)=u(t)-j v{t)=u{t)-Jt^dseL ^dseLllr((a,b);H). r((a,b);H). For any w € H, the numerical function (v(i),w) H € L^oc((a,6)). V>€CS°((a,&)), I/
Ja
= (j
For each
{v(t),w) (v(t),w) Hp'(t)dt H
v{t)v'{t)&,w\
-(jT^yw <*-/V(<) */**&*..)_
-<-jf^»«*+jr^"*->.-Here, the interchanges of integrals and inner products are permitted since v(t) is integrable on the support of tp(t) and so can be approximated by simple functions; while for simple functions the aforementioned interchanges are permitted. Thus, for each w € H, the numerical function (v(t),w)H has a generalized derivative, which equals zero, so that {v(t),w)H equals a constant almost everywhere on (a, b). Consequently, v(t) = a€ H almost everywhere on (a, 6). 0 We finally point out the following result, which is similar to a fact wellknown for numerical functions. Let C°°((a,6);tf) ( * ) |\ f(t) :f(t):(a,b)^H C°°((a, 6); H) = { /f{t) (a, b)-+H differentiate arbitrarily many times >. C°°((a, 6); 6);H) tf lx((a, ((a, 6); H). Then C°°((o, F ) is a subspace of H Proposition 6.4. C°°((a, 6); #H)) is dense in H ((a, b); FH). i / 1 ((a,6); ).
235
Operator Evolution Equations Equations 6.2 Projective Solutions of First Order Evolution Equations
Let H be a separable real Hilbert space, with inner product and norm (•, ■)„ and || • || H f ,espectively. Let V bb e aense eubspace eo H, equipped also with the inner product and norm (•, •)v and | • \v, respectively. Then V is itself a Hilbert space. Suppose that the embedding V <-> H ii sompact, with hth embedding constant 7: (6.12) IMIir<7Mv, Vvev. (6.12) IMIH<7Mv, Furthermore, let {A(t) 11 > 0} and {B{t) 11 > 0} be two families of linear or nonlinear operators mapping from DcV toH, where D is a linear subset of V, which is independent of t and dense in V. In the following, we study the projective approximate solution of the operator evolution equation -
^^-= A(t)u(t) + B(t)u(t), at at w(0) = uuo€D. € D. u(0) = 0
*>0,
(6.13) (6.14) (6.14)
6.2.1 Initial-boundary value problem of a linear parabolic equation As an example, let us consider the following initial value problem of a parabolic equation: __
du(t,x)
= -(Au)(t,x) — (Aw) (t x) ++f(t,x), f(t x) u{t,x) = 0, 0, w(t,x) xedQ,t>0, xedn, t>o, ti(0, x€ ft, u(0, x) = u«o(x), 0{x),
xeft xeft,i>0, t>0 ft,
(6(615) 15) (6.16) (6.17)
N
where ft C R ii a bounded region wiih a Lipschitz- conttnuous boundary dfc, u0(x) € H&(Sl), and the function / ( t , x) satisfies the following conditions: for each * e [0,oo), /(t, •) € L 2 (ft), and for any T > 0 there exists a Co = C 0 (T) > 0 such that \\f(t,•)-f(s,-)\\L 2{a)
0<s,t
(6.18)
We first show how this problem can be converted to the general problem (6.13)-(6.14). To solve problem (6.15)-(6.17) in the generalized sense is to find a mapping u(t,x) : [0,00) - m(Q) such that
-(•■iL"^v,,U+(''^. V«€ffj}(n), v«€fl2(n), (»,«)La(n)a(n, = («.«o>*,(«>.
t>0, t>o, V ^. ^e f ^o ') p, , ,, < = 00..
(6.19) (6.20) (6.20)
236
Chapter 6
ue proble: problem In order to convert the above generalized initial-boundary value the (6.19)-(6.20) to the operator Equations (6.13)-(6.14), we first observe tt •iginal inner following well-known result: (Vv,Vu)L2(n) is equivalent to the original inn product ^ ' U ) W l ( n ) = (^' U ) 1,2(0) + ( V V ' V U ) i
„ •
Hence, it follows3 from the Riesz Representation Theorem that
[HS(n)Y = {eu\ 4 H =
« ^e ueV(A), P-r»/7i (i),
where the domain iflo^n) ^ O ) III| there V(A) {w u ee€ MQ{M) flo^n) there exists exists w L2(f2) such such that that Ho^n) V{A) = =
(V^,Vw) H^U,V^ttl.
v
'^(n)
"-2C")
J
We can show that 71(1) (fl) ft(l) H(A) = La(n) L22(f2) (0)
and
lX V{A) P ( 3I ) = F H0H^(Q). j0 (fl). (ft). (Q).
Indeed, for any to w € L2(Sl), L2(n), since ^ hw e€ [fl^(n)]* [#<}(n)]* there exists a w w ee iH^{U) H^{il)
such that. that
h {v,w) =
= - 00 ,
V V
It then follows from the definition of A and the fact H(A) H{A) = L22(Q) (Q) that (w,u)L2{n)=0,
WweL2(Q).
Operator Evolution Equations
237
Letting w = u gives u = 0, a contradiction. Hence, we must have V(A) = Based on the above-obtained results, we can now convert the general ized initial-boundary value problem (6.19)-(6.20) to the following operator equation problem: find a u(t) : [0, oo) —» T>(A) such that -
^
= M t ) + /(t),
(6.21)
u(0) = u0 ,
(6.22)
where u(t) = u(t,-) and f(t) — / ( t , •). Obviously, any u(t) that satisfies (6.21)-(6.22) must satisfy (6.19)-(6.20), and conversely, any u(t) satisfying (6.19)-(6.20) and also u(t) e V[A) for t > 0 will also satisfy (6.21)-(6.22). 6.2.2 Continuous-time projection methods Now, we discuss some continuous-time projection methods for the operator evolution equation introduced above (Equations (6.13)-(6.14)) [8]. We will use the same notation such as (•, -) H , || • ||#, (•, -) v and | • | v , etc. Suppose that {Vn} is a sequence of finite-dimensional subspaces of V such that VncVn^cD,
n = l,2,-..,
U?=1Vn = V
(under | - | v ) .
The continuous-time protective approximation problem associated with prob lem (6.13)-(6.14) is the following: Find un{i) e Vn such that -
^
= 4 ( t K ( t ) + 5n(tK(t),
*>0,
un(0) = Pnu0,
(6.23) (6.24)
where Pn : H —► Vn is an orthogonal projection operator, An(t) = PnA(t)\v and Bn(t) = PnB(t)\y . Equations (6.23)-(6.24) can also be written as - / ^ P >
vn}
(un(0),vn)H
= (A(t)un(t)
+ B{t)un{t),
vn)H ,
V«„eV„,t>0, = <«o,v„) H , V«n€VB.
Now, we have the following basic assumptions:
(6.23') (6.24')
,
238
Chapter 6 (Hi) For any T > 0, there is a constant L = L(T) > 0 such that I ((A(t) + B(t))u-(A(t)
+ B(t))v,w)H\<
V oi ii (z D
in a V
L\u - v\v ■ \w\v , 0 < t < T
(H2) For any T > 0 and i? > 0, there is a constant M = M(T, R) > 0 such that |<(A(i) + B(t)t)){A(s) B(t)t))*-(s) ^ B(S))V,W)HI B(s))v,w)H\ + Vv€D, \\v\\H
< M\t - s\ •■ | \\w\\ < M I HH , , weV, 0
(H3) A(t) has the following uniformly strong accreativity: For any T > 0, there is a constant Co = Cb(T) > 0 such that (A(t)u (A(t)u-A(t)v,u-v) H
2 A(t)v,u-v) >Co\u-v\l, H>Co\u-v\ v,
Vu,v€D, Vu,v€D,0
(#4) B(t) has the following lower semiboundedness: For any T > 0 there is a constant K = K(T) > 0 such that (B(t)u-B(t)v,u-v)H
2 s s -K\u-v\ -K\u-v\lv- \\u-v\\ H,
>
V « , » 6 D , 0
VweV,
0
and there is another constant K2 > 0 such that \((A(0) + B(0))Pnuo,w) B(0))P nuo,w) H\
Vt»€V,n VweV,
n == , ,l ,22-- "- . .
(F 6 ) For any T > 0, there is a constant A > ACo such that for each t € [0,T], operator \I+A(t)+B(t) has range K(\A+A(t)+B(t)) = H, where if £ = = 2,2, (r J K, f, ACo == { / 2 - * \ (2-«)/« / K x 2/« Ac„ if0 , if 0<6 1 /
Vbr)
ws
~ (T) (!f •
<22 .
<*< -
(6.25) (6.25)
It can be verified that the operators A(£) and S(<), defined by A(t)u(t) = A«(t)+/(<) introduced in the initial-boundary value problem of the parabolic Equations (6.15)-(6.17) and B(t)u(t) = 0, satisfy the Conditions ( # i H # 4 ) ,
Operator Evolution Equations
239
{He), and the first part of (H$) stated above, with H = L,2(£l) and V = therein. Choosing suitably Vn can satisfy the last part of (#5) as well, under the assumption that u0 € T>(A) (see Exercise 6.4). HQ(£1)
Proposition 6.5. Under Conditions (H\) and (#2), problem (6.23)-(6.24) i a s a unique solution, un(t), at least in a neighborhood of the right-hand side of t = 0. Proof: Without loss of generality, let us suppose that dimV^ = n. Let { a i , - - , a n } be a basis of Vn, and let un(t) = Y^=1 ^j{t)aj. Then it is clear that Problem (6.23)-(6.24) is actually an initial value problem of the following system of first-order differential equations: « / i ( t ; &,•••,£»),
(6-23")
6(0) = 6 o ,
(6.24")
t = l,-..,n,
where fifc
n 6 , • • • , £n) = ~ ^jT, ^ j=l n
(A(t)un
&o = 2 ^ Cij (uo, otj)H ,
+ B{t)un
, O,)^ ,
i = 1, • • •, n,
and Cij is the (i, j ) t h element of the inverse of the n x n symmetric and positive definite matrix [(cij, a*)]. Thus, according to the solution existence and uniqueness theorem for ordinary differential equations, it suffices to show that the functions ((A(t)un
+ B(t)un , ctj)H,
j = 1, • • •, n
satisfy Lipschitz conditions with respect to (£1, • • • ,£ n ) and are continuous in (£; £1, • • •, £ n ) on the set G defined by
G={
(t^W'^n)
f>aJ i=i
J
for any T > 0 and i? > 0. These conditions are satisfied, since for any (*; £1,' • •, £n), (s; m, • • •, 77n) € G?, if we let n
un=^TZjCtj
n
and
vn = ^ 7 7 ^ ,
(7/iapter 6 Chapter
240 then it follows from Conditions (Hi) and (H2) that
| (A(t)u )B \ (A(*Kn + B(t)u B(*Kn , aj) <^>„ B(sK n , aajj)J H - (A(s)vn + B(s)v
-vnv\ny \v ■ \\aj\ + M\t - s\ ■ • \\a \\aji\\H aj\vv+M\t-s\ // n»
^5>u£l&-*l
2
\\ V2
+M|hiij*-,i,
as expected.
Q
Suppose that we have extended the solution un(t) to the right extreme, with the largest denning domain [ 0 , 4 ) . Then, according to the extension principle of ordinary differential equations, if un(t) is bounded on [ 0 , 4 ) under norm || • \\H or | • |v, then dn = oo. Next, we give an upper bound for «„(*) on [ 0 , 4 ) . We first need a preliminary result [4]. Lemma 6.1. Let q{t),f(t), t
f^t)
be continuous and q{t), fi(t) > 0 on 0 <
1m~ g(s) " gq{t)( t ) < < 2f(t)g(t) + 2h(tW 2U(tW22{t), {t), s-»ts-»t-
0
(6.26) (6.26)
0
(6.27) (6.27) (6.27)
S —- t<
then 2 F FF 1/2 q1/2(t) (0) ^~^dr ^dr {t) < 9qV (0) •■ eeFF«W ++ f/ ' /f^r) ! ( r ) •■eFe^~ Jo
where F(t) = /„' /(s)ds. Proof: Let F 2 p(t) = q" fl\t) W d r .. {t) ■ ee-- F^ « - f /AI ((TT )) .• ce-- ^F^W
Then (6.27) can be written as P(*)
(2.28)
Since p(t) is continuous on 0 < t < h, it suffices to show that p(t) is decreasing on 0 < t < h. We first show that for each t € (0, h), p -m-^■PMzM^o. MzM<0.
s-»t-
S—t
.29) (6.29) (6 K
'
Operator Evolution Equations
241
Indeed, if q(t) = 0 then p(s)
= qV2(s) • e " F W - j
-p(t)
&
h{r) • e~F^dr
> 0,
and so (2.29) holds. If q(t) > 0, then taking a limit s —» t~ in the following equality: P(s)~p(t) s-t
I q / (s)-^q1/2{t)
=
q{s) - q(t) s-t
1 2
P-F(s)
_
W'\t)
F{s)
P-F{t)
i
j
~t
s—t
rs
Mr) -e-^dr,
s —t Jt
and then using (6.26), we obtain lim s->t~
p(s)-p(t) s-t
e-W —-q(s)-q(t) = —77777-7 lim 2(?V2(t) s->ts-t -q1/2{t)f(t).e-FV-h{t)-e-FV<0.
Hence, (6.29) also holds. Next, we use (6.29) to show that p(t) is decreasing on 0 < t < h. For any t € (0, h) and e > 0, it follows from (6.29) that there exists an rj(t, e) £ (0,t) such that p{s) > p(t) — e(t — s)
when
t — rf(t, e) < s
We can further verify that this inequality actually holds for all 0 < s < t. Otherwise, there would be a to G (0, t — 77(t, s)] such that when to — s is small enough, p{s)
(6.30)
p(to)=p(t)-e{t-t0).
(6.31)
On the other hand, for t 0 — rf(t0, e) < s < t 0 , p(s) > p(t 0 ) - e(t 0 - s). Thus, substituting (6.31) into the first term on the right-hand side of the above gives, for small enough t0 - s, p(s) > p(t) - e(t - s),
t 0 - 77(t0, e) < s < t 0 ,
242
Chapter 6
contradicting (6.30). Hence, we have p(s) > p(t) -£{t-
S) ,
0 < S
which, since e > 0 is arbitary, yields p(s)>p(t),
0<s
as claimed.
Q
Now, we are ready to establish the following result. Proposition 6.6. Under Conditions (Hk) (k = l , - - , 5 ) , for any T > 0 there exist constants C^C^Cz, independent of Vn, such that for any t €
[o,T]n[o,dn), (i)
\\un(t)\\H
(")
\\iMt)\\H
(hi)
\un(t)\v
Proof: (i) It follows from (6.23') and Conditions (Hk) (k = 3,4,5) that when* € [0,T] D [0,d n ), d
All
^ \ l l 2 ^\
o /
du
n(t) lH
= - 2{A{t)un(t)
+ B(t)un(t),
= - 2(A(t)un(t)
- A(t) (0), un{t))H
- 2 ( A ( t ) ( 0 ) + S(t)(0) > <-2C0\un{t)\l
+
un(t))H - 2(B(t)un(t)
- B(t) (0),
un(t))H
un(t))H
2K\un{t)\2-^
Then applying the inequality d? W 1 1 ab< — + — , a > 0 , 6 > 0 , p > l , g > l , - + - = 1, P <7 P q to the second and third terms on the right-hand side of the above, we obtain ! ( | | * n t o | | y < - 2 ( C o - s ) K W | 2 v + 2(A£ + 1 ) 1 1 ^ ( ^ ) 1 ^ + ^ , where £ > 0 can be arbitrary, and X£ is as defined in (6.25). Letting e € (0, Co] gives
| (||«»(t) | £ ) < (2A. + l)||« B (t)|g r + Jf?.
Operator Evolution Equations
243
Consequently, \\un{t)\\\
\\un(s)\\2Hds.
+ {2\£ + l) f Jo
Thus, by the Gronwall inequality [23] we have
\\un(t)\\2H<(KfT+\\^\\2H)-e^^T:=Cl (ii) Pick an arbitrary t e [0, T] D [0, dn). For a small enough £ > 0, let q&) = \\un{t +
ti)-un(t)\\2H.
By using the Cauchy-Schwarz inequality, we have %(*)-%(*)< = 2 ( [un(t
2 % ( t ) - 2 < l i n ( s + 0 - * „ ( * ) , tin(* +
+ 0 - Un(s + 0 ] -
K ( t ) - Un(s)]
0-«n(*)>H
, U n ( t + 0 - Un{t)
)
H
,
where s < t and t - s is small enough. Consequently, we have gg(*)-gl(*) ^ Q /dun{t
+ £)
dun{t)
.5?- ^H^f^ *2 \ ^ V - -ir' u"(<+« " uM/H Thus, it follows from (6.23') and Conditions (Hk) (k = 2,3,4) that f —S
3->J-
<=-
2 (4(t + £)«»(* + 0 + B(t + £)«»(* + 0 A(t)un(t) - B(t)un(t), un(t + 0- un(t))H 2 (A(t)un(t + f) - A{t)un{t), un(t + 0 - un(t))H 2 (B{t)un(t + £) - B{t)un(t), un{t + £) - «„(*))„
-2<[A(t + 0 + B(* + £)K(* + 0 - [A(t) + B(t)]un(t + £) , Un(t + £) - «»(*)>«■ < - 2Co|wn(< + 0 - «n(*)|v + 2 M £ | M < + ^) - U»(*)| | H + 2JT|«„(t + O - « » W | v N M * + 0-U»(t)||tf <2X£q((t)
+
2M^/2(t),
where C 0 = C 0 (T), K = K(T), M = M(T,Ci), end, Lemma 6.1 can be applied to yield q\'2\t)
< <7«/2(0) • eKt + M£ f
and 0 < e < C 0 . To this
e^^ds,
244
Chapter 6
so that T x T eAeT \\u ll^ft + £)-«„.mll„<e^ (|t« (£)-H Wn (0)|LH + ++ Mt;T) M£r). n(t + n(t)\\H<e ° (\\un(O-u nn(0)\\ IM* + £)-u 0-«n(*)IL^ ( lk(0-«»(o)|| Mfr)..
Now, dividing both sides by £ f and then letting £ -+ 0+, we obtain, by (H5), Condition (HK). (#5), rr \\dUn{t)\\ \\dUrM 1\\dUn(t)\\ 1 <*»»(«) |MM0)||II +MTA XcT( *■»(«) [I11 <e<eA.T/ <ex.r/ ||*!-(0)|| ++MT\ MT)\ IV dt y) *dt \\H L„ -dt \\LH
IIII dt A \\H ~~
^T'Tr ce*
Vll * lU VII dt \\ H
/)
(||A +B = ( ||A (0)P„«o (0)P Bn(0)Pn«o|| n(0)Pnuo\\H H + MT) = e^ (\\Annn (0)PnWo n u o + Bn(0)Pnuo\\H + MT) x T <ex*T{K2 + MT):=C2. <e * (K2 + MT):=C2.
(iii) It It follows follows from from Conditions Conditions (Hk) (Hk) (k {k = = 3,4,5) 3,4,5) that that (iii) Co\u n(t)fv< Cb|«n(«)|v^ C 0\un(t)\l<
(A(t)u uunn(t)) (t) - A(t)(0) , «»(*)>* (A(t)unnn(t)-A(t)(0), (t)-A(t)(0), (t))HH
^2^2 2^ -- B(t)u A(t)(0), u A(*)(0), = ttn(0) = // -- ^ ^ ^ B(t)unn(t) (t) -- A(t)(0) A(t)(0), , ttn(0 unn{t)\ {t)\\ = =
_ l/ ^^ ^ ^^jj-^^ w„(t)\ W„(t)\ (B(t)unn(t) (t) - B(t)(0), B(t)(0) B(t)(0) ^,l l , u B(t)(0 ,, U _ unit)} « (t)\ - (B(t)u (B(f)« uUn(t)) unnn(t)) (t))fHf nn(t)\ n(«) \ (ft /ff -(A(t)(0) + + B(t)(0), B(t)(0),u - «„«)>„
<<||*#ll ^M«)lv-'lk(«)lt + ^lk(«)IL < l\\*f\\ lll^^llll IM*)llH+ IkwlU+^kwirikwlli+^lkwllH lk(*)l|H+ifk(*)irik(*: lk(*)l|H+ifk(*)irik(*)lli+^lkw II II
ff I IIff ,
lt j l ^ 4< C1C2 -T 4- t\u>n\ £|r punn^(t)|v 4- ^^A^Gi + 4- ^*i^iGi. K\Ci. < G1G2 4e C^1 1 "T 4M ££ \ v^iv^2 ')\v 1" 1 ^G 1I •.
Let 0 < e£ < < C0.. Then it follows from the the above inequality that
M*)&<^^-t^l:=C|. The following result can be established based on the extension principle of ordinary differential equations and Proposition 6.6. Proposition 6.7. If Conditions (Hk) {k l , -•- -•, 5•,5) ) are aresatisfied, satis/led, satisfied, (k = 1, problem (6.23)-(6.24) has a unique solution un{t) (t) defined on [0,oo), 1 u««(*) V) for all T T>> 0. "»(*) n(t) € C ([0,T]; V)
then then with
We following result. vve also aiso have nave the me iouowing resun. Proposition 6.8. If Conditions (Hk) (k {k = 1, • • •, 5) are are satisfied, then then for any anj (t)} in the sequence {«„(*)} {«„(<)} of projectivt T > 0 there is a subsequence {ujn(t)\ projective approximate solutions of problem prob]em"(6.23)-(6.24), (6.23)-(6.24), such that when n n-+oo, -» 00,
245
Operator Evolution Equations «W (ii) (ii)
{«*„(<)} strongly converges to u(t) m in C([0,T);H); W „ ( t ) | strongiy C{[0,T\;h); {du {t)/dt} weakly converges to du(t)/dt in L L 2 ((0, T); H), and weak*jn {duin (*)/*} weakiy converges to du(t)/dt in 2 ((0, T); F ) , and weak*converees to du(t)/dt in L^^T^H); L~((0. T1: H): and converges converges to du(t)/dt in ^ ( ( O , T J j f f ) ; and
(iii) € [0,T], weaWy converges (iii) For For each each tt e [0,T], (( «« jj nn (( tt )) }} weaify converges to to «(t) u(t) in in V. V. We remark that we will further prove later that for each t € [0,T], (i)} strongly converges to u(t) in V. Thus, by the Lebesgue (Dominated) {ujn (t)} Convergence Theorem, {ujn(t)} strongly converges to u(t) in L 2 L2({0,T);V). ((0,T); V). Proof: (i) For every fixed t € [0, T\, since K \un((t)\ t )v| v < C 3 , there is a weakly convergent subsequence in {«„(<)}. Hence, it follows from the compactness of the embedding from V to H that this subsequence strongly converges in H. Take a countable subset {te}, dense in [0,T], such that for any 77 > 0 it set {tj I j= = l,--1, • •f •,k{r})} k(n)} satisfying satisfying contains a finite subset {tj\j sup
0
inf
l<e
\
(6.32 (6.32)
From the sequences {un{U)}, {te£)}, I = 1,2, 1,2, •••• ••,• •,•,using usingthe thestandard standarddiagonal diagonalseset£ = using the standard diagonal selection technique we; can find find a subsequence {ujnn{t)} of {«„(*)}, {«„(<)}, such that it strongly convergess within H fort = te, i = " l , 2 , - - . Thus, it follows from ||Ai„(t)/cft|| < C 2 , 0 < t < T and n = 1,2,-••, that {«„(*)} is equi-continuous on [0, T\: for any e > 0, if 0 < n r? = = 77(e) < e/C2 then |\\u | tni(t')-u n ( * n'(t")\\ ) - « BH<e, (*)||H<e,
V t*' ',,,*tt""e€e[[00,,TTJ]>,
ti '' --tit""| < |\t'-t"\
nn ==l ,l 2, ,2- ,- - .
For this 77, as described above there is a finite subset {te \ I = 1, • • •, •,*(»?)} fcfa which satisfies (6.32). Hence, for each ts[0,T\ there exists a te, l<£< l<£
I K (*)-«*„(*) I | H IK(*)-«*„(*)L IK(*)-«j»(*)L IK(*) -«^(*<)||fl++ \\u IK(*<) -«*»(*i)|U ++ \\u IIIK(*<) K (. ^(*<) ) --«*»(*)!!* -"i-wllja < ||«j -«*.(*<)! IK(*<) K < ^ „ ( t f ) | |I* ||«in(*<) -«A»(*i)|| ujm(U)\\H H + K -«*»(*)!!* ujm(t)\\H B (t) H + jn(te) jm(U) < 2 £ + jn|(t| Ui)-u -{t ^i.)-u t ,{t) e|)\\ | f Hf . <2£+ j n ( i\\u m ( jm jn <2e+\\u (t, ))\\ < 2 £ + | | U j n jm ( i , £) - ^H m ( t , ) | | f f . lerefore, Therefore, M 0 I h n W - t t ^ W H t f - O0 as ^m,n-* uniformly on on 00 < IKW-^Wll/f-* . n - * 000 uniformly < *t << TT, , W- -tttt^^W WH H tt ff - O as m,n-* T, Ih KnW ro,n-» 00 00 uniformly on 0 < * < T, namely, lamely, {w , (t)} is a Cauchy sequence in <7([0,T];#). C([0,T\;H). Consequently, there then Uj namely, is a Cauchy sequence in C([0,T\;H). Consequently, there n{t)} iss a «(t) u(t) {uj € C([0,T];ff) such that { {uWj „(*)} converges to «(<) «(*) in C([0,T]; C([0,T];tf) C([0,T];H). tf). jn(t)} {ujn(t)} of {«„(<)} {«„(*)} discussed in Part (i) above, we w< (ii) In the subsequence {«*,(*)} further {t)/dt} weak*-converges to some rp(t) ip(t) e Loo Lx ((0, H her show that {dujn (t)/dt) ((0, T);T)\H). T);H).
Chapter 6
246
Indeed, it follows from Proposition 6.1, Part (ii), and Proposition 6.6, also Part (ii), that {ujn(t)} has a subsequence, denoted {ujm(t)}, such that {dujm(t)/dt} weak*-converges to some ijj(t) e Loo((0,T);if). That is, for every v(t) e Lx((0,T);ff),
lim / T / V ( 0 , % ^ \ dt=
m
^°°Jo
\
dt
IH
[T(v(t),m)Hdt, Jo
which implies that {ditj m (t)/d£} weakly converges in I/2((0,T); if), since for every v(t) e Z/2((0,T); if), the same limit exists. Therefore, using integral by parts and Part (i) above, we obtain
-J
(u(t),yj&} dt = Jo (ip(t)Mt))Hdt, V^)€C0°°((0,T);F).
This implies that ip(t) = du(t)/dt. It then follows from the uniqueness of the generalized derivative that the entire sequence {diijn(t)/dt} weak*-converges to du(t)/dt in Z/QQ ^(0, T")5 if), and so also weakly converges to diiit^/dt in L 2 ((0,T);ff). (iii) We show that for every t e [0, T], the sequence {ujn (t)} weakly con verges to u(t) in V. Indeed, from Proposition 6.6, Part (iii), we know that {ujn(t)} has a subsequnce {ujrn(t)} which weakly converges to u(t) e V. Then, it follows from the compactness of the embedding from V to H that {ujm(t)} strongly converges to u(t) in if, so that Part (i) above implies u(t) = u(t). Consequently, the entire sequence {ujn(t)} weakly converges to n u(t) in V. [] Proposition 6.9. If Conditions (Hk) (k = 1, • • •, 6) a r e satisfied, then lem (6.13)-(6.14) has a unique solution u(t) e D, t > 0, satisfying
prob
u(t)eC([0,T}-H)nL2((0,T);V), ^GLoo^T);^).
VT>0.
Proof: By Condition (He), there exists a A > Xc0 such that for each t € [0,T], the range Tl(XI 4- A(t) + B(t)) = H. For any v,w € D, it follows from Conditions (H3) and (H4) that < [XI + A(t) + B(t)]v - [XI + A(t) + B(t)]w, >(X-Xe)\\v-w\\2H
+
2
{C0-e)\v-'w\ ,
v - W)H
Operator Evolution Equations
247
If 0 < 6 < 2, let e > 0 be such that X£ = A, so that £ < Co; if S = 2, simply let £ < C 0 . Hence, we always have
||[AJ + A(t) + B(t)]v - [XI + A(t) + £ ( * ) H L >
C0-£ 7
(6.33)
\v-w\v,
where 7 is the embedding constant defined in (6.12). This implies that the inverse operator [XI + A(t) + Bit)]"1
:
H->DcV
exists, and is Lipschitz-continuous. Now, let v (t)
= [AI + A(t) + B(t)]
-1
du(t) 4- Xu{t) dt
(6.34)
We next show that v(t) = w(t), which implies that u(t) is a solution of Eq. (6.13). To do so, let vn(t) = (n n t;) (t), where II n : V —» Vn is an orthogonal projection. It is easily seen that {vn(t)} C V is bounded: 7 C0-£
\vn(t)\v<\v(t)\v<
(C 2 + ACi + # 1 ) := C 4 ,
V t e [0,T].
It then follows from (Hi), (H$) and (H4) that
< (A(t)vjn(t)
- A(t)ujn(t),
A(t)vjn(t)
+
dujn(t) dt
< (^^-+A{t)v(t)
vjn(t)-ujn(t))i + B(t)ujn(t),
vjn(t)-ujn(t) H
+ B(t)v(t),
vin(t)-ujn(t) H
+ V \vjn(t) - ujn(t)Iy + L{C3 +
+ A„I\vjn(t) -
ujn(t)\\2H
Ci)\vjn(t)-v(t)\v.
Letting 77 = Co in the above leads to dujn(t) dt
+ A(t)v(t) + B(t)v(t),
vjn (t) - ujn (t) H
+ A c 0 | h n ( * ) - u i n ( t ) | | l f + L(C3 + C 4 ) | t ; i n ( t ) - i ; ( t ) | v > 0 .
(6.35)
Cfeapier66 Chapter
248
It is then easy to verify that each term in the right-hand side of the above belongs to Loci&T)). By multiplying an arbitrary nonnegative function (f(t) € Li((0, T)) to Eq. (6.35), and then integrating the result on [0,T], we obtain
Jo(^ Jo(^
+ A(tHt)++mv{t) mv{t) + A(tHt)
W
W
W
' '"*>^{t) - ^®) - ^H )„^ ^*
2 + / TT[ A[^c + i(C-3 L(C3 + C44)\v c o0\K(t)-u | K ( * ) jn- (t)\\ « i „ (H0 | | f f + )K(<)-t;(*)| jn(t)-v(t)\vv]
*
Letting n -> oo, by the Lebesgue (Dominated) Convergence Theorem we have
T j£(±& o ^ +MtHt)+Bm + A m t ) t) +
BitHt)
v(t)-u(t)\ + A Co («(«)-«(*)), v(t)-«(*)\
/H In
for all v>(t) € Li((0,T)) with y>(*) > 0. Consequently, / c^H^;
^ / > \ f+\ _i
T>{+\
(+\ _\_ \
( (+\
(+W
(+\
(-t\\
^ n
almost everywhere on [0,T]. Now, substituting (6.34) into the above yields ({\A CoC-\)\\v{t)-u{t)\\l>0. o-A)||t;(t)-«(t)|£>0. Since A > ACo, we have u{t) = v{t). Also, since uj (0) = />■ « 0 , letting r» -* oo gives «(0) = u0. Therefore, «(*) is a solution of problem (6.13)(6.14). We next show the uniqueness of the solution. Suppose that u(t) is also a solution of problem (6.13)-(6.14). Then, it follows from Condition (H3) and (H4) that
! I Wo-«.)|& |lWo-«o|li
- ( ^ - ^ ' <"-H
= -2<[i4(<)+B(*)]«(*)-[^(*) + B(*)]«(*), « ( * ) - « ( * ) > H <-2CoK*)-«(t)|t 2 £ Kt)-f2(*)| 2 K + 2A ee||||«(*)-«(t)||^. < -2C7o|«(t)-ti(t)|^ + 2e|«(t)-fi(*)|^ W (*)-i i (<)||^.
Operator Evolution Equations
249
Letting e = Co gives jt\\u(t)-u(t)\\2H<2\c0\\u(t)-u(t)\\lApplying the Gronwall inequality [23] to the above yields u(t) = u(t).
\\
We remark that the uniqueness of the solution of problem (6.13)-(6.14) implies the convergence of the approximate-projective solution sequence {un(t)} in the sense of Proposition 6.8. Moreover, we can show that it also has the convergence in the sense described below. Observe that Conditions (JHI), (#3) and (H4) together imply
c0\{nnu)(t)-un(t)\2v < {A(t)(Unu)(t)
- A(t)un(t),
(llnu)(t)-un(t))H
= ([A(t) + B(t)] (n n n)(t) - [A(t) + B(t)]u(t), dU
(n„«)(«) -
un{t))H
+ B U
lT " ^
^ »W - B(t)(nnu)(t), (nnu)(t) -Un(t)\
<2LC3\(nnu)(t)-u(t)\v
+
2C2\\(nnu)(t)-un(t)\\H
+ e|(nnii)(t)-un(t)|^ + Afi||(nnti)(t)-i*n(t)||Jr. Let e < Co. Then it follows from the above inequality that \(Unu)(t)
- un(t) \2V -> 0
(n -► 00).
Consequently, \un(t)-u(t)\v-+0 namely, {un(t)}
(n-^00),
strongly converges to u{t) in V, 0 < t < T.
Now, combining Propositions 6.5-6.9, we obtain the following result. Theorem 6.1. Suppose that Conditions (Hk) (k = 1, • • • ,6) are satisfied. Then problem (6.13)-(6.14) is uniquely and strongly approximate-solvable under the projective approximation scheme {Vn, Pn}: for each n = 1,2, • • •, problem (6.23)-(6.24) has a unique solution un(t) defined on [0,00); for each t>0, {un(t)} strongly converges inV to the unique solution u(t) of problem (6.13)-(6.14). Moreover, for any T > 0, u{t)eC([0,T\;H)nL2((0,T);V),
^eM(0,T);tf).
250
Chapter 6 The next theorem gives an estimate for the convergence rate [8, 15, 37].
Theorem 6.2. Suppose that Conditions (Hk) (fc = 1,■ • • ,6) are satisfied. Then there are constants C,r] > 0 such that between the solution u(t) of problem (6.13)-(6.14) and the solution un(t) of problem (6.23)-(6.24), we have +T UU U U U II\UlM ~~UnWnIlL((0,T);tf) I lL((0,T);/f)+r + M~-\ - AA\l2li((p,T);V) IlL((0,n/J) >\\ ((0,T);V) 2((0,T);V) rfn 112 112 r .|2 112
C U I I Vn I
L
~ \ ~ + +
yH
~fT ' )+
I li>oo H^?-* />■" /
U Vn
b^-^IL((0,T,^,}' h^-v4L2mTyJ>
'
.|2 .|2 L2((
°' T); V) )
-L'2VV^»-' )i*
V«-(*)€K, Vt^WeK,
where vn(t) {t) € Loo((0,T);ff) Loo((0,r);H) n L ((0,T); ((0,T);V) V) and dv (t)/dt wherevn(t) € Loo((0,r);H) n L 22 ((0,T);V) and dvnn(t)/dt Proof: It follows from (6.13) and (6.14) that Proof: It follows from (6.13) and (6.14) that ^ u « ) - « n ( « ) ] > 1 B ^ + < [ i l ( t ) + B(t)]tt(4) _
=
[il(t)
(6-36) (6.36)
€ L2((0,T);F #). € L2((0,T);#).
+ s ( < ) K ( t ) )W)^
{dHt)7n{t)\^)H <[A(t) + B(t)]u(t) - [A(t) + B(t)K(t) B(t)]un(t) ,w-w + <[i4(t) B(*)]ti(t)B(t)]«„(t) ,,ti; t«u;--nu«)w n))H w;„B w ,
>r all allw w €€ V V and andall allw„ wnn € e KJ. V Letw iu== u(t) u(t) ——uunn(t) (t) and and w wnnn == vvnn(t) (t) —— wwnn(i), (t), for w €V w; n.n. Let r where here vn(t) can be any any function that satisfies the properties stated in the theorem. Then W ( (t) + AAA U U W (( tt )) W t) AA W - Un(t)) Jt ~~ l «" ++ << \\2 A Jt IHH' WUU(t) (*H*) ('K(*) (t) «»(*)>„ C) ~-- W»(*)) «n(*)> HW ~ U ""( t )lll« H < (*H<) ^) (*) -- A(thn(t) (*K(*) ,> >U(t) (*) w
Mn(t)) + (B(t)u(t) - B(t)u u(t) - uo„(0) „ B{t)un(t), u{t) n(t)> w H /d\u(t)-u(t)] W U J \ m = rft
-\ -X£\\u{t)-u (t)\\22HH £\\u(t)-unn{t)\\ < ^>-**™ ( d ^ 2 + L,
t
^ \
2 u(t)-Mt))H u(t)-v u(t)-Mt)) e\u(t)-un(t)\l e\u(t)-un(t)\l +e\u(t)-un {t)\ v +n(t)^H+
.22 ^Ht)-vn(t)\ v.
.
Operator Evolution Equations
251
Let e < Co/A. Then d 2 dVlu(t)-un(t)\\ H^C0\u(t)-un(t)\l < C'{\\u(t) -un(t)\\2H
+2
-vn(t)\2v)
+ \u(t)
d[u(t)-un{t)] dt
l
-y
u(t)-vn(t) H
where C" = max{2A £ ,L 2 /(2e)}. Multiplying both sides by e - 6 "* and then integrating it from 0 to t < T, we obtain e-°'*||tt(t) - « » ( t ) | | ^ - ||«(0) - « „ ( 0 ) | | ^ + C 0 / e-c'a\u(s) Jo
- un(s)\2
ds
\u(s)-vn(s)\2ve-c'°ds
f Jo
+ 2 [<«(«) - wn(s),«(«) - »„(*)) H e- c ' s ] *~o
-2/'{(^)-„„W,*(fl__M£)!J% -C"(w(s) - u „ ( s ) , u ( s ) - v „ ( s ) ) H e " c ' s > ds < IKO) -
Wn (0)
2 e ^-C't I& + H O ) - vn(0) \\% + e \\u{t) - «*(*)!&
+ 2 7 2 e /* \u(s) - un(s)\2ve-c'° Jo + C'(l
+ ^ - \
i;
1 f \\du(s) ds
ds+-
e
\\u(t) -
f \u(s) - vn(s)fv e-°'s dvn(s) ds
e~c's
vn(t)\\l
-C't
ds
ds,
H
where, we have applied the Cauchy-Schwarz inequality and (6.12) in the last step. Thus, if e > 0 is small enough, by using
IKO) - un(o) \\H = IKO) - pnuo\\H < IKO) - vn(o) \\H,
Chapter 6
252 we obtain, from the last inequality,
IK*) - un(t)\\2H + ^ r < jL-
1
j f e~c's'u(s) ~ Unis)&ds ■***
|| tt (0) - * n ( 0 ) | £ '* + j
^
\\u(t)-vn(t)\fH
£ ( ' ♦ ¥ ) jf !■<•>-<•>&■ +
1
r*||du(s)
3e^T 1 - e ' s (T^)\ l-e)
+l-e ec'T
e(l-e)
1
BC'('->«i8
ds
ds
l-e)Jo
H^'^H^ao.nH)
+ ^ 7 - j eC'THU " du dvn ~di~~dt
V
»\\la({0,T);V)
L 2 ((0,T);H)
Prom this, the constants C and 77 > 0 defined in (6.36) can be found.
\\
6.2.3 Discrete-time projection methods In this subsection, we suppose that all the assumptions such as Conditions (Hk) (fc = 1, • • •, 6) imposed in Subsection 6.2.2 are satisfied. Let At > 0 be the time step size, M a positive integer, T = Af At and t m = mAt (m = 0,1, • • •, M). Let also t m +* = 0 t m + 1 +
{l-0)tm
and vm+e = 0vm+1 + (1 - 0)vm , where m = 0,1, • • •, M — 1 and \ < 8 < 1. Then, the discrete-time projection approximation problem is to find w^, tz*, • •, u^f in V^, such that
253
Operator Evolution Equations Equations
At
-<_ = A (tm+e)u™+e n
+ Brl(tm+0)n^+e, (6.37)
m = 00, ,l l, ,--. .. .. .M M--l l, , uu°0nn = PnPun0u, 0,
(6.38)
or
- {^^-
-)H - (M^x«+*
« >„w = (no, t, n ) H , = <«<>.«»>*.
*>.,
m = 0,l,---,M-l,
(6.37') (6.38')
V vt>„ n € V„ ..
When 0 = 1/2, the above formulation gives the so-called Crank-NicolsonGalerkin approximation scheme; when 0 = 1, it yields the well-known backward difference Galerkin approximation scheme. We next establish the existence result for the solution of problem (6.37)(6.38). Proposition 6.10. Under Conditions (Hi), (H3), (HA), and (H5), for sufficiently small At > 0, problem (6.37)-(6.38) always has a solution. Proof: Using mathematical induction, it suffices to show that for a given < \ 0 < m < M - 1, when 0 < At < 6, equation w = u™-At u™ - At [An(tm+de])
m+d + Bn(tm+e )} )]
(6w (Ow ++ (1 (1 -- 0)
has a solution in Vn, where 6 > 0 is a fixed constant, independent of Vn. To do so, define a parametric mapping 5M : Vn -> Vn by m e (? TO+ «™ - M/.At At [A )]*)] (6w S^w = < [ ^n(t(tm+ +) ) + Bflnn(t(im+e (Ow++(1(1-- 00) )<<) ) ,,
u;«;€€ KK . .
It follows from the continuity of An(tm+e) +Bn(tm+e) that SM is continuous in (JM, w) € [0,1] x Vn. Hence, by the Leray-Schauder fixed point theorem, Theorem 4.15 in Chapter 4, it suffices to show that all the fixed points of SM (if exist) are uniformly bounded. Let w e Vn be a fixed point of S^: w = S^w). Then by using Conditions (Hi), (Hs), (Hi), and (H5), and the Cauchy-Schwarz inequality, we have
Chapter 6
254
\\w\\ (SliwMH HI*2H==(-V^)* = w)H - MnAt {[A(tmm+(e>) ) + + B(t B{tmm+*)] +d)] (fti; (6w + + (1 (1-- «* )) << )) = « \ «;)„ At <[A(i m+f? ro+e - [A(t [,4(tm+e )) + B(t B{tm+6)] )}
-
Ati M MA
m+S
( [A(t [^(t"^) )
m
e
-[A(t + )
(1 - « 0 ) < ,>W) ™) HH m+e m+$
+ B(t m
+
)} )]
(1 - 0 ) <
e
B(t + )](0),w)H
m+e
+ B(tmm+ee)}(0),
f,At ([A(t ) - M At ([^(t"**)
W)H u;)^
< |\ I K I I H + | \\w\\2H-9»AtC\\w\\]!-^teCo\w\l+evMK\w\l< +OnAtK\w\l-ss\\w\\ \\w\fsH 0\w\l
+ \w\v+vAtK + /zAtL(l - 0vAtL(l-6)\uZ\ ) | t C | v M v v+ ^AtKx1\\w\\HH
^l\\<\\2H+I%rlAt\
+
^At
+ 1 ( 1 + 2Ae0At + A t ) ||«,|& - ^0AiA*(C„ A t ( C 0 - 2e) |«/| |«/|*2 . Let e = C 0/2. /2. Then for 0 < At < 1/[2(1 + 20A£)], the above inequality yields
\M%<2\K\\l+I+^^At\u-\l \n\l<2\\u':\\l ^^At\u-\l
2
2K At. + 2K^At.
o
We next give an error estimate for the solutions {<*} of problem (6.37)(6.38) as approximations of the solution u(t) of problem (6.13)-(6.14). Theorem 6.3. Suppose that Conditions (Hk) {k = 1, •••,6) are satisfied. Let u{t) be a solution of problem (6.13)-(6.14) and {<*} be solutions of problem (6.37)-(6.38). Ifu{t) has a second order generalized derivative with respect tot with du(t)/dt e Loo((0,T);F) and cPu^/dt2 e Lo o ((0,T);if). Then for any B e [\,1], there exist constants rj > 0 and C > 0, depending only on C0, K, L, T, such that M-l
0<£f<M l'W r
Wn
M-l
Nff
^ £^0
~Un
'V M-l
2
< J|K-^(0)|| H+om^M IK-CI&+ M£- l K--<-| 2 vAt C
~ ~ < c {*-^| K - II^ (0Wm+S ) | | 2_Hv m + +o ma, | | « » -_Cvm-l+6\ | | i + ro=0 £n2 K ^ - C l ' v * ^ _ Mrm-l+e k
~
~
+ ^22 IIp( ™+* _ m+fl\ 2—^—^ _ ( m-l+e = l 'Ip A + m2J 2—Z—A^ w
lld2wll2
v
u
/ » ^2
lldull2
1 »
_ vm-l+6\
m=0 ||2 I Iff
L\\ At L\\ A^
/A
v2l
(6.39)
255 255
Operator Evolution Equations Equations
and for 8 = 1/2 and u(t) has third order generalized derivative with respect to t, with du{t)/dt, d?u(t)/dt* € ^ ( ( O . T f c V ) and #u(t)/dP €
LooftO.T);*), m
M-l
r o++11//22 og&i OSM lh IK-^II^+^Eh -
2
-
m=0
= + =—y =——1AtL +EE-—=—y— ll^wH2 / A ^ 4 ll^wH2 /A,N4l 4 V II d ^ llL<x>((0,T);H) II dt2 NL«„((0,T);V) V J II dt-1 llioo((0,r);ff)v Ndt2 llL,„((o,r);V)v J +i m
(6.40) Hl&lll ,„ , j * H l £ l l l ,„™<*> }- (6-40» where
<€K,
m
u«•» = =
u(tmm), u{t ),
«r=^ +(i-«K -
m+i wmm+* +* == 0u 6um+1 (1 -- 0)« 0)«mm .. ++(1
W
Proof: Let du(t™+°)
Urn+l_um
** dt At dt At e™ e™ =«(*»»+*) = tt(t*»+«) -_«"»+*. ™+* . w Then it follows from Eq. (6.13) that
/ t«t Tmn++^^ - «t t r"o, ))
w
e l e m e \ == _([A(t'"+ + £ r o 1),), -([A(iTO+<') ) ++S(t" S(t"+l + e)]( )](WU " l+ ( '+e"
-(f\™>H. -<£ ,«»>*,
VweV, VweK,
)
WW ) HH
m= 0,l,---,M-l.
Rewriting (6.37') as
/<+^-iC)
\
+
([^( t ™+*)+ i? ( f ™+*)]<^,
^
TO+e m e m+tf fl = ("^7"", / < + ^ - < , w-u; +<[A(« )+S(t +')]ti™+e)]<+ , = «;-«;„\ +<[^(t )+B(t-+ , w-w )ff n\ n)H ffi-%
V twoeeVF , WnCVn, w„ey„,
= 0,l,---,M-l. m=
,,
256
Chapter 6
Let
zz™+e ^ == um+e_um+e u™+e_um+e
Then, a subtraction of the he above two equalities yields the following: /1 yym+l m+l n
_ _zzm m
\\ W W
\\
" A* A* " ''' l)/)HiH " A* H m+0 m+0 m 00 mm+e m+e m+e m+0 0 )]um+e + ([A(t ++)]u )]u + ([A(t )) + B(t B(t'tmm+0 )}u
m+e m+0 -- [/ [A(tm+e ))
/ zm+l
n (r,w-w == -(C,w) -(rM + (r,U>-Wn) (r,u>-w ))HHH) + + ({ ^ w - nw + " H H H + n H
n
^ ^
m e m+0 + B(tm+0 +)]u™+ )]u™+00e0,, W) W)HH
_ zm n " ,
\
n , w-w W-W ,W-W nn\)\ n
mm +*)](u(umm+0 + e + e m) - {[A(t m+e ) + £(t(t +*)] m+0 m m+e m+0 -[A(tmm+0 +0))+B(t+ + B(t )]umm+0 +00)]u , m+d , m+e m 0
m+0 mm+0 0
+ {[A(t ([A(t +))
m m+ee m m+0
W)HH m
+ + B(t[t+ )])])](u(u + + e ) +e )+
m+0 0 +e +0 0 m+0 m+0 --[A(t [A(t+ +)+B(t [A{t ]) + + B(t )]uZ )]u™+ ,,w-w , n)w )]u™+ H. - wn)H . m+e m m 0 0e
(6.41) (6.41 (6.41)
Inn this lis equality, let w == z™+° z%+ z™+060 and wn = = v™+ v™+00 - u™+ < u™ + *+00... Then using Conng Con ditions litions ns (Hi), (H (H^, (H (H4),4A), ), as well as the t Cauchy-Schwarz Cauchy-Schw inequality ity an and t), (H3), and (Hi), Eq. Cq. (6.12), (6.12). 6.12), the left-hand side (LHS) of (6. (6.41) gives ++1+ m+0 m+0 m+0 m+e n m+e Z+1 r22~n+Z™ +eA + m+0 +e m+d m+d m+e L \-~+1 zrn t ^B{t LHS HS= = //ZZZ™ n™ zm+e\ ™+A {[A(t +°) ) ) + B ( B(t +°)]u )]u - +e + ([A(t B(t )]um+0 +e\ AAA ~~ZZ™ zZ )) +/rA(t"*+«) LHS = ^™"L ,,, ZZ^n *Z + ([A(t { V mm+0
m+0+0 +0 +e +e m+0 m+0m+0 m e 0e m+0 m+a m+a --[A(t [A(t +)+B(t ) m+0 +B(t )]u™ )]u™ ,,, 't+mm+d )+B(t )]u™ , , +a ) )]u™ ))+B(t + B(t )\u™
+e <<*+°) z™ * ++0 % )HH
^(n i i ^^ni iii-^i k - i iiiy) -+ ^ - ^ i i i k ^ - c i iII22 , , i0i"y0'6\l-%r% 0i i c , ^ 2 0+ -D^ii^-cia + \+C^ + c b |CCCQt\z^ |\z^ v \l-K\z^ - ^\l-K\z^ C w l v\\: H '|li o
1 ^ | C i| iyy - + ( Ceio)k"-& -el)k-|2v ^(ii^ ^ ((l ikim^i+i&-iKiiy+(cbi Hi i2-, -i|w ^(H^iii-iKiiy+ccb-oKriv
Nii-ii-ciiy+^-eoi^it +e 2 -^\\*n \\ H, -VllC+'HL, -VllC+'HL, -^IIC+'Hlr, -Mkrnitf. 9 2
(6.42) (6.42) (6.42 \\ H, (6.42) for or some side ome le constant constant ei ei >> 0. 0. On the the other other hhand, hand, the the the right-hand right-hand si side (RHS) (RHS) oof LHS) of of 0. On (6.41) 6.41) 1)) becomes becomes mm ee 0
m+1 _
+ / ^
m
bi. f „™+<> _ *i
m m0 0 0 m 0 m & mm 0 m+0 0 m 0 m (\A(t ++)+B(t )}^+B(t (u --([A(t ([A(t ) ) ++B(t )}(u +m+0 +)}(u ++ +e >+ 90)} )}(u e m)) m+0 m+ m+0 m+0 m+0 m+0 m+0 ) ))+B(t ) + )]u, , --[A(t [A(t \(t + m+0 B(tB(t )]u )}u
Z™+ ZZ+09)H
Operator Evolution Equations + ([A(tm+e)
257
+ B(tmm+a +9)](u )] m+e (um+e
m+ee m - [A(t [^(tm+( +')))
+e B(tm+e)]uZ , + B(«™+*)],C+*, )]iC+°,
<\\r\\2H+\\\u™+° — ii-
,,
mi
111
/ ~m+l _m z // zznn ~ ~ z nn ,,
\
\
At e At
+ L\zZ+ L\z™+
m+e rn+0 uum+e
' m+e
'
■"
m e(> um+e v%+ee)H + - v™ vZ+
-vz+%+\\\zr% iiia
MJ
2
*
\ __ v^^m^6 m m+ + 00 \\
n
n
m+e + me\mv\u \v\u +e -vZ+e\v-
e
+em)
4
lHL
+e
v™ \v +
m e L\e L\e\mv\z™+ \v\zZ+e\v
^llrlt + ^ i + ^ r t + iii^it+^ias^lt ++1MK t (ii+£)+^]i«"*'-***•& + -"l+i 2 ll» m +.-<+*£ m+++lll _ _ m / _mm
\
+e \ .»+*_„,»+« (643) m+e m + - v™ + \/( Z " A *" ', w«U™+* (6.43) -vZ + ' - «+e») + ' )) t,, (6.43) IH \\ A t IH At /ff > 0. Now, by >y combining (6.42^ (6.42) and (6.43), when both for some constant e2 > et and e2 are small enough, we have ave ei 2
+ (l-CsAt)\\zZ (l-C %-(l 5At)\\z^\l-(l
t-i
A,Ml.m||2 +i ^ CC5C At)\\z: 5At)\\zZ\f 5At)\\z™\t H
2(C0-e1-e2)At\zr$\2v
+ 2
m 2 + \ v2 + \ u ^ + \e \e™\ v+
2 \u^-v^\ -vZ+v]t]
2 m+ e 9 1 + e +e -^-At\\zZ\\ -^A -|+2(zZ | |2| |2HiH++1 ((z^^r+1+1 --z% )>6H,),H,, A tt | || |^, HC ^-# ^, ,., ^u^« »+°+ -« -C< +-vz *-vr ++ 222<
> 0. Multiplying both sides by [g( [g(At)] for some constants C5 > 0 and C6 > [g{At)] m" 7/ ( 1l ++ Cs5At), At), with g(At) g{At) (At) := (1 - C 5 At)/(l + C 5 At), and observing that that there are constants C > 0 and C" > 0 such that, for small enough At > 0, constants G" > 0 and C" > 0 such that, for small enoug mm m C <[g{At)]
m m= = 00 ,,ll,,,,.-. .- ,
we obtain
r+1n*rii&-fcr(At)]miicii2„+^|zjr9iv 22 ^^^[HrllL ^ [ H r l l L ++l^lv l^lv++h^-^lvl-CsAtiicll h^-^lvl-^tHcll , , m+1 2 m +1 H 1 2 [|_JA'+' vAt | C "9 | vv fcl [ 9»(At)] (A t ) ] m\\z^\\ & - f-c r[g(At)} ( A t ) ] m\\| |z|-\\l C „ + VJ | ||~| n« r | H/f L»V-"VJ | ~ |n| \\H '^ ' "| "zr {n r | IV
rilAml|2
, I ml2
. I m-\-0
-.m+012 1
A-tll^m||2
/^
2
m m+e e + + Cc55At At ^^"r ++ 11 -- z*™ ™'' k[am] + li + ( A ' ) ] m {u ( « m + e "- v™+ ™ ) > H))' H, V
+S
,C 88. Summing the above inequalities over for some positive constants 7?,C J7,C77,C* m gives «-i e-i
[giA^WziWl + ^ ^ t A t [.(At^iKiii+^EKr+^At m=0
258
Chapter 6 m+e e 2 < KWl \K\t + + CrT, C7T [\\r\\ \ llr2HIII + + \e \emm\l\l + + \W < u ^ - v r\tC+'l* l v} At1
^IKIIi + cvi:[||r||i + rt + |«^'-«^| ]At
At
m=0 m=0 £-1 £-1 £-1
e-i £-1 £-1
9 9
-c s^n HAt+YTd-Ki^+ T T § ^m=0 -c,£|K-||> £ m=0 m=0 m=0 m=0 + +1 1
5 & &
m t f m=0++ 8 [ s ( A i ) ]m ( ummm+++'-t;™ - t C+ *)) )) m (u [9(At)]
(( zz ™ ™ + 1 -- zz ™ ™ ,, [ 9 ( A t ) ] ( u
,,
'-t;™ *))
(6.44) (6.44)
for £ = 1, • • •, M. M. Summing by parts the last term on the right-hand side of of (6.44), and d using the Cauchy-Schwarz inequality, we have (6.44), and using the (Jauchy-Schwarz inequality, we nave e-i £-1
E ( r - C ,-zb ( A * ) ] m (V" ^ - C-+ s") n> H ) l^V-n n,\y\^)\
m=0 m=0
/
H
1 1+t 1+9 = «*-<)„ = <4, « , hi*t))'[
-^(c[#)] m r-r) ro=l ro=l
1 mm ,+ -[g(At)]mm-1-(u -[g(At)} (u-^-v--^)) -^-v--^)) H H -[j(A*)]-'(«"-'+»-»r *)>„
m 1
m
2-[g(At)] - (u -^-v--^))e H1 e l i+# < P o l M | l 2, + ^ | | [ , (-A <-||4|| t ) ] - (- u(,-l --+-e-,f<^ - 1-+)eU\* ||i i.-L\\UM\\ t i e 1 e <eMA\\l +— \\\a(AtW - (u - + -vi-1+0M\l
^ii4iii+in^)r(^-^ 1
,
1
-*"
! II^0I|2
, 111 0
fl,|2
, ^
)iii
1
1 ^ - !
V^ll«m||2
A +
,
1
V^
m==l l '4 m
m=l m=l
1 m A t )m]-i(u ™m-"1+° ^ - ^ - << - -1 +^ g )) ||II22 ||II [[g(At)] g ( A f m) ](u™+ ( ^ +e g - < + *g ) - ^\0{At)]
II
||H '
At
for some positive constants e3 and e4. Now, substituting this back into (6.44), and using a new constant x\ 77 > 0, for small enough e3 and e4 we have e-i m=0
f n ni.2
2
ii
a
/3ii2
2
li
*_i_i_/>
^ u / ) i i 2
+ 2 E[llrHi +++ 2J E[lirni +|«"r, +l«™«-.r»lt]A* +k"& +l«™ 11^11^ +lOv + l -'-»r»i ^ - ^ r Tv]A< v At m=0 m=0
+ EE + £ fFF m= m = ll I'
—
^~±£I" —
- 2—— ^- /AtAtV}> V '^66-(45645)-45 \\H I Iff
J )
Operator Evolution Equations
259
for lor some some constant constant Cg Gg > > 0. 0. Now, it it can can be be observed observed that that when when du(t)/dt du(t)/dt € € Loo((0, Loo((0, T); T); V) V) and and dd22u(t)/dt u(t)/dt22 Now, Loo((0,T);ff), Loo((0,T);ff), we we have have
ll^ll
II s
and
llff-^
,7/2 at II ^flT; II at
llLoo((0,T);ff) llLoo((0,T);ff) Mi>oo((0,T); llLoo((0,T);ff)
Lml ^||M0|| le-l^cll^ll II ^ IlLooCCo/rjjv IlLooaCTjjV) <
II UL^ao.Tyy) ii "* «* iiLooKo/njv) while when ivhen < 09== 1/2 1/2 and anddu(t)/dt, du(t)/db, du(t)/dt, o9u(t)/dt o9u{t)/dt (Pu(t)/dt (Pu(t)/dt222 ee Loo( L^ Loo((0,T); ((0, T); V) V and
lllrlU^II^H l r |l|L„ < c | | ^ | | nuse||^|| II
ai a i
(At)* (Atya (A*)
\\Loo({01Ty llLoo((O %H) IlLoo^T);^) fT);Jf)
and
l
£ m
OT | v ^ II| | OT ^ | IlLooCCO^); |IlLooaO^);^) OT IlLoottO^V) II OT IlLooaO^);^)
^
where C > > 0 is a constant. Substituting then into (6.45) and rearranging terms, we arrive at at ^o.c^yj (6.39) ana and (6.40). [] lerms, we finally nnany arrive ^o.4uj. 6.2.4 Initial-boundary value problems of nonlinear parabi parabolic equations In this subsection, we illustrate by an example how the computational framework established above can be applied to some initial-boundary value problems of nonlinear differential equations. Consider the following initial-boundary value problem of a nonlinear parabolic equation: paraoonc equation: H a J2 ~-^= - ^HD ' "a£ 'A^a(x,Pu), "^a(*,Pu), ^(x.Pu), -757= S 5 3 ((-l) (-l)
>0 x e€ ff ll , t > 0 ,,
(6.46)
|a|<m |a|<m
( Daaa% x , t )y = (D u)(x,t)=0 (D u){x,t) =0 0 (i? u)) ((x,t) 0,,, w(x,0) = w ( x ) , u(x,Q)=uo(x), 0 u(x,Q)=uo(x),
xedQ, xedQ, x€<9ft, xxett, eft, xett,
t£ t> >> 0 00 ,, || aa || < <m m -- ll ,,
(6.47) (6.47) (6.48) (6.48)
where Q 11 C R i ?N^ is a region with a Lipschitz-continuous boundary dQ,, a = («i, • ••,•,ajsf) aajsf) AT)isisaamulti-index multi-index satisfying satisfying a\i -f 0 < \a\ := a
a^ <<m m,, h\- a^v
e e
Chapter 6
260
and
Pu=[D*u\0<]al£m, in which there are s components of Dau arranging in an appropriate order. Suppose that Aa(x,£) is a function of x € Q, and f e Rs, satisfying the so-called Caratheodory condition: for any fixed f € f? s , A a (-,£) is measur able, and for almost all x € ft, Aa(x, •) is continuous. Assume also that for any u e H™(Q), Aa(x, (Pu)(x)) € L2(fi)- Finally, for simplicity of notation, we only discuss real functions and real spaces etc. To this end, the generalized Dirichlet problem of (6.46)-(6.48) is to find a u(t, •) G HQ1(Q) satisfying
-(^,v\=a(u,v)
+ b(u,v),
<«,«) = (t*o,v>,
V ^ W ) ,
VveH™(tt)y
t>0,
(6.49)
t = 0,
(6.50)
where (•, •) is the inner product of L 2 W , &nd
<*(«,«) = £
<^ a (.,(P«)(.)), (/?-«) (•)>,
|a|=m
6(«,«)=
£
<^(.,(J>«)(.)), (z>V)(-)>-
|a|<m—1
Let H = L 2 (fi) and F = and b(u, •) are bounded linear well known that the dual space subspace of the dual space V*. ff~ m (ft), under the norm |M|_m =
^ ( Q ) . Then for each u e V, both o(w, •) functional on V\ On the other hand, it is (l/2(^)) («-e., space 1/2(0) itself) is a dense Moreover, the completion of Z/2(^)» denoted
sup
|(v,w)|,
ueL2(£l),
IMIm
is an isometric isomorphism of V*, where || • || m is the norm of space Hrn(Q) defined as usual by r
rn
IML = EK
2
x 1/2
•
with |«|i= E ( ^ ^ )
x 1/2
•
Based on this, we introduce two operators A and 5 , both mapping from V to if, as follows: For every u e T>{A) C V, there is an Au e L2(ft) such that a(w, v) = (Aw, v ) ,
v 6 V^ ;
Operator Evolution Equations
261
and for every u € V{B) C V, there is a Bu € L 2 (Q) such that (Bu,v), b(u,v) = (Bu,v),
v €v€V. V.
In addition, we assume that V(A) is a dense linear subset of V, and V{A) C Thus, problem (6.49)-(6.50) is reformulated as an operator equation problem: Find u(t, •) € D := P(A) such that -^^-=Au(t,-) - ^ 2 d = Au(t, •) + Bu(t,-), flu(i, •),
tt >> 00 ,,
(6.51) (6.52)
u(0, u(0, •) = ««,(•),
namely, a solution of problem (6.51)-(6.52) is a solution of problem (6.49)(6.50), and so is a generalized solution of problem (6.46)-(6.48). Let {Vn} be a sequence of subspaces of V satisfying VncVn+1 VncV (cD), n+1{cD),
nn == ll,,22,,------,,
V™=1=1V„ Vn =— V. V. U~
Then the continuous-time Galerkin approximation problem is to find un(t, •) € Vn such that (^£,Vn)+ (^T>Vn)+ \
M M
£E
I
\a\<m |o|<m
aa (Aa(;Pu (Aa(;Pn n),DvV n)=0, n),D n)=0,
( Un , Vn) = 0, vn), , (ttn,»») = (u («0,^n)
Vv„el4, V«„€Vn, Vv V VneV n €n, V n ,
*t > 0 , t< = 0. 0.
(6.53) (6.53)
(6.54)
The discrete-time Galerkin approximation problem is to find uen e Vn such that
/ ^ r At f ^ , ^ \ +
\
Y.
I |
(Aa(;Pui+°),D°vn)=0,
€ = 00, 1, !, ,■-■• ■• , M --1l ,, VvneVn, v v e y„.
l|a|<m \\a\<m < L\u-v\L\u-v\ < m\w\m,m\w\m,
I V
u,v,w€.V. Vu,v,w€V.
(6.55) (6.56)
Chapter 6
262
(ii) There is a constant Co > 0 such that (Aa(;Pu)-Aa(;Pv),Da(u-v))
J2 \a\=m >C0|ti-«|m.
Vti,«€V.
(iii) There is a constant Ko > 0 such that
J2
(Aa(;Pu)-Aa(;Pv),Da(U-v))
\a\<m-l >
~ K0\U
- vlmWu - vWrn-i
,
Vu^veV.
(iv) There are positive constants K\ and K^ such that
J2 (Aa(;P(Pnuo)),Dav)
V*;eV,
n>\,
\a\<m
£
(Aa(-,P(0)),
Dav)
VveV.
|Q;|71
Then we have the following result. Theorem 6.4. Under Conditions (i)—(iv) stated above, for a fixed UQ € D, the continuous-time Galerkin problem (6.53)-(6.54) has unique solutions {un(t, #)}. Moreover, this sequence of solutions has the convergence de scribed in Proposition 6.8 with the limit u(t, x) being the unique solution of problem (6.49)-(6.50), and has the approximation error bounds given in Theorem 6.2. On the other hand, the discrete-time Galerkin problem (6.55)(6.56) has solutions {u^}, which satisfy the approximation error bound given in Theorem 6.3. Proof: The spaces H — L<±{pL) and V — B^i^l) both satisfy the required separable and reflexive properties and the compactness of embedding. Since A and B are independent of £, Condition (H^) is satisfied. Conditions (i), (ii) and (iv) together imply the Conditions (ffi), (#3) and (H5) stated in Subsection 6.2.2. Thus, it follows from Condition (iii) and the intermedi ate derivative interpolation inequality in Sobolev spaces that there exists a constant K > 0 such that (Bu-Bv,
u-v)>
-K \u - v\^m\u
- v[
which implies that Condition (HA) is also satisfied.
\/m
u,v G D,
Operator Evolution Equations
263
What is left to verify is Condition (HQ). For this purpose, introduce two operators 1\ and T 2 , both mapping from V to V*, by the following: (v,T±u) = a(uy v),
V *x,
v£V,
(t/, T2w) = b(u, v),
V u, v € V,
where (vyTku) is the value of Tfcix at v £ V, where Tku € V* and k = 1, 2. Also, let I be the identity operator from H to H restricted on V, namely, for any u eV, Iu €V* and for every v € V the value (v,Iu) is equal to the inner product (v,u) of L 2 (fJ). We first show that the range R(A/ +
1 / 2 r a - l \ 2 ™ - i / i f \ 2m A>i(££!)-( m \ Com ) V2 /
T1+T2) = V.,
Indeed, for any w, t; € V, it follows from Conditions (ii) and (iii) that (u-v,
(AI + T i + T 2 ) t * - ( A J r + T 1 + r 2 )t;)
>(\-\e)\u-v\l
+
(C0-e)\u-v\*n,
where e > 0 and 1
/2m-l\2m-l
/]fx2m
m V Em / \ 2/ Let A£ = A. Then C0 - e > 0. Hence, A/ + Ti + T 2 : F -► V* is a strongly monotone operator. By Condition (i), we have |(ti/, (T1+T2)u-(T1+T2)v)\
V t*,«, ti; e V .
This implies that operator T\ + T 2 is demicontinuous, and so is operator XI + T\ -h T 2 . Thus, according to the theory of monotone operators (see Chapter 5), we have K{XI + Tx + T2) = V*. We next show that U{XI+A + B) = H, where I: H —> H is the identity operator without restriction. It amounts to observe that for any w € H, from what has been proved above we know that there is a u G V such that (v, (Ti + T2)t*) = (v , TI/ - Xu) ,
V v € V.
Hence, by definitions of operators A and B we have AIA -h Bu
= w — Xu,
u € JD,
namely, 1l{XI + A + B) = H, and therefore Condition (#6) is satisfied.
Chapter 6
264
As a result, all conclusions of Theorems 6.1, 6.2 and 6.3, as well as that of Proposition 6.10, hold and so can be applied to the present case. Finally, similar to the proof of Proposition 6.9, using the Gronwall inequality it can be easily shown that the solution of problem (6.49)-(6.50) is unique, so that the solution of problem (6.51)-(6.52) is the unique solution of problem (6.49)(6.50). D We remark that actually the restriction of UQ G D and Vn C D can be removed. Problem (6.49)-(6.50) can be directly discussed by following the track of Sections 6.2.2 and 6.2.3. To do so, in the next section we first extend the related operators, and then directly derive the generalized solution of the problem. 6.3 Projective Solutions of Second Order Evolution Equations In this section, we let H and V be the same (but not necessarily real) spaces as defined in the last section, and let {A(t) \ t € [0, T]} and {B(t) | t e [ 0 , T ] } be two families of parametric linear or nonlinear operators, with parameter t, mapping from V to H. We consider the operator evolution equation Sai (t) - " ~ = A(t)u(t) + B(t)u(t), u(0) = u0 , du{0) = ux, dt
(6.57) (6.58) (6.59)
and its numerical solution [9]. For this setting, we have the following basic assumptions and convention: (tfi) D is a dense subset in H1 ((0, T); V), and for any v(t) € Z>, A{t)v(t) € L 2 ((0,T);tf) and B(t)v(t) € L 2 ( ( 0 , T ) ; # ) . In other words, A(t) and B(t) maps every element of D into L 2 ((0, T); H), respectively. We will say that A(t) and B(t) are operators from D C H1 ((0, T); V) to L 2 ((0,T);ff). In addition, for any sequence {vj(t)} c D, if {vj(t)} and {dvj{t)/dt} are both weak Cauchy sequences in Vy t e [0, T], then when iy j —► oo we have (w,A(t)vi{t)-A{t)vj(t))H-+0, (w,B(t)vi(t)-B(t)vj(t))
->0,
V*€[0,T],
weV,
Vt€[0,T],
weV.
265
Operator Evolution Equations
(Ho) U<(t)} C D, if it is a weak* Cauchy sequence in (H2) For any sequence {«,-(«)} Loo((0,T); V), then as t, j -* oo, we eave f/ {w(t),A(t) {w(t),A(t)ViVi(t) (t) 7o Jo /
-- A(t) A(t)VjVj(t)\ (t)\
w H
dt dt -- 0, 0, Vw(t) Vw(t) €€ ^^00((O O..TT));; yy)),,
# - > 0 ,
V«7(t)€ff1((0,r);V).
JO
(Hs) There are continuous operators T) x L2(0, T) -* >), (F3) o p e r a t o r sgk ^ : Loo(0, Loo(0,T)xL2(0,T) ^ 1^(0, LLo(0,>), k = 1,2, such that where Jk
| <™,,4(i>(i)>J < ^ f>(t)| v , 1- ^^1 |4(*M*))J
eD, weV, J^ H|«,|„, V , Wv(t) Vv(t)eD,weV,
I| (w,B(t)v(t))
|„,l \/,,(t\ €all \w\ Hv> Vv(t) Vv(i) A €D,weV. w „,(=V )j 1M „v,, .V«(<) D, w € V.
(HA4) ) UO ^o £ ^ and Ul ut € if. H. (H5) There are constants > 00 aiiu and KJi d > (ij-5) Tiitfit; are constants Co 1^0 > > 0 0 such such that wiat
Re
f(^?'X(TH*-CoK')l*
■Ci' *€ [o ,T l '
vV«(t)€D, , ( t ) e j ) , Ko)| ||^1|| |«(0)|vv << |«o| |tko|yv,, ll^^ll
< ^ j li ^w
(He) There are constants if > 0 and C2 > 0 such that Re f /^p-,B(r)v(T)) dr Jo \ dr >~v,-vy^~
^KU'^+imi„j*-cv«(t)eD, |«(0)|v <|« < |«o| l ^^pj Jl !r L <
Chapter 6
266
are bounded linear functionals on V. According to the Riesz Representation Theorem, there exists unique A{t)v(i) e V and B(t)v(t) e V such that (w,A(t)v(t))B
= (w, A(t)v(t))v,
(w, B(t)v(t))H
= (w, B(t)v{t))v
V^eV, ,
V w € V.
Then, we can extend A(t) and B(t) to the entire space ^ ( ( O , T); V): for every t;(t) G ^ ( ( 0 , ^ ; F ) , since D is dense in tf1((0,T);F), there is a sequence {^(£)} C D such that £ /o
(\vj(r)-v(r)\2v
+
dvj(r) dr
dv(r) dr
dr —> 0
(j —+ oo),
so that \vj(t)-v(t)\v^0
dvj(t)
and
dv(t)
~dt
(j -> oo)
dT
almost everywhere in 0 < t < T. Thus, it follows from Condition (Hi) that (w, A(t)vi(t) - A(t)vj{t))v
-+ 0
(ij -► oo),
V w € V,
namely, {A(t)vj(t)} is a weak Cauchy sequence in V. Hence, there exists a unique z(t) € V such that A(t)vj(t)
w
-> z(t)
(j -► oo)
in V .
It is easy to see that z(t) depends only on v(t) but not the selection of {vj(t)}. Therefore, we may define A(t)v(t) = z(t), which is an extension of A(t). Thus, it follows from Condition (H3) that
<«;, A(t)vj{t))v\<9l
h(t)|^
dt
w
VweV.
Thus, Proposition 6.3 implies that {VJ(t)} converges to v(t) in L ^ ((0, T); V). Now, we can let j —► oo in the above inequality and obtain
At)v(t)\
<9l
(\v(t)\v,
dv(t) dt
eL2(0,T).
Hence, A(t)v(t) e L2(0,T;V)^ An extension of B(t) to B(t) can be similarly carried out.
Operator Evolution Equations
267
On the other hand, for each v(t) G JD, / (w(t), A(t)v(t))Hdt Jo
and
/ (w(t) Jo
,B(t)v(t))Hdt
are both linear functional on /f 1 ((0, T); V). Let (w ,Av)=
[
(w{t), A{t)v{t))Hdt,
(u;,i?t;)= / (!!;(«), B(t)v(t)) H dt, «/o
V w{t) G Hl ((0, T); V) , V ^ J G ^ ^ r ) ^ ) ,
where (w, Ay) and (w, BV) are the values of the functional Av and £?i> at w, respectively. Under Conditions (Hi), (#2), and (#3), in a similar manner, we continuously extend both (it;, Av) and (w, Bv) to bivariate functional on ^((O^T^V) x Loo((0,T); V). In doing so, pick any v(t) G Loo((0,r); V). It can be easily seen that there is a sequence {vj(t)} C .D which weak*converges to v(t) in Loo((0,T);y), namely, lim /
(wit)^))
j->ooj0
dt=
[
(w(t),v(t))
dt,
Vti;(t)€Li((0,T);V).
Jo
Indeed, this can be verified by observing that {Jev)(t)eCoo(R-,V)nLoo((0,T);V)cH1({0,T)-,V) so that eKm
y
(Mt), ( J c v ) ( t ) - V ( t ) ) v d t = 0,
Vti;(t)6Li((0,T);V)
and noticing that D = ^ ( ( O , ? 1 ) ; V). Thus, Condition ( # 2 ) implies (w , Av. - i4vj) = / Jo
(w(t), A(t)vi(t) - i4(t)vj(t)) H dt -> 0
( i , j -> 00)
holds for all w(t) G iJ 1 ((0,T); F ) , that is, the sequence {AVJ} weak*converges in [H1 ((0, T); V] , and its weak* limit is independent of the choice of {vj(t)}. Denote this limit Av. It is clear that this A is weak*-continuous, in the sense that if {vj(t)} C L o o ((0,T);V) weak* converges to v(t) G
268
Chapter 6
Loo((0,T); V) then {AVJ} weak*-converges to Av. Similarly, we can obtain an extension B of B. Now, we show that for each v(t) e Hl((0,T); V), rp
(w,Av)
(w,Bv)=
= f (w(t),A(t)v(t)) dt, Jo V^eJEr^^T);^), J
(6.60)
(w{t),B(t)v(t))ydt, VttfWeff1^,!);^.
(6.61)
Indeed, according to the definition of A, we have lim (w(t), Avj(t))v where {vj(t)}
= (w(t), A(t)v{t))y
for almost all t G [0,T],
C D satisfying
Vj(t) -► v{t) Vj(t) -* v(t)
as j -» oo in H1 ((0,T); V) , dvjlt) dv(t) and •; —► as j —> oo in V (JLL
(IT/
for almost all* € [0,T]. Hence, using Condition (H3) and the Lebesgue (Dominated) Convergence Theorem [35], we conclude that fT .lim / (w(t), A(t)vj(t))vdt
rT = / (w(t), ^ ( t ) v ( t ) ) v d t .
(6.62)
On the other hand, it can be easily seen that (u,(£)} weak* converges to v(t) in Loo((0,T);y). It then follows from the weak*-continuity of A : ^ ( ( C r ) ; V) - [ H 1 ( ( 0 , T ) ; y ) ] * that
rT .lim / J
* (iy(t), A{t)vj{t))vdt
= lim (IU, AVJ) = (w, .Av) .
(6.63)
Combining (6.62) and (6.63) gives (6.60). The proof of (6.61) is similar. Next, let {Vn} be a sequence of subspaces of V, satisfying VnCK+i,
n=l,2,..-,
U ^ l ^ K ,
Operator Evolution Equations
269
and let {au--,aN} be a basis of Vn. Consider the following projection approximation problem: Find N
«. = £&(*)«*
(6.64)
such that
-" ( % r^ *, - ^°*)H ==(I(tK(t) ,««>„v >, < * K ( * ) ++B(*K(0 *(*)«»(*),««>
(6.65) (6-65)
( u^ n( 0W) ,, a^O) /du /du„(0) n(0)
=
,
(6.66)
\
,v
, „„. (6.67)
/A
^ - ^ , a ^ H " ! ><*>„•
(6.67)
for all i = 1, • • • , AT. We have the following results. Proposition 6.11. Suppose that Conditions (Hk) (k = 1, • • •, 4) are satisfied. Then problem (6.65)-(6.67) has a solution un(t) in the form of (6.64) defined on 0 < t < h for some h>0, and un(t) € tf2((0, h);V). Proof: Problem (6.65)-(6.67) is actually the following initial value problem of a second order ordinary differential equation:
(fie-^=/«(*;6,-,6r), «,, 6 (( 0 )) = Vv«),
(6.65') (6-65') (6.66')
^ ^ = = ^V-i0O, , ^jp-
(6.67')
= 1, • • •■, N, , AT,where where i =
r IC^A^Ur, l+B(t)un,aj)v,
N /
<
(
*
;
&
,
■ •
-,£*)
=■
N
=1 N
ViO --
N
>°^) v >
AT ^0
:
N
, ( & i ; ><*?>„>
a n d C ^ and a n d C ^y are the (i,j)th (i, j ) t h element of the inverse matrices of [(a <*)„]* andCij [{aj3;,, <**}«] *.j=1 =1 and [[
270
Chapter 6
From the definitions of A{t) and B(t), we know that for fixed ft , • • • , ftv, /i(•; ft , • • • , ftv) € L 2 (0,T) and for fixed t € [0, T], /„(t; ft , • • • , ftv) is continuous with respect to (ft , • • • ,ftv). Also, according to Condition (H3), / , is bounded on the set f
G:=[0,T]x G : = [ 0 , T ] x ij(ft,--..ftv)| ( f t , •••.ftv)| I
I
AT N
I
Y ^ -
' I j=l
Iv
1
(r > > 00 )) .. (r
J
Thus, it follows from the Caratheodory Theorem [22] that the initial value problem (6.65')-(6.67') has solutions {&(*)}*! defined on the interval [0,h] for some h > 0, and both ft(i)jind dft/i are absolutely continuous on [0,h]. Finally, note that both A(t) and B(t) map from ^ ( ( O . r ) ; V) to L 2 ((0,T); V); hence, «„(*) € tf2((0,T); V). Q Proposition 6.12. Suppose that Conditions (Hk) (k = 1, • • • , 6) are satisfied. Then un(t) satisfies
IM*)IL, M*)lv. I\du l1 ^d(t)\tl 1l *c, |M*)|L,|«n(*)|v.| n
II
"<-
lltf
for a constant C independent of n for ail t in the domain
ofu
n{t).
Proof: According to the definition of A(t) and B(t), under the Conditions (#3), (H&), and (fig), the Lebesgue (Dominated) Convergence Theorem implies that Re { j jTf (/ ^ ^l Re
,
2 ^ ( r ) t , ( r ) \ dr} rfrj > > C C00\v(t)\ , J^TMT)) \v(t)\l C,, v -- C,,
Ren*(^j{T)v{r)\
(6.68)
dT\
2)dr-C* > - K / [|I;(T)|* + R l l 2) •/o V II dr T llff/ ■/o V II d I Iff/
>-*/YH<+II^II V-^
(6.69) (6.69)
for all v(t) € H 1 ( ( 0 l T ) ; V ) satisfying |t,(0)| v < |«o| v and ||
/dun(t) /dun{t)
,
~
\ A(t)Un(t)\
Iv
/du /duJt) n(t)
~s , \ B(t)un(t)\ .
Iv
Operator Evolution Equations
271
Now, integrating the above from 0 to t and then take the real part of the result, it is easy to verify by using (6.66)-(6.69) that dun(t) I dt \H <
+ C0|un(t)|5
5lMli + * j f (MT)£ +
dun(r) dr
dr + C1+C2. H
To this end, it follows from the Gronwall inequality [23] that there is a con stant C3 > 0 such that dun(t) dt
+
\nn{t)\2v
H
Since ||w n (£)|| H < 7|w n (t)| v , the conclusion is immediate. Proposition 6.13. Suppose that Conditions (Hk) (k = 1, • • • , 6) are satisfed. Then problem (6.65)-(6.67) has a solution un(t) e H2((0,T);V) well defined on the entire interval [0, T]. This result follows directly from Propositions 6.11 and 6.12, and the solution extension theorem from the theory of ordinary differential equations [22]. Proposition 6.14. Suppose that Conditions (Hk) (k = 1, • • • ,6) are satis fied. Then there is a subsequence {ujn(t)} in {un(t)} satisfying the proper ties that when n —* 00, (i) {ujn(t)} strongly converges to u(t) in C( [0,T];Zf); (ii) {ujn(t)} weak*-converges to u(t) in Loo((0,T); V); and (iii) {dujn(t)/dt} weak*-converges to du(t)/dt in Loo((0,T); H). Its proof is the same as that for Proposition 6.8. Next, we establish a generalized solution for problems (6.57)-(6.59). Definition 6.4. (6.59), if
u{t) is said to be a generalized solution of problem (6.57)-
u{t)eC([0^H)r\L„({0,T^V)y du(t) €ioo((0,T);ff), dt w(0) =
UQ
Chapter Chapter 6t Cftopier
272 272 272
r / . \ _ ^-Y/|V> m l U\ TT\ n TrMln. rr,\.Tz\ __i;_t_: ../T,\ _ 0. r. H(\C\ T};H)n Th T V\ satisfying satisfvino„(T\ = isfying, v(T) w(r jHjnff^CO,Tj-.Vjsatisft and C([0, V) (T) = 0, andforallv(t)eC([0,T];i n di for allit v(t) € C([0,T\;H) n„ H ^Tfl(((\ (1 (((0, O , TT); )V; V) w(T)
[T ldv{t) du{
(6.70) leads Is to the second required equality in Definition 6.4.
[]
Theorem T h e o r e m 6.5. 6.5. Suppose Suppose that that Conditions Conditions (Hk) (k (jfe = 11,, • • • • ,6 )aare r e satisfied. satisfied. Then roblem (6.57)-(6.59) has a generalized generalized solution. solution. Then problem problem Proof: W h a t tthe h e u{t) Wee show tthat u(t) obtained in Proposition 6.14 6.14 is a generalized solution. Let InInn : V -» Vn be an orthogonal projection operator. It follows from (6.66) that t h a t un(0) = n n u „0 . Hence, {un(0)} converges ttoo u0 in V, aand n d so i i H. It then follows from Proposition 6.14 that {ujn(0)} {0)} converges to u(0) in H, so that u(0) = uo. T); V) satisfying u0. Pick any v(t) G C([0, T]; H) nnH H 1 ((0, ((0,T); v(T) = 0. Then by (6.65) we have
-- ((( W «t), ^^ ^jf1)^^ )} n i n in)/ ) «t),
= ((
•
Integrate the above from 0 to T, and then integrate its left-hand side by parts using (6.66) aand n d its right-hand side by parts using (6.60)-(6.61), we obtain
f M f fi + (n...^ ? +B^) -jf(%^.^)* + -r( % ' ^ )/ K-- - + -) = ((Ujnjnv)(0),u11)HH =
- /(Ujnjnv)(T),
^ ^ }
••
((6.70) (6.70)
According to Proposition (t)/dt) du(t)/dt {t)/dt} weak*- converges converg. to du{t)/dt (dtu (t)/dt\ du(t), in ion 6.14, {d {duj Uj n(t)/dt} L^ (t)} u(t) in L L Loo((0,T);H), (t)} weak*-converges to u{t) Loo( ijn(t)} x ((0,T);V). Also, T O ((0,T);H), and {ujn . [[^((O.TfcV)]* rrr1/7n T)\;.V T r)t]l** are both u . . u weak*-continuous, i.. „ _ . : _and _J L LooftO.TfcV) -* &B : Loo((0,T);V) ^ ( ( O . T weak*A,B [^((O.T);V)]* {(0,T);V) -* [H ((0,T);V)\ are both weak*-continuous, and } {(Ujnnv)(t)} {(nj v)(t)} )} converges to v(t) v(t) in ^ ( ( O . T ) ; V). Therefore, letting 77, —> oo in 77, —> oo in (6.70) leads to the second required equality in Definition 6.4. [] Finally, t h e above computaional framework for secly, as an application of the ond order nonlinear evolutive equations, we discuss a typical higher- dimensional Schrodinger equation, which models many physical problems such as nonlinear reactions of mono-colored waves, soliton of plasmatic physics, aand nd horizontal speed of higher-frequency electrons [20], etc. T h e initial-boundary The
273
Operator Evolution Equations iue problem of such operatic value by ch a wave operation Dion equation equation is is described aescriDea Dy
2
2
2 ^ £, 95d 22uu A A ^ a8d (/ ,, ,.,du\ ,du\ du a \ ^A £,L6L/LL, ,, ,,, dddd222uuuu + c2 Uu c2 c2 9n\ akjix) + akjix) +++E 6j(*)a^a7 +6 ++ 6*c2uuu a* " E &£ (^'WtejJ z^k.l ^ {^ w f edx-) j ; Szox*) r—f w dx,Ct w-^w ^ 'pW ^^°^ ^ - - fc,j=i ax-J g ^ax-a^
w-^aii: { dx-) E^■(*> dx~M 9 x f Kc
.
fdu Vat \ ds *t V
= f(x,t),t'j), ? f(x,t), f(x,t), = = /V*£> = /|x,z;j,
u(x,t) u ( x , t ) ===0o,o, «(x,t) «u(x,t)=0, ,
v
22 r)^)+/3(x)g(H )n :)|?-)+/3(*)«(M )u a xdx dx JT^ 71~{ ===1 11I ax,/^i^jJi)/ ax.,; iGtfGO, ttO!xen, f!, !iM,!, ,, itt>0, iXXxeft, *rt> xtsi, >0>,u00o0,,,
xxedn €exedn, dadff tI,, ,
(6. (6.71 (6.71) (.o-'J-J (6.72 (6.72)
f>>>000,,, tft>0,
^ 0 ( x ) , —/ft (iXi(Zx(x)z)))),,,, VH)(x), ^^ |l^^^^=^— =I=V ==^V Ii(V (V»i(x), u(x,0) = Mx), u(x,0) = M*), ^VV Vtt(x),
x €e f ti , xell,
(6.73 (6.73)
QC c .iR where, as3 usual, i< = = vy ^^T and ft i?RR ?wNNN" is a bounded region with a boundary boundar 9ft, aft, (5, 6, and id a are real constants, f(x,t)=(f f(x,t) / ( x , t ) =1(x,t),...,fM{x,t)), ((//1i((x,t),...,fM(x,t)), xM , t)(h(x,t),...,fM(x,t)), ) , •- •- -• ,,//A *M((*X, *, 0) )),, MX) =
M )X,))-, ,-----,-,V (0^MOX ,VVOOOM M((XX)))) ,, 1( (X
V-I(X) V*I(X) =
,1,1 (VH ((XX))),,,--------,,VV ' II M ( „(^\ X)), I I(x\.... r
/
\-» JV
i
i
i
/
.
are complex-valued {^(x)}^ jlex-valued vectors, ctors, {C j(x)}f=1 =1 are complex-valued functions, aOfcj(x) (x), kj(x) ) = ajfc jk(x),
.j(x), bj{x), bj(x),
/?(x), /3(x),
and g(s) (s > 0)
k,j = l,---,N !,-■■ l,---,N ,N
are real-valued valued functions, and =( «(Uli ((x,t),--«u{x,t) (x,t)= x , * ) , "•••
,uMM {x,t)) M({x,t)) > «,u M))
are complex-valued ilex-valued vectors to be determined, denot Euclidean ed, with |u| denoting the Eu norm of vector u. Let H = L2(ft) L2(Q) and V = H%{Q). H^{Q). We say that the vector-valued ffunction (x) = («i(x), («i(s), (vi(x), La(fi) r in H&(Sl)), H^(Q))t denoted w(t) (fi) v(x) is in L H%(fl)), v(t) €€e L 2 (ft) Wl(s), • • • ,vM(x)) 2(ft) (or 1 v{t) e H^(n)), L2(fl) flj(n)) >r u(t) fl2(n)), w,(s) (^) (ft)) for all jj = M. (or fl3(n)), if w,(x) t»j(s) €e6 L i 22(n) (2«(n) ) (or u,(x) Vj(x) H^(ft)) = 1, • • •, • ,M. «j(x) fl3(n)),ift>j(x)eL r (x) € Ho et Let
- « - £ £(•*■>£). -)■
2
. ( du
^-^
,
„ , x = r5^>, x/ )x ^ ^ ci 2 • f9u ^ ^ x, x)x du B — \j Bt)u=> bAx)-—B ( t ) u U ( ++ 6r u -u »^a ^ -- ++ £ >c j C( cAx)-. B3 ( t) u b + 6u %a + {x) W = E M * ) ^ + ^ ( + E ^ ) ^JJJ W ) ^ a ^ ^ ( x ) — u = 2>(x + t + 23 = 1 v
^ = T, ^)e^
222 + /3(x)< / 3 ( xg)(M ((|u| H2 )u-/OM). ))n-/(x,0. )u-/(x,t). u-/(x,t). /3(x) + /?(*) 99 ?(H
du \
- [m ^ dx-j)
Chapter 6
274
Then Equations (6.71)-(6.73) can be written in the form of Equations (6.57)(6.59). Choose a complete sequence {Wj} from H^(Q), in the sense that if h(wi) = 0 with h e \Hi(Sl)Y for all j , then h = 0. The Galerkin app r o b a t i o n problem is to find nn < j(x), a; Un(x,t)=j2^jn(t)w
un(x,t)=E^«( H( )' 3=1 1=1
where
unB(x,t) (Itt) U
=
(u(« (i,t))) nl(x,t),---,u Bl(I,t),-)ttBM nM(x,t)),
^»(*) = fenl (*),"•
,^(*)),
such that
\
Sp . ^ ( O )
\
' L2(fi)
+ 2 ^ (akj(-) fc,j=l
'
+ E ( ^ ) % ^ , ».(■)) j3=1 =l
x x
J J
'' Li-2("> 2(n>
d
3
\
J
ij=i =i
I z,2(n>
+« a (iw(-,t),u,.(.)> tj(0)
, .. / dUntj; t) , j ^ _ , , dune(; t) \
>~fc) k
•'
I/
Loin)
, 2)u e(;t),w (.)) (f3(-)
+ + x
=(ft(;t),w =(M-,t) s(-)) ,wsL2(n) (-)),LiW,
(6.74) (6.74)
<«n/(-,0),«;.(.)> ( ^ ( . ) , u ; . ( -Him ) ) H.o x ( n ) . («ne(-,0),M-))HiH(a, ()n) = (M-),M-)) /dUruj-,0) / d i w ( - , 0 ) w^ ^A\ *
= (ll>u(.) ,W,(-)) L =(^w(-).tw.(-)>
n
(6.75) (6.75) ,
(6.76) (6.76)
' L 2 (fi)
^ = 1,-.- , M e=l,--M,, s5 = = l,--1 , . . - ,n. ,n. Now, we have the following assumptions: (i) akj(x) that
LaofrlkJfc,j = 1, 1,---,N, e Loo(n), • • • ,7V, and there is a constant r > 0 such f,
N
v
N N
11
k,j=i k,j=l
> >
j= 3 =i1
N
*)
Re Re £E ay ^ (*)&& w ^ r >- r^£N|^|22', dbjW/dxj eL (ii) dbi{x)idxj eL0000(n),j (n),j == iit ... jv. t ...) )jv.
V(& , • • • , £N). v(6,•••,&)•
Operator Evolution Equations
275
= l , .l,--.,N. (iii) Ccj(x)€L ( x ) €00L(Q),j oo(n),i = ..,^. (iv) /?(x) € e Loo(n) and /?(x) p[x) > > 0. 0. r) 9gq(s) (s) = SW P/2 4/(iV P / 2;,, where oo o00 <
aurx.t)
_
- ....
.
^^-eL^((0.T):Lo(n)) ^ ^■e ^L o 6LooftO.T);/*(£!)) o^O.TJj^n))
. .
ufx.0) and «(ar,0) ^rfofx): (ar); u(x,0) = Vo(*);
1 1 Forall*,(x,*) € C([0,T];L C([0,T};L (n))nH\(0,T);H^il)) (b) ForaU»(x,t) Forall^(x,t) C( [0,r];L n ^)T);i/ H ^ 0T1(fi))satisfyingz;( ) SA ; ^tisfyingv(x,T) ^ ) ) satisfying 22(O))nF a;!r) 2 (Q) j ((0 v (a:,r) = 00,
fT1/d/due(;t) Ui(;t)
~Jo
,
\~~d^'~^/ \~~9^ ~dr/L2{n) L2in
+ fT X- In
b
•'
M
^ j=i ^ j=l ^ jj=\ = l \\\
3(')
Q
\
dt
\—d^
y
3 •»3'
AT
I
I/dudeUl(;t) {;t) + t a
^
M^A\ M j*)\
M*
d t /
~
akAak] j( ) k%\ ' ~dx~~'~dxVl ' ' ^x~''dxV/L. L2m n h\akA ')^X ~dx~~'~dxVI L.Ci.
Jo h 1 / 000
dv{;t)\ dv(;t)\
^ ^ +
^
I1'I z, n) L2(n) L2( 2 (n)
J
dxt
^'^h2(n)
\
&<<(•,<) dut(;t) Jw
\U£^t}
\\
' -' '
^Cj{-)-dx—M-'t))
L2W
22
(\u(;t)f) * ?(•) q
(6-77) (6-77)
where It = 1, • • • , M. where we £ =utilize 1, • • integrals • , M. by parts with respect to both x and t to achieve Here, Here, we utilize integrals by parts with functional respect to both x and t to achieve ;hes continuous extension for the bivariate functionals the continuous extension for the bivariate functional (w(-), («;(•), t))L2{n),, («;(•), A(t)u(; <«;(•), B(t)u(;t)) L2{n),, («;(•), A(t)u(-, A(t)u(; t)) t))L2(n) <«;(•), B(*)«(., B(t)u(;t))L2m L2{n) L2m («;(-, A(t)UU(; t))L2{n) (n;(-,t),i4(t)ti(.,t)> cft,dt, f/ T (W(; t)t) ,, A(t) (; L2(ft) dt, L2{u)
(w(; t) dl ) (ft. t .• /fTT <«/(-, (u;(,t),B(t)ti(.,t)) «) , B{t)u{; B(t)«(-, t)) *)>L^La 2 ( f(fl)*
276
Chapter 6
The extended bivariate functional (in Eq. (6.77)) have the aforementioned properties. Theorem satisfied. Then Theorem 6.6. 6.6. Suppose Suppose that that Conditions Conditions (i)-(vii) (i)-(vn) are are satisfied. satisfied. Then the the Galerkin approximation problem (6.74)-(6.76) has a solution v u (x,t) €ee {x,t) Galerkin approximation problem (6.74)-(6.76) has a solution u nn(x,t) 22 1 #H ((0,T)-H^(Q)). ((0,T);Hi(Q)). {x, convergence described 0 (n)). The H2((0,T);fl ((0,T);Hi(Q)). The sequence sequence \u \unn(x,t)} {x, t)} t)} has has the the convergence convergence described in Proposition 6.14, and the corresponding limiting function u{x, u(x,t) t) is in Proposition 6.14, and the corresponding limiting function u(x,t) u(x,t) is aa gen generalized solution of the problem, as defined by Conditions (a) and ((b) above. Proof: Recall the Embedding Theorem in Sobolev spaces (Appendix B), 2, the embedding H&(Q) which implies that when N < 2, fl£(n) <-+ «^-> L,(fi) (1 < q < oo) is compact; when A NT > 2, the embedding H&(Sl) <-» L L,(n) q(Q,) (1 < q < 2N/{N 2)) 2)) is compact. Hence, if {V } weakly converges in n^il), H&((1), tithen j ziv/[i\ - zjj is compact. Hence, it |Vj) weaKiy converges in it must be strongly convergent in L,(Q) (when N < 2, q = 2{p when 2, 2(p + it must be strongly convergent in Lq(Q) (when N < 2, q = 2{p + + 1); 1); w; N>2.a = ANH2N -(N2)v)). the Holder ineaualitv N>2,q 4N/(2N (N 2)p)). It then follows from inequality N>2,q = 4N/(2N - (N - 2)p)). It then follows from the Holder inequa that for any w € H&(Sl), when N < 2, p p pP f \vk\ \vk\ vkwdxvkwd, dx- /I \vj\ Ivtfvjwdxl I f\vk\ vkwdxvi
f/
<(p+l)2P <(p+l)2P <( P+1)2P p+1 +1 +1 < < (p+l)2 (p+l)2P (P+1)2P
f t ,
(|,
p+1
nP+)
sui sup snp(f ( f m \v\m\p+1dxY Y ^ mp(f\v lx)d cdxY^^ -LIS :■>, _LIS
•(7ta-f*l • / h-^l ->0
pp pp (\vj\ +\vkk\kkp\)\v -vj\-\v>\dx \-\w\dx (\v (\vj\ijp\+\v —)\vVj\ \w\dx kk-vj\-\w\dx ij■ k-v
\V(2(P+1)) '+!)) / f/•
ikfip+1)dx) h-»*l ^J
M
(I I(( /
\xl/(2(p+l)) V(2(P+1)) D)
l 2(p+1) h Iw^+Vdx) k|\w\^+ dx)
(6.' (6.78)
(fc,j-^oc
and when N > 2, nd when AT > 2, | f jW dx / Kl|V»^-/j»,|'.,»^| *
■ -»0 ^-►0 0
a
/ /•
o„ »„r ,„^„r „, os 2N/(N-2)
p(N-2)/(2JV) \\ \P{ PN~ (^-2)/(2JV)
/(Ar 2) \vmm\ \2mN ~- 2)
< (p + l)2 p "
jf:,j^oo), fce, j -^>o
(6.79) (6.'
277 '£(7
Operator Evolution Equations = 4N/{2N AN/{2N -- (AT (AT 2)p).Also, Also,when whenN ATT<< <2,2, 2, 4N/(2N (N ---2)p). where 9q = 2)p). Also, when A
I/„ M "H < ^
/
r
\P/(P+I) /
/ H^dx v/n \Jn )y \Jn J /
/
I
I -30—I-1
T
\
\V
r
/ \v\Wdz) \Jn \./n y) \Jn )/ 1,<< , , ,, /
/
I
l2f77-m
7
\
. ( / no w-»*) .(/ M - » * ) " ^" ^ ^ ^r. ip+l
i i
uw, | ^ cCc\bl^(n)l lv\vVl^(n) lHl(n)\ ^ ( n w) |l-H »0oUn) ( n ) '> \Hl{n). »o(n)'
w
. _ rrl/^\ .
/^ oi\\ (6.80) (6.80)
V« iJ #ffo(^); ( fnl ) ;; v, -y,, w €€ J#(fl)
and wheni AT A r>22, , / |«|»Wda; |v|*Wdx I Jo. Ju I < <
/ trr 2 \\ (AT+2)/(2AT) (JV+2)/(2JV) 22N V p+1)/ ( p + 11) N+2) / ( JJVV+ 22) d \ 2 JJV v\ N(p+l)/{N+2) da; II + )rfa; I //I/ \|M \v\ ((P+ ()/( dx)1) V| .■ x // //• \ f / mU„|2AT/(7V-2) ax, \
(N-2)/(2N)
H U dx) \L ) UH dxJ ^cK^HHicn,, v«,«,€^(n).
(6.81) (6.8i)
editions Conditions Hence, it follows from the given Conditions and and (6.78)-(6.81) that C« {Hk) {k (Hk) (k = = 1,2,3) 1,2,3) are aresatisfied. satisfied. Besides, Besides, Condition Condition (H4) (H4)is isobviously obviously satisfied. satisfied. satisfied. rheorem What are left to verify are Conditions (H5) and (He). By the Theorem conditions, it can be easily verified that for all ve(x,t) G H&{(0,T); ffifO)), H$(n)), €£=l,--,M, = 1, • • •, M,satisfying satisfying .
.
. . . .
K-.0)|^(n,^N-)lH4(n,
«"*
Il3wf..0}ll
R P
iiit
..
iiL2(n) iiL2(n)
where v = (v (Vlt,, •■ •■• ■ , vM , v),M),wewe have have thethe following: following:
_ / v A aki \kkhdx* hdx»aki
d () M;t)
dve(;t)\ **, '' M dt /) **,
i££222(<
N — t(. ,dv dv£e(x,t) (x,t) dx ^ dv dv £{x,t) e(x,t) 1 d ff ST *—vak dvff(x.t) dve(x.t) a x) dx]*t = o 37 / / ^ fc? W —EZ Er 1 d
= 2JtJn^
fc-,3—1
^ ~d^j
. ...
^<\\M-)\\L2(ny
dx~T
Chapter 6
278
-jm-E^-o-gf.-SrV U tt
M 1V1
I I
N JV
r\
r\
/
, \
r\
/
,\ \
'' JJ
M
iV N iII i On
/
,. N \ |i| 2 | 2
M M iV JV iI n
CM»\dv.
I
L 2{n) ^2 (") 1^2
/ „A X N i| i| 22
( ;0)\\
^2^E - EE-^ 2 f - f ^-f i#^ *i >iK^)|^(n)-CC>'' >iK^)|^(n){JL/ ,, . , »2, dv.(:f\\ 1 R4E(«) W,O,^) «e{i;(/J(-)9(K,*)| } ? (K,*)I W-,*),^) Xl 1=13=1 £=1 ?=1 "
^
J
"MI / 2 ( " ) i/o(ri)
^
\ ST^ / nr ^
/ I/
* = 1 J =l £ = l .? = !
AI2X
,
^
"^2<") ''-Loin)
dvA',t)\
x x
II e=i e=i 2 2 ion/ o « «A„(L,(„*M ) 9 ( | * « ) |\?-U„*\2*r )||»(M)|^
= «.).(K«.o|')|K..o|'* -i/ «.),(K*.«)|')||.M'* (3(x)\v(x,t)\p+
^
'' ^2<") ^2<") J'
dx,
Jj;i( B.{jf£(«).(K.o|'M-.o.^) *} n-MH,f)M^^) w-} *
I L^ 22<Sl) V»»;
*.— J.
J /
p+2 p+2 = ^ —m\ (3(x)\v(x,t)\ dx- 2**-jJ^x)/3(x)\v(x,0)\ dx\ 2 U/I(X) \<*>*)V \v(x,0)\p+2 dx}
» - c ,
-(§M..^.^) XT - :
oxjuz
\j=l
_
1 l
ai
^
/
/
vV^^ / /* vbj^x) dbAx) \dvAx yt)\ \dv£(x yt)\ T
Z,2(n)
^ ^||^(a;,t)||2 - ~ \\ dt dt "
"^2(") "i,2(n)
d
Re( Re R e(*,,(,*) ( *(S\(,t), ,^, ((, * , t)-^) ) ,, ^* * ^) )\ Re^(,t),^i) \^^ 6i '/'' 1,2 z,i 2/ (n) (n) ((n) ") 2 2 A / ^ II ^«,„r 2
s-TfiM-.oiiuHi^ir )•
> _ f flL,X ,MI ■-y(lN-.«)l£.( Bm, ++, |1I^(->*)H f A )) • ^-ffiM-.oiiu+i^ir). ^-T(lM-.«)lll |||2!!^5r| i |f • \
Re ( -ia —^—-^ , \ dt ' X X
M
2
M
wy
) L2(Cl) L at ''' L2(Ci) /(n) 0
£2(n) /
279
Operator Evolution Equations
• V^ ,,dM;t) ■
p„/
dv (.,t)\
R e( <-ia^cji-) - . « ^ Jc , (- . ^) -- ^- -, — , -5 ^-e— - ^) Re \
*-^
at
dxj
J
i2(n)
22
dv 2 /yJ|d^(-,t)|| .> rr(\^\\ ^/v^ll^(->*)H > Y v l l ^ ^ ir ^^\\ [ ^ \\ dX
-"~ "
|
^dt + \\ dt
dx
lV^-f ^-f
| ^**(,t*) ( -et t ) | | 22II2 .|H^(,t*)ir IIIl^(-tt)|| \\^( ^
3j ax,
^\'^ /) ''
R e / Jtx _A <, ),^)\ R.(_ w , (t),»«M\ '
*
"
dt
/
' i2(0)
l/(-.')HL«)+ 1 1 ^ 1 1 )■ • ^-Kii/f.'iiiu+ii^ir
i f f).l*l U ^ _- »+ IIr ^ i iII r.~/"o\ 2>- _± 5 ( l Vl /i M \
M
/
"i2(n) /
Therefore, ore, Conditions (HK) (H*) (ff 5 ) and (ff (He) (He 6 ) are satisfied based on the above inequalities. Consequently, the final result follows from Propositions 6.13 and 6.14 as well as Theorem 6.5. [1
280
Chapter 6 Exercises
6 . 1 . Prove Proposition 6.1. 6.2. Consider the following problems: (i) Let i / b e a Hilbert space and 1 < p < oo. Show that the embedding C([a,b];H) <-> L p ( ( a , 6 ) ; i ? ) , - o o < a < b < oo, is continuous. (ii) Let Hi and # 2 be Hilbert spaces, with a continuous embedding Hi <-> #2- Show that the embedding Lp((ay b)\Hi) <—► Lr ((a, 6); # 2 ) , - 0 0 < a < b < 00 and 1 < r < p < 00, is also continuous. 6.3.Suppose that 1
= Lq((a,b);V*)
.
6.4. Consider the initial-boundary value problem (6.15)-(6.17) in Subsection 6.2.1 of the text. By letting H = L 2 (fl), V = H$(Sl), and A(t)u(t) = Au{t) + / ( * ) ,
B(t)u(t) = 0,
and
2? = £>(!),
formulas (6.21)-(6.22) can be converted into the form of (6.13)-(6.14). (i) Show that operators A(t) and B(t) satisfy Conditions (Hi)-(H/i)y the first part of (i/5), and (HQ). (ii) Suppose that the boundary dQ of Q belongs to C 2 , which ensures that if f(x) € L2(£l) then the generalized solution u(x) of the boundary value problem -Au = / , w|a n = 0, is in H£(Q) H H2(fl). Assume also UQ(X) G D and let K =span{ei(x),... ,en(x)}, where {e J -(x)}^ 1 are the generalized eigenfunctions of the first boundary value problem defined by the Laplace operator —A in region ft, with the corresponding eigenvalues { A ^ } ^ . It is well known that <\?+i > Xj > 0,
j = 1,2, • • • ,
and
lim A? = 00, 3—>°° { e j( x )}>Li can be chosen such that it becomes an orthonormal basis of L2{ft) and {ej(x)/ yj\j + 1 } becomes an orthonormal basis of #o(Q), which implies that U^K
= H^n)
(under || • | | f f . ( n ) ) ,
0 ^ K
= L 2 (fi)
(under || • | | i a ( n ) ) .
Operator Evolution Equations
281
Show that the second part of Condition (#5) holds. Note: e (1) For any g(x) G #o(^)> i t s Fourier series Y^LI^^J)L2{0) j con" verges to g(x) also in HQ(SY). (2) Every ej(x) G (7°°(fi), and satisfies equation —Au = XjU almost everywhere in ft. (3) Under the condition 80, belonging to C 2 , e5(x) G H%(Sl) n H2(Q,), j = l,2,.--. 6.5. Consider the following initial-boundary value problem of a system of nonlinear, degenerate parabolic equations: ^ , x )
= A
^ M
+ / M t ) i ) ) j
0<X<e,0
(a)
w
0
(c)
., is a real constant matrix and
ui(t,x) u{t,x) =
^i(x)
' /iW " ,
,
/(«) =
_uM(t,x)_
>(*) =
JM{U)_
7
_^M(^)_
are all real-valued functions. Assume the following conditions: (1) A satisfies (A£,£) > 0 for all £ G i ? M ; where (•, •) denotes the inner product in RM, with the induced Euclidean norm denoted by | • |. (2) fj(u) G C2(RM) and fj(0) = 0, j = 1, • • . , M , and there exists a constant if such that df(u) du
e,e < w ,
v^er.
(3) ^-(x) G ffoW) n ff2(0,£), i = I,- • - , M . Then, let V^ = span { sin(7rx/£), • • • , sin(n7rx/^) } . The Galerkin projective approximate solution of the above initial- bound ary value problem, (a)-(c), is given by Un,l(t,x)
un(t,x)
CTuipfer66 Chapter
282 282 with ln u«n,l(t, =E E &>.«.*(*) £»,*.*(*)S sin ^cr)> X) = ( ^ ) ' n,i(t,*)
•, .M . »»==1,1,• ••• •, Af
fc=l
fc=i
It is required that this solution satisfies / OUnti A \ /%£, aT ,V
_ L Y " V ^^ " .,J ^ "^\ \ ) v) ^ , ■(d) -=( (/f(~ ^W (d) + v / a 3, dx dx dx I , ( 0L2(0,> /) 9X \\~~ ' /L2(.o,i) /L2(0,t) hp{\ \ /L2(0,t) ' /L2(o,e)~ ' dt
(e) (e)
<«n,i(0, ••)) , »(•) & , ^) (0,£) '> w(-) ) il 2a (( 00 €/ ) = ((^i^) ,e) L2 L2{0
for all « € Vn and alii = 1, • • • , M. Prove the following three results: (i) Under Conditions (1), (2), and (3), the approximate problem (d)(e) has a unique solution un(t,x) defined on 0 < t < T, satisfying «n,i(<, x) € C\ [0, T); ^ ( 00,,**) «n,i(<,x) C 2 ( [0,T]; ) ntf2 (0, *)) I) ) ,
i« = 1, • • •, M, M,
and \\dUn(t,-)\\ a
\\un(t,
II
dx
S ^ 2 i
\\L2(0,t)
ll/Mv))|| || ||^^( iv|)|| w| ) £ C < , \\f(»n(t,-))\\
3
||^V)|| ||9t^V)|| 5
U IL (o,*) U llII * *** * lli IL222(0/) (o,*)
II
dx2 \\L2(o,e) ~
) (/(/)
^ Vte[0,T],
where C*1; • • •, C5 are constants independent of n > 1, and r M r M
.1/2 .1/2
IM.olU^^JEIM^ollLco/)} , ^ i4 == 1l ^
''
2
2
etc. Hint: In (d), let consequently v = wn,i, d unA/dx , d^u^/dx*, and dunti/dt, and then sum over i = 1,'- • •, M,' the inequalities of (f) can be obtained. In deriving the fourth inequality, the following interpolating inequality in Sobolev spaces may be used: For all v(x) € LPl(a,b) n W*-»(o,6), - o o < a < b < oo, k > 1, and 1 < Pi < P2 < oo, we have \Hw'.P(a,b) \\v\\W<.r(a,b)
< C\\v\\)£ < C | M l i{at - Ab)( 0 f 6 ) •■ \\v\\w I M kk»,PHai . - 2b)( a . 6 ) ,,
283 283
Operator Evolution Equations Equations where C = C(k,£,Pi,p2) satisfy
is a constant, and A, p, and t together
p-1l-l -e=(l-\)p= (l-1+\(p\)p~11 + A (p^ 1 -k), - fc),
It then follows that
Vve HHa,b). VweflV.t).
4
IMU4(a,6) < ■ ||t»||^x |M|^ 4(a>&) ll«IU«(a,6) < c\\v\\%\ C7||«||^4(a>fc) ab) ■ ( a i 6 ),,
(ii) Under Conditions (1), (2), and (3), there exists a subsequence {ukn(t,x)} in the sequence of approximate solutions {un(t,x)}, such that for each t = l,---,Af, (ii.l) {uknA(t, i ) } converges strongly to Ui(t,x) in L 2 ((0,T) x (0, t)), and weak*-converges to Ui(t,x) in ^ ( ( O . r ) ; # 1 ( 0 , 0 n H2(0,£)); (ii.2) {duk i(t,x)/dt} weak*-converges to dUi(t,x)/dt in ^ ( ( O . T J j L a (0,0); and (ii.3) {/i(«fcn(t,x))} weak*-convergesto/(u(t,x)) i n L o o f t O , T ) ; ^ , * ) ) (iii) Under Conditions (1), (2), and (3), the initial-boundary value prob lem (a)-(c) has a unique generalized solution «(«, x) = (ux(t, x ) , • • • , uM(t,x))T, namely, «u,(t,x)eL ((0> r ) ; f f 00 11 (o,/)nJi ( 0 , 0 n f l aa((o 0 ,lO), /))l i ( t , x ) € L o00 o ((o > D;ff ^9m0|,g) ^ ^ € L o eo (^((0( >0T, T) ); ;L£22( (001,00)) >,
tt = = !l,,•-•---,,M M,,
which satisfy
/a Ui \ /au* (-37'^) 9 i \\
A A // a22u,%- \
= Z^\a*J ^2'u) d x
d x /La(0,/) /La<0,*) /La(0,/) J=f ~ ? \\ /L2(0,«) ( u i ( 0 , - ) ^ ( - ) ) L 2 ( M ) = (V'i^) L 2 ( 0 ,,),
_,,,, x v v
+
\fi\u)>v/L,
^ '' ''
al
for eHi(0,t),i = 1, !,•■-, for all all v(x) w(x) € fl£(0, t), i = • • •, M. M. 6.6. Consider the initial-boundary value problem of a linear parabolic equa tion:
du du A a //" au\ a u ,\ A A au au ,-^oo nn^^++^^ ^^ ++ + x € e n 00<
xedSl, xeao, 0 <0
284
Chapter 6 N where 9. ft C Rfl" is a bounded region, 0 < T < oo, and the coefficients Oi,-(x), aafx), aJx), aAx), 0(x) 8(x) and the function f(t,x) are real-valued, satisfying (1) aihahfiOij/ajtPeLeoia); €/,«,(«); (2) there exists a constant C0 > 0 such that AT N iV
AT N iV
£ > « ( * ) & & > Q>$>?, i,j=l i,3=l
V(e 1 ,---,^)€ J R JV ,
*eft;
3j=l =1
(3) for all t €e [0, T], /(£, •) € L 2 ((^); (0); moreover, there is a constant L > 0 [0,T], snr>h that that such | | / ( i , •) - / ( * , Olkcn) ll/(i, Oilmen)
V 8*,* , t € [0, T ] .
Based on the results given in Subsections 6.2.2 and 6.2.3, discuss both continuous-time and discrete-time Galerkin methods for the above initial-boundary ial-boundary value value problem proDiem and and obtain obtain error error estimates. estimates.
References [I] R. A. Adams, Sobolev Spaces, Academic Press, New York, 1975. [2] B. A. Bacilehko, Spline Functions: Theory and Numerical Programs, Hayka, 1983. [3] F. E. Browder, "Remarks on nonlinear functional equations: II and III," Illinois J. of Math. 9 (1965), 608-616. [4] F. E. Browder, "Nonlinear operators and nonlinear equations of evolu tion in Banach spaces," Proc. of Symp. on Pure Math., Amer. Math. Soc. 18 (1976), 1-308. [5] M. Chen and Z. Chen, "The constructive solvability of monotone oper ator equations," (in Chinese) Proc. of 60th Ann. of Zhongshan Univ.: Comput Sci. & Comput Math. (1984), 85-91. [6] W. Y. Chen, Nonlinear Functional Analysis, (in Chinese), Ganshu Peo ple's Pub., 1982. [7] Z. Chen, "Some results on approximation solvability for nonlinear op erator equations," (in Chinese), Acta Sci. Natur. Univ. Sunyatseni, 2 (1984), 62-71. [8] Z. Chen, "The projection approximation solvability and estimates of the rate of convergence for a class of nonlinear evolution equations in Banach spaces," (in Chinese), Acta Sci. Natur. Univ. Sunyatseni 1 (1985), 116-126. [9] Z. Chen and M. Chen, "Generalized solutions for a class of operator evolution equations containing second derivatives with respect to time," (in Chinese), Acta Scien. Natur. Univ. Sunyatseni 2 (1988), 47-54. [10] Z. Chen and M. Chen, "K-monotone operator method and its applica tions," (in Chinese), J. of Appl. Math. & Comput. Math. 2 (1990), 77-84. [II] P. G. Ciarlet, The Finite Element Method for Elliptic Problems, NorthHolland, Amsterdam, 1978.
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[12] E. Conjura and W. V. Petryshyn, "Extension of nonlinear densely de fined operators, rates of convergence for the error and the residual, and application to differential equations," J. of Math. Anal. Appl. 67 (1978), 651-694. [13] J. B. Conway, A Course in Functional Analysis, Springer-Verlag, New York, 1985. [14] K. Deimling, Nonlinear Functional Analysis, Springer-Verlag, New York, 1985. [15] J. Douglas and T. Dupont, "Galerkin methods for parabolic equations," SIAMJ. ofNumer. Anal. 7 (1970), 575-625. [16] N. Dunford and T. J. Schwartz, Linear Operators, Parts I, II, and III, Wiley, New York, 1958, 1963, and 1971. [17] P. L. Duren, Theory of Hp Spaces, Academic Press, New York, 1970. [18] D. Gilbarg and N. S. Trudinger, Elliptic Partial Differential Equations of Second Order, Springer-Verlag, New York, 1977. [19] J. A. Goldstein, Semigroups of Linear Operators and Applications, Ox ford University Press, New York, 1985. [20] B. L. Guo, "Initial-boundary value problem for one class of system of multidimensional nonlinear Schrodinger equations with wave operator," Scientia Sinica, Series A 26 (1983), 561-575. [21] D. J. Guo, Nonlinear Functional Analysis, (in Chinese), Shandong Sci. & Tech. Pub., 1985. [22] E. Hille, Ordinary Differential Equations in the Complex Domain, Wiley, New York, 1976. [23] H. K. Khalil, NonHnear Systems, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ, 1995. [24] M. A. Krasnosel'skii, G. M. Vainiko, P. P. Zabreiko, Ya. B. Rutiskii, and V. Ya. Stetsenko, Approximate Solution of Operator Equations, "Nauka" Moscow, USSR, 1969. English Translation: Wolters-Noordhoff, Groningen, 1972. [25] J. G. Lei and X. D. Huang, The Projective Method for Operator Equa tions, (in Chinese), Wuhan Univ. Press, 1987. [26] R. H. Li, "On estimation of the convergence rate for the Galerkin meth od," (in Chinese), Numer. Math. 1 (1980), 14-23. [27] R. H. Li and G. S. Feng, Numerical Methods for Differential Equations, (in Chinese), 2nd edition, People's Education Pub., 1994. [28] Y. S. Li, Splines and Interpolations, (in Chinese), Shanghai Sci. &; Tech. Pub., 1983. [29] J. L. Lions, Problemes Aux Limites Dans Les Equations Aux Derivees Partielles, 2nd ed., Les Presses de l'Universite de montre'al, 1967. [30] J. L. Lions and E. Magenes, Nonhomogeneous Boundary Value Problems and Applications, Springer-Verlag, New York, 1973.
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[31] G. Nurnberger, Approximation by Spline Functions, Springer-Verlag, New York, 1989. [32] N. H. Pavel, Nonlinear Evolution Operators and Semigroups, SpringerVerlag, New York, 1987. [33] W. V. Petryshyn, "Projection methods in nonlinear numerical functional analysis," J. of Math. Mech. 17 (1967), 353-372. [34] W. V. Petryshyn, "On the approximation solvability of equations involv ing A-proper and pseudo-A-proper mappings," Bull, of Amer. Math. Soc. 81 (1975), 223-312. [35] H. L. Royden, JReai Analysis, Macmillan, New York, 1988. [36] G. Strang and G. Fix, An Analysis of the Finite Element Method, Prentice-Hall, Englewood Cliffs, NJ, 1973. [37] V. Thomee, Galerkin Finite Element Methods for Parabolic Problems, Lecture Notes in Math., 1054, Springer-Verlag, New York, 1984. [38] M. M. Vainberg, Variational Method and Methods of Monotone Opera tors in the Theory of Nonlinear Equations, Wiley, New York, 1973. [39] D. Xia, Z. Wu, S. Yan, and W. Shu, Real Functions and Functional Analysis, (in Chinese), Vols. 1 and 2, People's Education Pub., 1979. [40] K. Yosida, Functional Analysis, 6th edition, Springer-Verlag, New York, 1980. [41] E. Zeidler, Nonlinear Functional Analysis and Rs Applications: 11/A Linear Monotone Operators and II/B Nonlinear Monotone Operators, Springer-Verlag, New York, 1990. [42] Z. G. Zeng, Remarks on Strongly Monotone Operators, (in Chinese), Math. Res. Report, Vol. 17, Wuhan Univ., 1984.
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APPENDIX A Fundamental Functional Analysis
In this part of the Appendix, we summarize some basic concepts from func tional analysis, including linear topological and normed spaces, some funda mental theorems and operator theories, and weak and weak* convergences, etc., which are useful in the reader's reading of the present book. A . l Linear Topological Spaces A. 1.1 Topological spaces Definition A. 1.1. Let X be a set and r be a set of some subsets of X. r is said to be a topology if it satisfies the following properties: (i) The empty set <j> and the set X itself both belong to r. (ii) Let A be an index set. If Ga e r for any a € A then U a G ^ G a G r. (hi) If both GuG2er then Gx n G2 € r . An element of r is called an open set. {X, r } is called a topological space. Sometimes, we call X a topological space for simplicity. Definition A. 1.2. Let X be a topological space. A point x £ X is called the accumulation point of a subset fi C X if every neighborhood of x, UXJ contains at least one different point y € /x, y ^ x. The set of accumulation points of n, denoted / / , is called a derived set. The union of fi and //' is called the closure of fi and is denoted Ji = fi U /z'. Here, by a neighborhood of x, we mean a subset Ux C X that covers an open set G (in r) containing x, namely, x G G C Ux, where G e r.
289
Appendix
290
A
Definition A. 1.3. A subset F C X is said to be closed if its complement X\F is an open set. It is clear that ji is closed
<==> \i — p
<£=>
p! C p.
With a topology, the concept of convergence can be introduced. Definition A. 1.4. Let {XJ} be a sequence in a topological space X, and let xo € X. The sequence {XJ} is said to converge to xo as j —> oo, denoted Xj —►
(i —► oo)
XQ
or
lim Xj =
XQ
in X ,
j—yoo
if for any neighborhood UXo there exists an integer N > 0 such that x^ € £4 0 for all j > N. The point xo is called the Zzrrat of the sequence {x?}. In general, a limit of a sequence needs not be unique. However, if the topological space X is a Hausdorff space, namely, if it satisfies the separation axiom: for any X'0,XQ € X with x 0 7^ x0;, there are disjoint open sets G\ and 6?2 such that x 0 £ Gi and x0' € G2, respectively, then the limit of a sequence (if exists) is unique. Definition A. 1.5. Let X and Y be topological spaces, and y = f(x) be a mapping from X to Y. The mapping / : X —> Y is said to be continuous at x0 € X if for every neighborhood of yo = /(#o), denoted V^0, there is a neighborhood UXo of x 0 € X such that f(UXo) CVyo. If / is continuous at every point of X, then it is said to be continuous on X. Proposition A. 1.1. A mapping f : X -^ Y is continuous if and only if for any open set V CY, its inverse
/-1(V) = {xeX|
f(x)ev}
is an open set in X. A. 1.2 Metric spaces Definition A.1.6. Let X be a nonempty set and p(xyy) be a real-valued function defined on X x X, satisfying the following properties: (i) p(x, y) > 0 and /?(x, y) = 0 if and only if x = y; (ii) p{x,y) = p(y,x); and (hi) p(x,y)
Functional Analysis
291
Metric can be used to define open sets (i.e., to introduce a topology): A subset G C X is an open set if and only if for each x G G there exists an e > 0 such that the ball B(x,e) = {yeX
\ p(y,x) <e}
CG.
Thus, X becomes a topological space, called a metric space. In a metric space, that a sequence {XJ} converges to XQ G X as j —> oo is equivalent to p(xj, x0) —> 0 as j —> oo. Clearly, the topology induced by a metric satisfies the Hausdorff separation axiom, and so the limit of a convergent sequence is unique in X. Also, the metric function /&(•,•) is continuous on X x X. A. 1.3 Completeness Definition A. 1.7. A sequence {XJ} in a metric space X is called a Cauchy sequence (or fundamental sequence) if p(xi,Xj)
—* 0
as
z,,?—>oo.
The metric space X is said to be complete if every Cauchy sequence converges inX. Theorem A. 1.1. Every metric space X can become a complete metric space X by adding new elements in such a way that X is dense in X, i.e., for every x' G X, there exists a sequence {XJ} C X such that p(xj,x') —> 0 as j —> oo. The completion X of X stated in this theorem is unique, and is called the closure of X. A. 1.4 Separability Definition A. 1.8. Let X be a metric space and let E and /x be subsets of X. If in any neighborhood of any point x in E, there is an element of /x, then \x is said to be dense in E. Definition A. 1.9. Let E be a subset of a metric space X. If there exists a set of finitely or count ably many elements and this set is dense in E, then E is said to be a separable set If X itself is separable, then X is called a separable space. A. 1.5 Sequential compactness Definition A.1.10. Let /i be a subset of a metric space X. If every sequence {xA in p has a convergent subsequence {#&.,}, i.e., there is an x G X such
Appendix
292
A
that p{xkj,x) —> 0 as j —> oo, then the subset /i is said to be relatively sequentially compact If, moreover, the limit x is always in /x, then \x is said to be sequentially compact The space X is called a sequentially compact space if it itself has this property. Theorem A.1.2. A subset /i of a complete metric space X is relatively sequentially compact if and only if fi is completely bounded, i.e., for any e > 0 there exists a group of finitely many points, M := {xi, • • •, x n } , such that for any 1 6 / 1 , there exists a point x^ £ M satisfying p(xfc, x) < e. Here, J\f is usually called a /irate e-net with respect to /i in X. A.1.7 Linear topological spaces Definition A . l . l l . Let X be a set. Suppose that every pair of elements x, y e X can be combined by an operation, called addition, to yield a new element in X, denoted x + y. Suppose also that for every complex (or real) number a and every element x G X, there is an operation, called multiplica tion, which yields a new element in X, denoted ax. The set X is said to be a linear space (or, a vector space), if it satisfies the following axioms: 1. x + y = y + x; 2. x + \y + z) = (x + y) 4- *; 3. X contains a unique element, denoted 0, which satisfies x + 0 = x for all x e X; 4. to each x e X there corresponds an element of X, denoted —x, such that x 4- (—x) = 0; 5. a(x 4- y) = ax -h at/; 6. (a 4- 6)x = ax + 6x; 7. a(6x) = (a6)x; 8. l x = x; and 9. Ox = 0,
where a and 6 are complex (or real) numbers. If, moreover, X is a topo logical space and the operations x + y and ax are both continuous under this topology, then X is called a linear topological space (or topological vector space). A.2 Linear Normed Spaces and Inner-Product Spaces A.2.1 Linear normed spaces and their completion Definition A.2.1. A norm on a linear space X over a complex (or real) field is a real-valued function, denoted || • || or more precisely || • ||x, satisfying (i) ||x|| > 0, where the equality holds if and only if x = 0;
Functional Analysis
293
(ii) ||Ax|| = |A| ||s||; and (iii) | | * + y | | < | | * | | + ||i,||. A linear space equipped with a norm is called a linear normed space. A linear normed space is a metric space since we can always introduce a metric p(x,y) = \\x — y\\ into the space. In a linear normed space X, the norm is always a continuous function since for every convergent sequence {XJ} in X satisfying lirn^oo | \XJ - x\ | = 0, we have lim^oo \\XJ\\ = \\x\\. Definition A.2.2. A linear normed space X is called a Banach space if it is a complete metric space under the metric induced by its norm: p(x, y) = \\x-y\\. Theorem A.2.1. Every linear normed space X can become a (unique) Banach space X by adding some new elements in it. Moreover, X is dense inX. Here, X is called the closure of X with respect to the metric induced by the norm: p(x,y) = \\x — y\\. A.2.2 Inner product spaces and their completion Definition A.2.3. Let H be a linear space over a complex (or real) field. H is called an inner product space if for any two elements x and y of i7, there is a unique, associate complex (or real) number, called the inner product and denoted by (x,y) (or more precisely, by (x,y)x), such that (i) (x, x) > 0, where the equality holds if and only if x = 0; (ii) (x,y) = (y,x); and (iii) (ax + by, z) = a(x, z) + b(y, z). Let \\x\\ = (x,x) x / 2 . Then we have the Cauchy-Schwarz and triangular inequalities:
|(*,v)|
Vx,yeH.
Appendix
294
A
Definition A.2.4. An inner product space H is called a Hilbert space if it is a complete metric space under the metric induced by its inner product: p(x,y) = (x-y^x-y)1/2. Theorem A.2.2. Every inner product space H can become a (unique) Hilbert space Tl by adding some new elements in it. Moreover, H is dense inH. A.2.3 Function spaces C(ft) and L p (ft) (1
inf
{
sup
| f{x) \} ,
^oo(^) is a Banach space. Let Lp(ft), 1 < p < oo, denote the family of complex- (or real-)valued measurable functions f(x) such that \f(x)\p are Lebesgue-integrable on ft. Lp(ft) is a linear space. Equipped with the norm
o,P:={fjf(x)\pdx}
I/P
LP(Q) becomes a Banach space. In particular, when equipped with the inner product (/,0)o : = / f(x)g(x)dx, Jn L 2 (ft) is a Hilbert space, with the induced norm || • || 0 = (•, -YJ2, which turns out to be equal to the norm || • ||0,2 defined above. C 0 (ft) is dense in Lp(Sl), 1 < p < oo.
Functional Analysis
295
A.2.4 Function spaces C m (ft) and tfm(ft) (m > 1) Let C m (ft) be a subspace of C(ft), in which all the functions have continuous mth-order derivatives in the sense that (Daf) (x) € C(Q) for 1 < \a\ < m, where a = (au • • -,aN), \a\ = ax + • • • + aN, and Da = d^/dx^1 • -dx%N. It can be verified that 11/IU.oo := ll/lkoo +
\\Daf\\0tOO
E l<|a|<m
is a norm on Cm(f]!). Equipped with this norm, Cm(Q,) is a Banach space. Introduce the following inner product into C m ( 0 ) :
(f,g)m = (f,g)o+
(Daf>Da9)o>
E l<\a\<m
and then denote the closure of C m ( 0 ) , taken under this inner product, by Hm(Q,). i/ m (ft) is a Hilbert space. It contains new elements that are not in C m (fi), which are equivalent classes of Cauchy sequences (denoted {{fj})) under the norm || • || m induced by the inner product (•, ) m . Since
ll/«-/ilL = {ll/«-/il£+ E
ll^-^llol
l<|a|<m
^ 0
'
(t,j-+oo),
it is clear that {fj} and {Dafj}, 1 < |a| < m, are all Cauchy sequences in Z/2(n). Since Z/2(ft) is complete, there exist f(x) and fa(%) in I/2(ft)> 1 < H < ra, such that ||/4-/||0-,0
and | | Z ^ - / a | | o ^ O
(i-oo).
These / and fa are uniquely determined by the equivalent classes ({fj}}, and is independent of the selection of {fj}. Indeed, all these fa are uniquely deter mined by / , which by nature is the uniqueness of the generalized derivatives (see Appendix Section B.3 below). / a is usually called the ath-order strong generalized derivative of / , also denoted by fa — Daf € L2(Q), 1 < \a\ < ra. Thus, every element / G Hrn(Q) corresponds to a function f(x) e L 2 (H) which has up to mth-order strong generalized derivatives f&_= Daf € £2(ft), 1 < |a| < m, namely, there exists a sequence {fj} C Cm(Q) such that .lim | | / , - - / | | 0 = 0
and
.lim \\D"fj - / a | | 0 = 0 .
296
Appendix A
Moreover, two different functions in Hmftl) correspond to two different func tions in L L22(Sl). (Q). Hence, we may think of Hm(Sl) as a subspace of L2(Si) (Sl) concon sisting of all functions that have up to mth-order strong generalized deriva product tives (these derivatives also belong to L2(Sl)), with the inner pro< •_±1
_r
_n
r.
J.:
J.U_J.
T
^.„
J-U
1
(/,). + E (/,<7L==(/,)„ (/,)„+ E l<\a\<m
a
~+
~
~
^ : ~ ~ ^ \
J«„:,„*
(V/>irg) (^ /.^)o> ( ^aa/>^)o> / > ^ ) 0,,
a
where both D ff and and LPg LPg D g are are strong strong generalized generalized derivatives. derivatives. HP(Sl) HP {it)) be the closure of CP(Sl) CP(Si) = Cb(fl)C\C Cb(O)nCmm(Sl) (Sl). Then Let HP(Q) CP(Q) (H) in Hm{n). all the functions / in HP(Sl) and their generalized derivatives Daf, 1 < |a| < TO-- 1, 1, are are equal equal to to zero zero (in (in the the generalized generalized sense) sense) on on the the boundary boundary dSl dSl \a\
fr
11
V/GZ/O V V/GZ/O / e Z Z 0 1 ( «^)^))-
It It follows fonows from from the ine Poincare Pomcare inequality inequality that mat
9)^\lk>£-X £—J \dx dx J k
k 0
is H$(Sl), satisfying iss an an inner inner product product of of H£(Sl), H£(Sl), satisfying 1 22 ,/>> ||/||?2 < (1 +N~ d)) {f,f) < / , /1,} , , v / e H&Sl) H'(Sl).■ < / , / ) , < ll/H +N-'d lence, the new inner product (•, •), Hence, )xx and the original inner product (•, •)2 are quivalent. equivalent. WhenTO> 1, observe that if / € HP(Sl) Daf e HP {SI) then D°f € H^(S1), \a\ < m - 1, so that by repeatedly applying the Poincare inequality one can verrfy 1 a fncxf a a a tViat na„\ ica limIr>\ „ u ; „ u :is equivalent : 1 * ■ nr tnat V th&tJ2: T Vl(Di-™ f,D(D g)f, D g) is an. inner inner ™.^,J,,„f product „t of HP (SI), .which to the original inner product. ' 'v
J-j u\J
uxxuu
*^J •*- vl/V/Oiuv/vli V i
Functional Analysis
297
A.2.6 Semi-norms and topologization of spaces C7n(ft) (0 < m < oo)
and Cg°(ft) Definition A.2.6. Let X be a linear space. A real-valued function p(x) on X is called a semi-norm if it satisfies the following properties: (i) p(x) > 0; (ii) p(Xx) = \X\p(x)] and (hi) p(x + y)
\
max
keA
pk(x) < e } ,
and introduce a topology into X as follows: A subset G C X is defined to be open if and only if for every x € G there exits an No{Aye) such that x + No(A, e) C G. Thus, X becomes a topological space, and each No(Ay e) is an open set containing the zero element, 0. Consequently, x + No(A, e) is an open set containing x. Note that all functions pk(x) are continuous. Suppose that the given set of semi-norms {pk{')} is complete, in the sense that for any XQ ^ 0, there exists a pk(-) such that pk(%o) ^ 0. In this case, the topology introduced above satisfies the Hausdorff separation axiom. Note that if X is a linear topological space generated by the semi-norms {Pk()} m the aforementioned manner, then the convergence Xj —> x (j —> oo) in X is equivalent to lirn Pk(xj — x) = 0,
k = 1,2, • • • .
Let ft C RN be a (bounded or unbounded) region. Let also /(•) be a complex- (or real-)valued function defined on ft. Then Cm(ft) = { f(x) |
f(x) is m—times continuously differentiate o n H }
m
c~(n) = n£^c (n), C™(ft) = { f(x)
e C°°(n) | support of / is inside Q and bounded }
are all linear spacas. For simplicity, we usually denote C(£l) = C°(Q). Let {ftk} be a sequence of subregions of Q, which increasingly converges to ft in the sense that fti C ft2 C • C n and for any bounded closed set F C ft, there exists an n > 1 such that F C ftk for k > n. Suppose also that ftk CC ft] here and throughout,
298
Appendix
ACCB A CC B means A is bounded and AcB. into C Cmm(Sl) (Q) by (£l) := pkr(f):=max PkAf) '■=max max Pk r(f)
A
semi-norm Then, we introduce a semi-non
a f) (x)(x)|, I, *k=l,2,--, m sup 0 0, ,l •l, ,•---,-,m sup I (D I (ZT/) *= =1 ,12, ,2- ,- - -, , r r= =0,1, , m, ,
\<*\
where rr < < oo if m = oo. We furthermore introduce a topology into C m (ft) (0) by using this semi-norm sequence, such that it becomes a linear topological -+ f (j -> -+ oo) in Cm(S2) (ft) space in which every convergent sequence /fj, -> (Q) is equivalent to that for any a satisfying \a\ < m (when m -= oo, |<x| |Q| < oo), a {{EPfj) (x)} converges uniformly to (D (D°f) n*k as the sequence {(LPfj) f) (x) on each Q j -^oo,k > o o , k== 1,2, 1,2, C Space 0°°(ft) space C$°(n) OQ (MJ can can become Decome aa topological topoiogicai space space in m the me following lonowing way. way. For rui any subregion K CC Q, we first observe that any subregion K CC fl, we first observe that 2>KK(ft) Cg°(n) |I SU supp K } T> (Sl) = { /(x) f{x) €e Cg°(fi) PP (/)
cz°(ti) <70°°(«) ==U u * £K>v*K((n), «), where the union is taken over all possible K CC O. fl. Then, it is clear that VK(Q) can be topologized, and so become a (locally convex) linear topolog X>A-(n) snace by hv using nsin
Ssup U
a (£>"/) (*) h|, | (D (x)\, P K ^ f)/ ; W
0< a K m x6A0<|«|<m xeK 0<|a)<m xeK
m == = u0,1, m m > l->'''• • -• . .
Using Cf?(Q) = U KVK(tt) and the topology of VK(Q), the space C§°(0) can be appropriately topologized [40] to become a (locally convex) linear topological space, denoted V(Q). In V(Q), the convergence of a sequence I{/,•} f.^ to t o /// fl.s - > no ennivalpnt to: t
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In particular, if X 0 such that ||Tx||x2<M||x||Xl,
VXGXL
The infimum of the values of M that satisfy the above inequality is called the norm of the linear operator, denoted ||T||, which satisfies ||T||=
sup
||TS||JC9=
ll*|| X l
sup
\\Tx\\X2.
IMIx!=i
A linear operator is continuous at a point if and only if it is continuous everywhere, and it is continuous if and only if it is bounded. The range 1Z(T) of a linear operator T : X\ —» X2 is a linear subspace of X2, which becomes a linear normed space if it is equipped with the norm || • ||x 2 - For any y € 7£(T), its pre-image is the set T'1y
= {xeX1\
Tx = y}.
If T is one-to-one, then for each y G 7£(T), the pre-image T~ly has only one element and, in this case, T _ 1 defines a linear operator from H(T) to X\, called the left inverse operator of T. It satisfies T~1Tx 1
TT~ y
= x,
VXGXI,
= y,
V y € K{T).
A linear operator T : X\ —► X2 has a left inverse operator if and only if Tx = 0 =>
x = 0.
If the left inverse T - 1 of T exists and is a continuous operator from 7£(T) to X i , then T is said to have a continuous left inverse operator. A linear operator T has a continuous left inverse operator if and only if there is a constant C > 0 such that ||Tx||x2>C||x||Xl,
Vxeli.
If the left inverse T~1 of T exists and its domain is the entire space 1Z(T) = X2, then T is said to have an inverse operator, if the inverse T _ 1 of T exists and is continuous, then T is said to have a continuous inverse operator.
Appendix
300
A
Definition A.3.2. Let the domain V(T) of a linear operator T be a linear subset of Xu and the range K(T) C X2. The linear operator T is called a closed operator if
h}cP(T) lim Xj = x lim
TXJ
=y
) in Xi
x € V(T)
and
y = Tx.
in X2
A linear operator T is closed if and only if its graph
G(T) = {{x,Tx)\
xeP(T)}
is a closed subspace of X\ xX2- In general, a closed operator is not necessarily continuous. However, under very mild condition this is true (see the Closed Graph Theorem, Theorem A.3.3 below). On the other hand, if the domain V{T) of a linear continuous operator T : V(T) —> X2 is a closed subspace of Xi, then it is a closed operator. A.3.2 Open mapping theorem and its corollaries Definition A.3.3. A Banach space X is said to have the Baire property if any countable family of closed sets {Fj} satisfying U ^ 1 F J = X has at least one closed set that contains a ball in the space. Theorem A.3.1. (Open Mapping Theorem) Suppose that the domain T*{T) of a closed linear operator T is a linear subset of a Banach space X\, with the range 1Z(T) equal to the entire Banach space X2. Then for any e > 0, there exists an 77 = rf(e) > 0 such that the operator T : V(T) -► U{T) maps the set U£ to the set T(Ue), where U£ is the intersection of V(T) and the ball B1(0,e) = {x€X1\
\\x\\Xl<e},
and T(Ue) contains the ball
B2(o,v) = {y ex2 \ |MU 2 <77}. This theorem states that for any open set G c l i , the operator T maps the set V(T) n G to an open set in X 2 . Theorem A.3.2. (Inverse Operator Theorem) Suppose that the operator T satisfies all the properties stated in Theorem
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301
A.3.1 and, in addition, is one-to-one. Then the inverse T1ofT is a continuous linear operator.
exists and
Theorem A.3.3. (Closed Graph Theorem) Let X1 and X2 be Banach spaces and T : V(T) = Xx —> X2 be a linear operator. If the graph ofT is a closed set in X\ x X2, then T is continuous. An equivalent statement of the above closed graph theorem is that if X\ and X2 are Banach spaces and T : V(T) = X\ —► X2 is a closed linear operator, then T is continuous. A.3.3 Strong extensions of linear operators Let X\ and X2 be Banach spaces and T : X\ —» X2 be a linear operator, with domain V(T) being a linear subset in X\. Consider the following two cases: (a) There is a constant M > 0 such that \\Tx\\X2 < M\\x\\Xl
,
VxeP(T),
namely, T is a bounded linear operator from T>(T) C Xi to X2. In this case, there exists a bounded linear operator T from T)(T) to X2, such that Tx = Txy
V x € V{T)
and
sup
| \Tx\ \x2 =
sup
| \Tx\ \x2 •
This operator T can be constructed as follows. For any x G T>(T), pick a sequence {XJ } C X>(T) satisfying lim j ^oo x j — ^ in Xi. Then let Tx — lim j-yooTxj in X 2 . By the boundedness of T, {TXJ} C X2 is a Cauchy sequence, and so has a limit in the Banach space X2. The boundedness of T also implies that this limit is independent of the selection of the sequence. Hence, the operator T so constructed is the one expected. This T is unique, called the norm-preserved and continuous extension of T. If X2 is a number field, i.e., if T is a linear functional, and if X± is a Hilbert space, then the Riesz Representation Theorem (see Appendix A.5.2 below) can be used to extend T to the entire space X±. This extension is also unique (see Appendix A.5.2 below). If X\ is a Banach space, using the Hahn-Banach Theorem (see Appendix A.6.1 below), we can also extend T (but this extension is not unique, see Appendix A.6.1 below). (b) Suppose that {*,•}<= P(T)
.limx^O lim jf-KX)
TXJ
\
inXi
I
= y in X2 )
^
y = 0
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302
A
In this case, the closure of the graph G(T) C X\ x X2 satisfies
(0,y)eG(TJ
=>
y = 0.
Define a linear operator T whose domain T>(T) is the projection of G(T) onto Xi, as follows. For every x e T>(T), there exists a y e X2 such that (x,j/) e G{T). Let Tx = y. Then the condition satisfied by G(T) guarantees T be single-valued. The linear operator T so defined has a graph G(T) = (2(2^ Hence, it is a closed extension of T. P ( T ) is dense in T>(T). The operator T so constructed is called the minimal closed extension (or strong extension) ofT. A.3.4 Example: Strong extensions of differential operators The classical differential operator D := d/dt is a linear operator from £2(0,1) to £2(0,1), with domain V(D) = {x{t)eL2{0yl)
I ^€^(0,1),
dx(t)/dteL2(0,l)}.
Operator D satisfies the conditions described in Case (b) above. Indeed, let {XJ} C V{D) be such that Xj -> 0
dx'
— l ^y
and
(j —► 00)
in
L2(0,1).
Then for any <£ e C£°(0,1), / cf>(t)y(t)dt= lim / Jo J^°°Jo
= - lim [* ^ xAt) dt = 0 . j-+oo J0 dt
Since C£°(0,1) is dense in L 2 (0,1), this result also holds for <> / e L 2 (0,1). Hence, letting > = y leads to y = 0, and so operator D satisfies the conditions stated in_Case (b) above. As a result, D has a minimal closed extension, denoted D. A function x(t) € £2(0,1) is said to have a strong generalized derivative, Dx, in L 2 (0,1) if x(t) belongs to the domain V(D) of the minimal closed extension of D. In this case, there exists a sequence {XJ } c I/ 2 (0, l j n C ^ O , 1) with {dxj(t)/dt} C L 2 (0,1), such that lim Xj = x
and
lim -—- = Dx
in L 2 (0,1).
We next consider the following two-point boundary value problem: (Lx) (t) := x"(t) + a(t)x'{t) + b(t)x(t) = f(t), x(0)=0, x(l)=0,
0 < t < 1,
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where a{t) € ^ ( [ 0 , 1 ] ) , b(t) e C([0,1]), and f(t) e L 2 (0,1). The above operator L, with the two-point zero boundary conditions, is a linear operator from L 2 (0,1) to 1/2(0,1), with domain T>(L) = CQ (0,1). The linear operator L so defined satisfies the conditions posed in case (b) above. Indeed, we can let {XJ} C Cg(0,1) be such that lim Xj = 0
and
lim LXJ =y
in L 2 (0,1).
Forany^€C0°°(0,l), / 4>{t)y{t) dt = lim /
and
lim LXJ = f
in L 2 (0,1).
Such a function is said to be a generalized solution (or strong solution) of the original two-point boundary value problem. If, for each / 6 L 2 (0,1), the generalized problem is solvable with a unique solution, then according to the Inverse Operator Theorem (Theorem A.3.2), L - 1 is a continuous linear operator. Hence, the solution of the above generalized equation depends continuously on the function / € L 2 (0,1). A.4 Uniform Boundedness Theorem A.4.1 Uniform boundedness theorem Theorem A.4.1. Let {Tj} be a sequence of bounded linear operators from a Banach space X\ to a linear normed space X 2 . If sup ||T.x||
VXGXI,
Appendix
304
A
then sup ||T,-||
in I 2 ,
then T is a bounded linear operator from X\ to X 2 . Proposition A.4.2. Let {XJ} be a weakly convergent sequence in a Hilbert space H, i. e., for every x G H, lim (x, Xj)H = (x, xo)H ,
xo G H.
Then {XJ} is bounded, i.e., there is a constant C > 0 such that for all j = 1,2, •••.
\\XJ\\H
< C
Here, XQ is called the weak limit of the sequence {XJ}. For each y G H, {-,y)H is a bounded linear functional on H with norm equal to ||2/||i/. It follows from the Riesz Representation Theorem (see Ap pendix A.5.2 below) that for any bounded linear functional £(-) on H, there exists a unique y G H such that £(z) = (x,y),
VxeH
and
||€|| = | M | H .
Hence, the convergence of the sequence {XJ} C H to XQ G H is equivalent to that for any bounded linear functional £{•) on # , lim
£(XJ)
= £(x0) .
Note that the concept of weak convergence can also be introduced in a Banach space, in which every weak convergent sequence is also necessarily bounded (see Appendix A.7 below). A.4.3 Banach-Sake theorem Theorem A.4.2. Let {XJ} be a weakly convergent sequence in a Hilbert space H, with a weak limit x0 G H. Then there exists a subsequence {#*. } of {XJ} such that x
ki
+ ' " ' + SCfc: —>
XQ
(j —► 00)
in
H.
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A.5 Riesz Representation Theorem A.5.1 The shortest distance problem Let K be a closed convex set in a Hilbert space # , and let XQ G H. The shortest distance problem is to find a x G K such that | | £ - * o | | f f = inf Hx-xolljf . x€K
This problem is equivalent to finding an x G K such that (xo — x, x — x)H < 0,
V x € K.
Theorem A.5.1. The above shortest distance problem is uniquely solvable. Theorem A.5.2. (Orthogonal Projection Theorem) Let L be a closed subspace of the Hilbert space H and L1- be the orthogonal complement of L, i.e.,
L± = {yeH\
(y,x)H=0,VxeL}.
Then H can be decomposed as a direct sum of L and iA: H = L 0 L±. Corollary A.5.1. In a Hilbert space, a subspace L is dense in the space if andonlyifL1-{0}. For a subspace L of a Hilbert space, LL is always closed, and (L1-)
= L.
A.5.2 Riesz representation theorem Consider the following problem: Let £(•) be a bounded linear functional on a Hilbert space H. Find a,n x e H such that (x, x)H = £(x),
VxGijT.
When if is a real Hilbert space, this problem is equivalent to finding an x G H such that J(x) = inf J[x), x£H
where J(x) — \\x\fH —2£(x). A necessary condition for x G / / to be a solution is \\X\\H = |K||. If a solution exists, it is unique.
306
Appendix
A
Theorem A.5.2. (Riesz Representation Theorem) For any bounded linear functional £(•) in a Hilbert space H, there is a unique x e H such that £{x) = (x, x)H , V x e H, with\\e\\ = \\x\\H. A bounded linear functional £(•) in a subspace L of a Hilbert space if can be continuously extended to the entire space H while preserving the norm. We can follow the procedure described in Subsection A.3.3 above to extend £ to the closed subspace L, so that by the Riesz Representation Theorem there exists a unique x £ L such that £{x) = (x, x)H ,
VxGL.
This formula can be used to define £(x) for all x € H. A.5.3 Inflexibility of Hilbert spaces All the bounded linear functionals £(-) in a linear normed space X constitutes a linear space. Equipped with the norm
||*||= sup
K(x)|,
||*||tf
it becomes a Banach space, called the dual space of X, denoted X* (or, sometimes, X1). The Riesz Representation Theorem establishes a one-to-one correspon dence, r, between a Hilbert space H and its dual H*: £(x) = (x,x)H,
Vxeff
<=>
X = T(£),
£ =
T-\X).
This r is norm-preserving and anti-linear, that is,
11*11 = I|T(0I|,
v*eff*,
and r
( a ^ + 64)
=
ari^)
+ 6r(£ 2 ),
V * x ,£ 2 e if* ,
where a and 6 are (complex) constants. Introduce an inner product into H* by {iu^)H.={r{l2\r{h))H,
V£ue2eH*.
Then the norm induced by this inner product is the original norm, || • \\HHence, the dual space of a Hilbert space is also a Hilbert space.
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The dual space H** = (#*)* of the dual space H* of a Hilbert space H is an isometric isomorphism of H, namely, there is a one-to-one, innerproduct-preserving, linear correspondence, T', such that for every I' G iJ** and x G H, X = T'(£')
*=>
£\£)=£(x)y
VfGff*.
So, we can identify H** = if, which is the reflexibility of a Hilbert space. A sequence is said to be weak-relatively sequentially compact if its every subsequence contains a weakly convergent subsequence. Proposition A.5.1. A sequence {XJ} in a Hilbert space H is weak-relatively sequentially compact if and only if {XJ} is bounded. A.5.4 The Lax-Milgram theorem Definition A.5.1. Let H be a complex (or real) Hilbert space. A complex(or real-)valued function a(x, y) defined on H x H is called a bilinear form if it is linear in the first variable and anti-linear in the second, i.e., a{cixi + c 2 x 2 , y) = c\a(x\y y) + c2a(x2, y), a{x,cxyi + c 2 y 2 ) = c1a(x,y1) + c2a{x1y2). A bilinear form a(x, y) is said to be bounded if there is a constant M > 0 such that |o(x>y)|<M||x||H|M|/f, Vx,yeH. The variationai problem: Let a(-, •) be a bounded bilinear form on H x H and let £(<) € AT*. Find & y € H such that a(x,y) = £(x),
V
xeH.
For each fixed y € H, a(-,y) is a bounded linear functional on # . The Riesz Representation Theorem implies that there is a unique Ty G H such that a(x,y) = {x,Ty)H, Vx G# . Similarly, there is a unique r(£) G ff such that <(a;) = (x,T(€)) j / >
Vxeff.
Hence, the above variational problem can be rewritten as Ty =
T(£)
.
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308
A
Here, the operator T : H —> H is linear and bounded. Theorem A.5.4. (The Lax-Milgran Theorem) Let a(-, •) be a bounded bilinear form defined on H x H. Ifa(-,-) is positive definite, i.e., if there is a constant Co > 0 such that a(x,x) >C0\\x\\2H,
M
xeH,
then for every £(•) e H*, there exists a unique y € H such that a(x, y) = £{x),
V x GH .
A.6 Hahn-Banach Extension Theorem A.6.1 Hahn-Banach theorem and its corollaries Theorem A.6.1. A bounded linear functional £Q(-) defined on a subspace L of a linear normed space X can be extended continuously to the entire space while preserving the norm, i.e., there is a bounded linear functional £(•) satisfying £(x) = £0(x) for all x e L and \\£\\ = \\£0\\. Corollary A.6.1. For any nonzero XQ 6 X, there exists a bounded linear functional £{•) satisfying £{XQ) = \\xo\\x and ||£|| = 1. Corollary A.6.2. For any closed subspace L C X and XQ € X\L, exists a bounded linear functional £{-) satisfying ||«|| = 1,
*(x0)=inf
Ik-^olU,
£{x) = 0,
there
VxeL.
Let X* be the dual space of X. The family of all the £(•) e X* that satisfy £{x) — 0 for all x G L C X is called the orthogonal complement of L, and is denoted LL. Corollary A.6.2 implies that an element x belongs to a closed subspace L if and only if £{x) = 0 for all £ e LL. This is a generalization of the formula (LL) = L for a closed subspace L in a Hilbert space setting. The orthogonal complement of C C X* is given by C1 = {xeX
\ £(x) = 0, V £ e C } .
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A.6.2 Reflexive Banach spaces Proposition A.6.1. Let X be a linear normed space and X** be the dual space of its dual space X*. The operator rf defined as follows is a one-to-one, norm-preserving, linear operator: For x € X and £' e X**, r\x)
=e
4=>
£'{£) = £{x),
Vlel*.
This proposition implies that X can be considered as a subspace of X**. In general, X is a strictly proper subspace of X**. But if X = X** then X is said to be reflexive. A bounded subset in a reflexive Banach space is weak-relatively sequen tially compact (see Appendix A.7.3 below). A.7 Weak and Weak*-Convergence A.7.1 Weak convergence and weak completeness Definition A.7.1. Let X be a linear normed space. A sequence {XJ} C X is said to be weakly convergent in X if there exists an XQ 6 X such that lim e(xj) = £{x0),
V £ e X*,
j—>oo
where xo is called the weak limit of the sequence. The weak limit, if exists, is unique. The weak convergence is denoted by Xj w-^
XQ
(j —►
OO)
or
w — lim Xj =
XQ
in X .
j—*oo
Theorem A.7.1. In a linear norrned space X, a sequence {XJ} is weakly convergent if and only if (i) it is bounded, i.e., there is a constant C > 0 such that \\XJ\\X < C for all j — 1, 2, • • •; and (ii) there exists an XQ e X such that the limit shown in Definition A.7.1 holds on a dense subset of X*. Proposition A.7.1. A reflexive Banach space is weakly complete, namely, every weak Cauchy sequence in the sense of | e(xi)
- £{xj)
I— 0
(i,j
-oo),
V I G T ,
is weakly convergent. In particular, every Hilbert space is weakly complete.
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310
A
A.7.2 Weak*-convergence and weak*-completeness Definition A.7.2. Let X be a linear normed space. A sequence {£j} C X* is said to be weak* convergent if there exists an £o G X* such that lim £j(x) = £0(x),
Vx€l,
j—>oo
where £o() is called the weafc* limit of the sequence. The weak* limit, if exists, is unique. Theorem A.7.2. Let X be a Banach space. A sequence {£j} C X* is weak* convergent if and only if (i) it is bounded, i.e., there is a constant C > 0 such that \\£j\\ < C for all j = 1,2,. ••; and (ii) there exists a dense linear subset L in X such that the limit lim j->oo £j (#) exists for all x G L. Condition (ii) above can be replaced by the existence of a dense linear subset L in X such that lim
\£i{x)-£Ax)\
= 0,
VxeL.
Proposition A.7.2. The dual space X* of a Banach space is weak* complete, namely, if {£j} C A"* is a weaic* Cauchy sequence then there exists an £o € X* such that lim £Ax) =£0(x), Vx e X . A.7.3 Weak* and weak sequential compactness Definition A.7.3. Let X be a linear normed space. A subset S of the dual space X* is said to be weak* -relatively sequentially compact if every sequence in S contains a weak* convergent subsequence. Proposition A.7.3. Let X be a separable Banach space. A subset S of its dual space X* is weak*-relatively sequentially compact if and only if S is bounded. Definition A.7.4. Let X be a linear normed space. A subset JJL C X is said to be weak-relatively sequentially compact if every sequence in [i contains a weakly convergent subsequence. Proposition A.7.4. Let X be a separable and reflexive Banach space. A subset f.c C X is weak-relatively sequentially compact if and only if \i is bounded.
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A.8 Dual and Adjoint Operators and Their Weak Extensions A.8.1 Dual and adjoint operators of bounded linear operators Let X and Y be complex (or real) linear normed spaces, and T be a bounded linear operator from £>(T) = X to Y. Define an operator T" \Y* —> X* by (x, T'h) = (Tx, h),
V h e Y* ,
x e l ,
where (x.T'h) represents the value of the linear functional T'h e X* eval uated at x € X, and (Tx, fe) is the value of the linear functional h € Y* evaluated at Tx £ Y. V is a bounded linear operator from V{V) = Y* to X*, with | IT"11 = ||T||, and is called the dual operator of T, which is sometimes denoted as T*. Let Hi and H2 be both complex (or real) Hilbert spaces, with inner products (-,•)#! a n d (*> *)H2 > respectively. Let T be a bounded linear operator from Z>(T) = Hi to # 2 . Define a linear operator T* : £>(T*) = H2 -> Hi by (x,T*y)
=(Tx,y)
,
VyeH2,
xeHi.
Then T* is a bounded linear operator, with ||T*|| = ||T||, and is called the adjoint operator of T. Let Ti and T2 be bounded linear operators, both map from Hi to H2, where Hi and H2 are complex Hilbert spaces, and let ci and c2 be complex numbers. For dual operators T[ and T^ we have (ciTi + c a T a J ^ c i T Z + caT^; but for adjoint operators T* and T%, we have (ciTi + c 2 T 2 ) = ciT* + C2T2 . A.8.2 Adjoint operators of linear operators in Hilbert spaces Let Hi and i7 2 be Hilbert spaces and T : H\ —» iT2 be a linear operator, with domain X>(T) being a linear subset in H\. If X>(T) = Hi then the adjoint operator T* of T can still be defined as discussed in Subsection A.8.1 above, namely, y 6 V(T*) C H2, T*y = x if and only if there exists a unique x £ Hi such that (x',x) = (7V,y) for all x' e V(T). Also, P(T) = Hx is a necessary condition for the existence of the adjoint operator T*. Moreover, the adjoint operator T*, if exists, is a closed operator.
312
Appendix
A
A.8.3 Closed extension of linear operators in Hilbert spaces Let Hi and H2 be Hilbert spaces, and T : V(T) C Hi -► H2 be a linear operator. Let also T be a linear operator from V(T) C H2 to ffi that is formally adjoint with T, denoted T A T, namely, (Tx, y ) ^ = (x, f y)^
,
V x e P(T), y € P(f).
If P(T) = F 2 , then f has an adjoint operator T*, which is the closed exten sion of T. A.8.4 Weak extension of differential operators Let ft C RN be a bounded region. Consider the differential operator (Lu)(x):=
J^
a>cc{x)(Dau)(x),
xeQ,
\a\<m
where aa(x) € C^(Q) operator
with |a| < m. Consider also the associate differential
(L<*>«)(x) := 2
(-l) W (£> a (oaf))(a:),
x€ n.
|a|<m
View both L and l/*) as operators from L2(Q) to itself, with domains
v{L) = {ue cm(Q)nL2(n) | Lu € L
2(n)}
and V(L^)
= C™(ft), respectively. Using integral by parts, we have
(Lu,v)
=(u,L^v)
,
V^D(L),
V€D(LW).
This implies that L and //*> are formally adjoint: L A !,(*). Since Q n (Q) = L 2 (ft), the adjoint of £,(*> exists: (L(*>)* = L, which is a closed operator. A function u e L2(Q) is said to be weakly operated by L, and weakly satisfies Lu = / e L2(f2), if w G P(L) and L^ = / , or equivalently,
( / '^(n, = (tt'L(*MLa(n).
v« € c^(n).
In particular, if L = D a , a function w £ L 2 (ft) is said to have a weak generalized derivative Dau = f if u is in a weakly extended domain of Da and weakly satisfies Dau = f e L2(Q), namely,
^ v ) i 2 ( , ) = (- 1 ) |Q| ("'^) i2(n) >
v„€cnn).
Functional Analysis
313
A.9 Linear Equations in Hilbert Spaces A.9.1 Linear compact operator equations Let H be a Hilbert space, with inner product (•, -) H and norm || • ||#, re spectively, and let A : V{A) = H —» H be a linear operator. Consider the solvability of the linear operator equation
(I-A)x
= f,
/eff,
(a)
where I is the identity operator. If A is a contraction operator, i.e., with \\A\\ < 1, then for any / e H, this equation always has a unique solution in H given by
x = (i-A)-if,
with
IMIH
^(i-Piir'ii/iii*-
We only assume that A is a compact operator, namely, it maps a bounded set to a relatively compact set in H. Consider also the adjoint operator equation {I-A*)y = g, g€H, (b) where A* is the adjoint operator of A. About the solvability of Equation (a), we have the following three basic results (called the Fredholm First, Second and Third Theorem, respectively). Theorem A.9.1. Let A : H —► H be a compact linear operator. (i) Equation (a) is uniquely solvable for an arbitarily given f e H if and only if Equation (b) is so for an arbitrarily given g G H. (ii) Equation (a) (or Equation (b)) is uniquely solvable for an arbitrarily given f e H (or g € H) if and only if the corresponding homogeneous equation (I-A)x =0 (or (I-A*)y = 0) has only a zero solution. (iii) In the case that equation (I — A)x — 0 only has a zero solution, the inverse operator (I — A)'1 exists on the entire space H and is bounded, so that the solution x e H of Equation (a) satisfies \M\H
Appendix
314
A
solutions there are only finitely many that are linearly independent. In this case, equation (I - A*)y = 0 has the same number of linearly independent solutions. Theorem A.9.3. Suppose that A : H —» H is a compact linear operator. Then Equation (a) is solvable if and only if the given f e H is orthogonal with all the solutions of equation (I - A*)y = 0. In this case, Equation (a) has one, and only one, solution x € H that is orthogonal with all the solutions of equation (I — A)x = 0, which satisfies \\x\\H < C\\f\\H for a constant C > 0, independent of the given f G H. A.9.2 Eigenvalues of compact linear operators Consider the following operator equation: (XI-A)x
= f,
f€H,
(c)
where A is a complex parameter. If for an arbitrarily given / G H, Equa tion (c) has a unique solution corresponding to a complex value of A, and (XI — A ) - 1 is bounded, then this A is called a regular value of A. If, corre sponding to a complex value of A, the homogeneous equation (AJ — A) x = 0 has nonzero solutions, then this A is called an eigenvalue of A, while each cor responding nonzero solution is called the eigenfunction associated with this A. The maximum number of linearly independent eigenfunctions is called the geometric multiplicity of the corresponding eigenvalue A, which can be either finite or infinite. In general, it is quite possible that there exists a number A for which (XI - A)"1 exists but is not everywhere defined in H. However, if A is a compact linear operator, this is impossible. In this case, it is also impossible to have an infinite geometric multiplicity (as shown in the following theorem). Theorem A.9.4. Let A : H —» H be a compact linear operator. (i) If A ^ 0, then X is a regular value of A if and only ifX is not an eigenvalue of A. (ii) If A ^ 0 is an eigenvalue of A, then the geometric multiplicity of X is finite; X is the eigenvalue of the adjoint operator A* of A, with the same geometric multiplicity as X. (iii) If X ^ 0 is an eigenvalue of A, then Equation (c) is solvable if and only if the given f € H is orthogonal with all eigenfunctions associated with the eigenvalue X of A*; in this case, Equation (c) has one, and only one, solution that is orthogonal with all eigenfunctions of A associated with X. (iv) The family of eigenfunctions corresponding to different eigenvalues of A are linearly independent.
315
Functional Analysis Analysis
The following is usually called the Fredholm Fourth Theorem. Theorem A.9.5. Let A : H -» H be a compact linear operator. For any constant M > 0, there are only finitely many eigenvalues of A that are located outside the disk of radius M centered at zero. Consequently A either has finitely many eigenvalues or has countably many eigenvalues converging to zero. According to this theorem, if a compact linear operator A has nonzero eigenvalues, then they can be arranged in a decreasing order in absolute values: .•••• Ai, ••• , A nn , .••
| A nn | > | A nn ++ n + i
VV=l,2,..• •
which can be a finite or infinite sequence of ordering, and the number of appearance of any particular eigenvalue in this ordering is equal to its geometric multiplicity. If this sequence of ordering is infinite, then lim n_+oo An = 0. Also, the eigenfunctions associated with the above sequence of ordering can be chosen such that they are all linearly independent. The above results can be directly extended to Banach spaces. As a special case, if the compact linear operator A ^ 0 is self-adjoint: A = A*, then the above sequence of ordering of eigenvalues and their corresponding eigenfunctions, Ai, A i , ••• • Ann ••• ^1 j
' ' ' ■> ^"n 5
will be nonempty, where all the eigenvalues are real, and the eigenfunctions can be so chosen that they constitute an orthonormal basis of the Hilbert space H: (en,e ( e n , emm)^=6 ) ^ nrn = ,6 n m , V n , m = 1,2,•.. 1,2,•.. , where 6nm is the Kronecker delta symbol (6nm — 1 if n = m, and = 0 if n 7^ m). Theorem A.9.6. (Hilbert-Schmidt Theorem) Let A: H -* H be a nonzero, self-adjoint, compact llnear operator. Then for any f e H, Af has a convergent Fourier series expansion by an orthonormal basis {en} ofH: oo
oo
Af = y ^ ( A / , e n ) ^ e n = y ^ A n ( / , e n ) j j e n . n=l
n=l
316
Appendix
A
Moreover, if A = 0 is not an eigenvalue of A, then every f € H has a convergent Fourier series expansion by this orthonormal basis: oo
/ = H(/>en)„en. 71 = 1
APPENDIX B Introduction to Sobolev Spaces
In this part of the Appendix, we include a brief introduction to the theory of Sobolev spaces, which has been applied frequently throughout the book. B . l LP(Q) Spaces B . l . l Lp(Q) (1
,
= inf sup \u(x)\, A xen\A
l
Vw€Lp(l]),
Vu e
LQO(O)
,
where A is any subset of Q with zero measure. Let also q be the adjoint index of p, satisfying p~l + q~x = 1 for 1 < p < oo. Then we have the following two inequalities:
317
Appendix
318
B
The Holder Inequality: For any 1 < p < oo, u(x)eLp(£l)
and
v(x) G L g (fi)
=>
u(:r>(x) G Li(Q) ,
with / | u(x)v(x) I dx < |M|o lP ,nlM|o ig> n •
Jn
The MinJcowsii Inequality: For any 1 < p < oo and u(x),v(x) G I/ P (fi), ||u + v|| 0|P ,n < IM|o,P,n + IM|of„,n • Lp(ft) (1 < p < oo) is a complete normed linear space, i.e., a Banach space, under the norm || • ||o,P,n- When p = 2, L2(f£) is a Hilbert space, with the inner product (u,v)0 := / u(x)v(x) dx , in and the induced norm equal to || • ||o,2,fi defined above, which is usually denoted as || • ||0,nB.1.2 Separability of LP(Q) (1 < p < oo) The following countable subset W is dense in Lp(tt) (1 < p < oo): W
=
J
{£ a ;x*.(z)|
oj€», £,-ez, J = I , 2 , . . - , J |
where K is the set of rational numbers, xE (x) is the characteristic function on the set E, and i? G Z if and only if E is a union of finitely many cubes whose vertices are rational numbers. CQ(Q) is dense in LP(Q) (1 < p < oo). B.1.3 Reflexiveness of Lp(ft) (1 < p < oo) Theorem B . l . l . (The Representation Theorem in L p (fi), 1 < p < oo) For every bounded linear functional £(•) on LP(Q.) (1 < p < oo), there exists a unique v G Lq(Q), p~l + g _ 1 = 1, such that £(u) = / u(x)v(x) dx,
V w G Lp(^),
ll'll = IMIo,,,n. This theorem implies that LP(Q) (1 < p < oo) is a reflexive Banach space.
Sobolev Spaces
319
B.1.4 Sequential compactness of bounded sets in LP(Q) (1 < p < oo) Since Lp(ft) (1 < p < oo) is reflexive, its subset p, is weak-relatively sequen tially compact if and only if [i is bounded in the space norm, i e . , there is a constant C > 0 such that |M|o,p,Q < C for all u € [i. This implies that the condition of boundedness in norm alone is not sufficient for the strong sequential compactness of a subset in Lp(ft) (1 < p < oo). Theorem B.1.2. (Kolmogolov Theorem) A subset /j, C LP(Q) (1 < p < oo) is relatively sequentially compact if and only if (i) \i is bounded in norm; (ii) lim |y|_>o JRN \uix + 2/) — ^(x)| p ^x = 0 uniformly for all u € JJL, where u = Q outside ft; and (iii) lim K-»OO I\X\>K \u{x)\vdx = 0 uniformly for u e /x. We remark that if the region ft is bounded then Condition (iii) is satis fied, and so it is not needed. A subset satisfies Condition (ii) is said to be totally equi-continuous. On the other hand, if a u € LP(Q) (1 < p < oo) satisfies lim / I u(x + y) — u(x) \Pdx = 0, \y\-*ojRN
then it is said to be totally continuous. It can be verified that all functions in Lp(ft) (1 < p < oo) are totally continuous. B.2 Smoothing Operator and Mean-Value Approximation In this section, we show that every function in LP(Q) (1 < p < oo) can be approximated by smooth functions in norm, to any degree of accuracy. B.2.1 Definition of smooth operators Take any function j(-) that satisfies the following conditions:
j{x)eC?(RN), j(x)=0,
j(x)>0,
|as| > 1,
/
JRN
xeRN,
j(x)dx=l.
Usually, we use ( !
/ e x
3 (*) = {
_U.2
r
P^T^j2)>
0,
|x|>l,
N
320
Appendix B
where rhere
X^)*-
-' -/Ji. L . ..r-H'u -- p K ( I^ ^>
Let ,et . , 1 ./x-y\ ie(^») = ^ r j ( £ 7 ^ ) '
. „ -
£>0
ntegral operator, parametrized by./ e > The following integral 0, X H C lyJLLVJ VV lli.CC. lllt/V_-£i J. CM v-» L/V/l C*u V^J. . p u i i * i i i v u i i t i v v i ""^ J (J««)(x) = /* // jJ^,y)u(y)dy= = -1 jif^Wt,)*,. £(x,y)u(y)dy (J,«)(*) = (J««)(*) i<(x,»)«(v)d»= 4-^r // i^ f —«(„)<*, W JRN £™ J\y-x\<s \ J ££ ..V V e " J\y\<£ \ £ J X e" y|w_x|<e V / is called a smoothing operator with fcerne/ meanfeme! j (x), and JJ£eewu is called the t value woke function of uu with radius e. B.2.2 Mean-value approximation in Lj,(n) For any u € Lp(n), let Hx) S(x) = 5(x)
ff u(x), u(x), «(x), \o, lo, io,
xen, x €xeCl, n, N xxeR n, x ^\n, € ^ \ \n, €
and define (Je«)(x)=
/" je{x,y)u(y)dy,
x € RN .
((Bl) Bl)
Proposition B.2.1. any u e L (Jl) (1 < oo), oo), the the mean-value m-value -value Proposition B.2.1. For tor any u E e Lppp(Sl) [\l) (1 <
(B2) (52) (B2)
IMU^NkP,n. fo)(x)=0, (J e«)(x) = 0,
(S3) (S3)
V x ee fBl " ,
dist(x, distfx, supp(w)) s u p p ( w ) )>> £ .
(S4) (B4)
N Proof: € e C°°(R r r u o i : N Differentiating l^iueieuuiaLing (Bl) ^ D I ; leads icaus immediately lmmeuiaieiy to co J Je£uu fc O — l/t ). JV I. For r o>rr any any N with dist(x,supp(w)) JV \supp(u). ,p(u) xx € e R dist(x,supp( )) > e, if \y x| x\ < e then y e ii"\supp(u). R W J upp(«) e R with dist(x,supp( W )) > e, if |y - x| < e then y e JR \supp(u). Hence, Hence,
{J ( J£eu)(x)= « ) ( x ) = f/ J\y~x\<e
jie(x,y)S(| = 0, £(x,y)u(y)dy / )dj, =
Sobolev Spaces
321
which gives (B4). Suppose u(x) G Lp(il) (1 < p < oo). Rewrite j£(x,y) as Je^^yY^Je^^y)1^^ P"1 + # _ 1 = 1- Then, by the Holder inequality and /
x G RN ,
je(x,y)dy=l,
/ j£(x,y)dx< Jn
y€RN
1,
,
we have
\J<»\ ILo
f \ f ~ \P / / N j^(^,y)^(y)^y
JQIJR
/
= /
I
( / N^£^y^dy)
i j
p NJe{x,y)\u{y)\ dy\dx
\u(y)\pdy f .e(x,y)dx
< \m\o,p,nThis implies that J£u G Lp(Q), and so (B3) follows. Similarly, for u G Z>i(ft) or u G Loo(Q), we can establish the same result. [] Proposition B.2.2. outside ft, we have
For any >(x) G Co (ft), which is defined to be zero
J£cf> G C£°(ft), when lim | | J ^ - ^ | | o , P , n = 0 ,
0 < e < dist (supp (0), 5ft), (l
(B5) (B6)
Proof: Let F = supp ((£). If 0 < e < dist (F, 5ft), then the set F£ :=(x€RN\
dist (x, F) < e } C ft.
Hence, it follows from (B4) that supp (J£(f>) C F £ , so that J£cf) G Q°(ft). It is then easy to see that |(J^)(x)-^(x)| = | / <
je(x,y)[
sup \>(y) -<£(x)|, |#-2c|<£
|(J^)(x)-^(x)|=0,
x€RN\Fs.
x6F£i
Appendix
322
B
Consequently, \\Je4> -
<
sup
^llo,p,Fe
|^(y)-^(x)|-(meas(F£))1/p,
|y-x|<£
where p — oo when l/p — 0. Since
xeFe
Moreover, the measure of F£ is bounded as e —> 0. Hence, l i m \\Je
0
Since Co (ft) is dense in L p (ft), 1 < p < oo, we have the following result. Corollary B.2.1. C£°(ft) is dense in Lp(Q), 1 < p < oo. Theorem B.2.1. (Mean-Value Approximation Theorem) For any u e Lp(ft) (1 < p < oo), lim ||J e t4-ii|| 0 | p,n = 0,
(B7)
where J£u is the mean-value approximation of u in the sense of (Bl). Proof: For any
e^o
which yields (B7).
inf
<^eCo(n)
| \u - <j>\ | 0 , P ,Q = 0,
[]
Sobolev Spaces
323
Proposition B.2.3. dense in C(Q).
Suppose that Q, is bounded in RN.
Then C°°(RN)
is
Proof: Let u(x) € C(Q). Without loss of generality, suppose that u{x) is real, and 0 < f(x) < 1 for x 6 Tt. In RN\U, define dist (x, fi)
u(x) = sup yen
^(y)
Then u{x) is well defined in the entire space RN. It is easy to verify that w(x) is bounded in RN, and is continuous everywhere. Approximate u(x) by (Jeu)(x)=
[ JR
j£(x,y)u(y)dyeC™(RN).
N
Since \(j£u){x)
- u{x) I =
/
<
j £ (x,?/)[w(y)-w(x)] dy
sup
|u(y) — u{x)\,
xeft,
|y-x|<£
and since u(x) is uniformly continuous in any bounded region, we have \\J£u-
u\|0|OOjn ^ 0
(s -► 0).
B.2.3 Fundamental lemma of the variational principle Proposition B.2.4. (Fundamental Lemma of Variational Principle) Suppose that u(x) € Lp(il) (1 < p < oo). If /
u<j>dx = 0,
V^C0°°(11);
then w(x) = 0 almost everywhere in ft. Proof: Take any ft CC ft and fix an arbitrary x e ft. Then, when e > 0 is small enough, j£(x, y) as a function ofy belongs to CQ°(£1). Hence, it follows from the given condition that (Jeu) (x) = / j £ (x, y)u(y) dy = 0, Jn
x
eft.
It then follows from Theorem B.2.1 that lo,P,n = Wu ~ JeuWo,P£
^Wu~
J u
e \\o,P&
-* 0
(e-+0).
324
Appendix
Hence, u = 0 almost everywhere on Q as well as on il.
B Q
B.2.4 Smooth approximation in CP(Q,) (1
tt(x)€Lp(n),
VftCCft},
(1
CP(Q) is called a local Lp space on Q. Introduce countably many semi-norms || • ||o,p,ofc, k = 1,2, ••, where {Q,k} is a sequence of increasing subregions that converges to Q, and Q,k C C ft. Then CP(Q) becomes a linear topological space. Equipped with this topology, that a sequence {UJ} in CP(Q) converges to u € Cp(Q) if and only if for any subregion Q CC 0, {UJ} converges to u in Lp(tl). A sequence {UJ} is called a Cauchy sequence in Cp(Q) if for any subregion Q CC £}, {wj} is a Cauchy sequence in L p (fl). Thus, since Lp is complete, every Cauchy sequence in Cp(Q) converges. Theorem B.2.2. Cff(Q) is dense in CP(Q) (1 < p < oo). Proof: For any u(x) £ Cp(fl), let u(x), u
*(x)=\
„
0,
x€^ e , _ „jv x o ,
x€^\^£)
where, for r/ > 0, n^ = { a ; € n |
dist(x,an) >r?,
|x| < ry-1 } .
Define the following mean-value approximant of u£(x): (j£u£)(x)
=
j£(x,y)u£(y)dy.
(BS)
It can be verified that J£u£ € Cg°(Q), and that for any Q, CC ft, \\JeUe-u\\Oipfi-+0
(6-+0).
D
B.2.5 Partition of unity In order to introduce generalized derivatives later (in Section B.3), we first establish the partition of unity by employing the method of smoothing, which
Sobolev Spaces
325
will help put all the local results together within a region, so as to provide some results on the entire region. Lemma B.2.1. Suppose that F C RN is a closed bounded set, and U is an open set containing F. Then, we can construct a function <j> e CQ°(RN) such that 0 < 4>{x) < 1, x e RN, 4>(x) = l, xeF, supp (
ls
= f
js(x,y)Xv(y)dy,
0 < e < dist(F, RN\V)
,
^ n e characteristic function of the set V = { x e RN |
dist (x, F) < 2~Mist (F, RN\U)
X.
[]
Theorem B.2.3. (Partition of Unity) Suppose that F C RN is a closed bounded set. For any finite open covering {UJ}J=I
ofF
>
there
exist
$3 e Co°(RN)>
hix)
= ^2(x),
3 = ! > ' ' ' > J>
such
that
0 < ^j(x) e C?(RN),
(B9)
j
supp(<^)Ct/j,
^<^-(x) = l,
VxeF.
(BIO)
Proof: Construct another finite covering of F , {V?}. = 1 , where V} is a bounded open set with closure Vj contained in Uj. Let F\ = F\ U^ =2 Uj. Then, obviously F\ C C/i is a closed bounded set. Replace C/i by the bounded open set Vi = / x € RN |
dist (x, F x ) < 2- 1 dist(Fi, i?"\£/i) } .
Then we obtain an open covering of F : {Vi, U2, • • •, Uj}. Continuing this procedure eventually yields the expected covering.
326
Appendix
B
It then follows from Lemma B.2.1 that there exist ft(x), hj (x) e C£° (RN), j = 1, • • •, J, such that ft(x)>0, h(x) = l,
hj(x)>0,
hj{x) = l,
WxeRN, VxeF,
VxeVj,
supp (ft) C U^=1Vj-,
supp (ftj) C f/j .
It suffices to define , , , _ I [h\{x) + ■■■ + h2j(x)] -1/2h(x)hj(x), [ 0,
if x G UJk=1Vk ,
otherwise,
and then let ^ = ^ . Equations (B9) and (BIO) are then both satisfied.
[]
B.3 Generalized Derivatives B.3.1 Weak generalized derivatives In Subsection A.8.4 of Appendix A, we introduced the concept of weak gen eralized derivatives for functions in I/2(fi), obtained from weak extension of classical differential operators. In this section, we give a more general definition of weak generalized derivatives. Definition B.3.1. For a u{x) e £i{ft), if there exists an f(x) € £i(ft) such that f uDa(j>dx = (-l)lal f f4>dx V<£€C£°(ft), (511) JO,
JQ
then u is said to have a weak generalized derivative, Dau = f. We remark that a weak generalized derivative, if exists, is unique. This is because if fi(x) and J2{x) are both weak generalized derivatives of u then it follows from (Bll) that [ (fi-f2)4>dx
= 0,
V4>eC 0 °°(ft),
and thus the fundamental lemma of variational principle implies fi(x) — fii?) almost everywhere in ft. We also remark that if a function u is m-times continuously differen t i a t e on ft, then its classical derivative Dau (1 < \a\ < m) is also a weak generalized derivative of u. If ft is bounded, the function u is continuous
Sobolev Spaces
327
on Q, and its classical derivative du/dx^ is piecewise continuous on 17, then du/dxk is the first-order weak generalized derivative of u with respect to X&, k = 1, •••, TV. On the contrary, it is easy to find examples that have weak generalized derivatives but are not difFerentiable in the classical sense. Finally, we remark that the test function 4> shown in (Bll) can be chosen from a larger class of functions, CQ(Q). Indeed, for any <j> G CQ(Q,), let J£4> G CQ°(£1) be its mean-value approximation (for a small e > 0). Then, using integral by parts, we have (D°Je<j>)(x) = [
\DSJe(x,y)U(y)dy
=(-l)|a| / JR"
= / JR
N
L
\D«j£(x,y)]
je(x,y){Da
= (J£Da
xeRN.
(B12)
To this end, in (Bll), replacing <j> by J£<j), and using (B12) therein, lead to [ u(J£Da
[ fJ£4>dx. Jo,
Finally, letting e —» 0 in the above, and using Proposition B.2.2, we arrive at (Bll), where ^ ^ ' ( O ) . Equation (B12) shows that the classical differential operator and the smooth operator can be interchanged in operation. More generally, we have the following result. Proposition B.3.1. Suppose that u G C\{Q) has a weak generalized deriva tive Dau G £i(Q). Then for any 6 > 0, (DaJ£u) (x) = (J£Dau) (x),
x G Q6 ,
0 < e < 6,
(513)
where fls — {% G ft | dist (x, dil) > 6}, J£u and J£(Dau) are the mean-value approximations of u and Dau, respectively, in the sense of (Bl). Proof: Taking a derivative on the integral, we have, for 0 < e < 6, (DaJ£u)(x)=[
JRN
D«j£(x,y)u(y)dy
= (-1)1-1 [
D«j£(x,y)u(y)dy.
328
Appendix
B
For a fixed x e ft<5, when 0 < e < 8, je(x, y) as a function of y belongs to C Q ° ( Q ) . Hence, by Definition B.3.1 we have (DaJ£u)(x)
j£(x,y){Dau)(y)dy
= f
= (j£Dau)(x),
xefls,
0<e<6.
[}
We remark that using the mean-value approximation defined by (B8), we have the following result, which is similar to (B13): (DaJ£u£)(x)
= (J£(Dau)
)(x),
xeO;,
0 < £ < min{V3, l / V ^ } . (£14)
B.3.2 Strong generalized derivatives Proposition B.3.2. If a it € C\{fl) has a weak generalized derivative Dau = f € Ci(fl), then there exists a sequence {UJ} C CQ°(Q) such that uj-tu,
DaUj -» /
(j -+ oo),
in d{Q).
(£15)
Conversely, if there is a sequence {UJ} C C' a l(n) satisfying (B15), then u has a weak generalized derivative Dau = f. Proof: Following the proof of Theorem B.2.2, we first use (B8) to construct a mean-value approximant J£u£ 6 Co°(fl), such that J£u£ —> u
(e —> 0),
in
Ci(fl).
According to Theorem B.2.2 and its proof, as well as (B14), we have DaJ£u£-^f
(e-^0),
in
d(Sl).
To show the second part of the theorem, in the following equality / (fyD^Ujdx = (-1)1*1 /
Jn
UjD
a
cj>dx,
V > e Cg°(n), j > 1,
Jn
we let j —> oo, so as to obtain [ >f dx = {-1)M JQ
Jn
f uDact>dx,
V<£eC 0 °°(f2).
This implies that u has a weak generalized derivative Dau — f.
[]
Sobolev Spaces
329
Definition B.3.2. A function u € £i(Q) is said to have a strong generalized derivative Dau = f € £i(ft), if there exists a sequence {UJ} C C^(Q) such that Uj —► w, D 0 ^ —► / (j —> oo), in £ i ( f i ) . Actually, the fact that u € £i(ft) has a strong generalized derivative Dau € £i(fi) is equivalent to that w belongs to the domain of the minimal closed extension of the classical differential operator Da : C^(Q) C £i(ft) —► £i(fi). This is because for any sequence {UJ} C C' a '(Q), if *^ —► 0,
D " ^ - -► g
(j -> oo),
in £i(fi),
then <; = 0. Thus, the minimal closed extension of the classical differential operator Da exists. Proposition B.3.2 can be restated as: A strong generalized derivative and a weak generalized derivative are identical Hence, we will simply call them "generalized derivatives" in the following. Similarly, we can prove the following result. Proposition B.3.3. If a function u 6 CP(Q) (1 < p < oo) has a generalized derivative Dau = f € £ p (fi), then there exists a sequence {UJ} C CQ°(Q) such that uj^u,
Dauj -+ f
(j -* oo),
in Cp(Q) .
(J316)
Conversely, if there is a sequence {UJ} C C' a l(ft) satisfying (B16), then u has a generalized derivative Dau — / . Proposition B.3.3 is a criterion for the existence of a generalized deriva tive. The following is another, more convenient, criterion. Proposition B.3.4. Suppose that u G Cp(Q) (1 < p < oo). If there is a sequence {UJ} C Cp(fl) such that (i) in Cp(£l), {UJ} weakly converges to u, i.e., for any subregion Q CC ft, {UJ} weakly converges tou in LP(Q); and (ii) every Uj has a generalized derivative DaUj e Cp(Q)f and for any subre gion ft CC ft, there exists a constant M = M(ft) such that ll^llo,p,Q^M>
J = l,2,...,
(£17)
then {DaUj} weakly converges in CP(Q), and its limit f e CP(Q) is the generalized derivative ofu, Dau := / .
330
Appendix
B
Proof: Since a bounded set in LP(Q) is weak-relatively sequentially compact, it follows from (B17) that {DaUj} has a subsequence weakly converging in Lp(tl). Thus, choosing a sequence of subregions {ftk} satisfying
^ c c Q f c + i c c o , fc = i,2,-..,
u^=1n = n,
and using the diagonal selection method, we can find a subsequence such that Daunj -+ / (j -* oo), in CP(Q).
{unj}
We now prove that / is the generalized derivative of u. Take any <j> G Co°(Q) and a subregion Q, with supp(^>) C ft CC £}. Then, letting j —» oo in / unjDa
[
we obtain / uDOL4>dx = {-\)^ Jn
j 4>fdx. Jn
This implies t h a t / is the generalized derivative of u: D^u = f. In t h e above, we have actually proved t h a t every weakly converging subsequence of {DaUj} has the same weak limit, Dau, which is t h e unique generalized derivative. Consequently, sequence {DaUj} itself weakly con verges to / . []
Proposition B.3.4 provides a criterion for t h e term-by-term differentia bility of a series.
B.3.3 Local dependence of generalized derivatives According to the definition of generalized derivatives, if a function u has a generalized derivative on a region Q, then it also has the same generalized derivative on any subregion Q c D . The following is a converse result. Proposition B.3.5. If a function u G C\(£l) and at every point Q G tt, u has a generalized derivative Dau = fq G L1(Vq) in an open neighborhood Vq of Q, then u has a generalized derivative Dau = f G Ci(Q) in the entire region Q.
Sobolev Spaces
331
Proof: The theorem condition implies that {VQ} is an open covering of ft. Select a countable subcovering {VQ.} and define f(x) = fQ.(x),
in VQ.,
J =
1,2,....
Observe that in the overlapped region of Vgi and VQ., functions fgi and JQ. are identical almost everywhere due to the uniqueness of a generalized derivative. Hence, f(x) is well defined almost everywhere in ft. For any subregion ft CC ft, let {Vg r i .}. = 1 be a finite covering of ft. Then
f\f(x)\dx
\fQ
(x)\dx
which implies that / € £i(fl). For any cj> £ C§°(ft), let {VQn. } - =1 be a finite covering of F = supp ((f)). According to the principle of partition of unity, there exist {(f>j}j=1 C C§° (RN) such that j
supp(^.)cVQn.
(j = l , - . - , J ) ,
]►>,■(*) = 1,
V
Hence, for this <£ € Cg°(ft), / uDOL
=
j uDa(
Y1 [
= J2 [
uDa(4>cf>j)dx
uDoc(4>(t>j)dx
J
J=I VQ~3
= (-l)|a|E/
fMjdx
i=i
= (-l) H I ftdx.
Jn This implies that u has a generalized derivative Dau = f on ft.
^
F
-
332
Appendix
B
B.3.4 Operational rules of generalized derivatives Proposition B.3.6. (i) The operator of generalized derivative, Da, is linear, namely, for any constants a and b, Da(au1 + bu2) = aDaUl
+ bDau2 .
(ii) If Dau = f and D?f = g, then Da^u = g. (iii) Ifu,Du € Cp(Sl) and v,Dv e Cq(tt), where 1 < p < o o , p _ 1 + q~x = \,D = d/dxk, then D(uv) = vDu + uDv .
Proof: It follows from Proposition B.3.3 that there exist sequences {UJ} and {VJ} in CQ°(Q) such that Uj —► w,
DUJ —> Du
(j —> oo),
Vj —> v,
D ^ —> Dv
(j —► oo),
Take any <£ €
CQ°(Q).
in
£P(Q),
in £ g (ft).
Letting j —» oo in
/ itj ^ ,D<^ dx = — j (itj DVJ + Vj -Dwj ) <^ dx yields / uvD(f> dx = — I (uDv + vDu) <j> dx . Indeed, in any bounded subregion 0, with supp (0) C tl CC 1^, using the Holder inequality we have / UjVjD(f>dx — j =
/
uvDcj)dx\
[UJ(VJ —v) + V(UJ - u)] Dcj) dx
I Jn
I
< sup | (D
-sup ^ J K H o ^
+ IMIo,,,nll"-«AlP,n}Hence, lim / UjVjD(f>dx = I uvD(f>dx. J-*°° Jn Jn Similarly, we can show that lirn^ / (ujDvj+VjDuj)
/ (uDv+ vDu)
[]
Sobolev Spaces
333
B.4 Sobolev Spaces B.4.1 Sobolev spaces: definition and properties Let m > 0 be an integer and let 1 < p < oo. Define Wm>p(Q) = {ueLp{Q) W°>*(Sl) =
|
DaueLp(tt),
l<|a|<m},
LP(Q).
In W m ' p (ft), introduce the norms t ll^" *llbIS*, 11^**1 lPl nn j
>
l
0<\a\<m
I M|m,oo,n =
max
|\D a u\| 0 ,OO,Q •
0<|a|<m
' ' m 2
Forp = 2, in particular, we write W ' ( n ) as i J m ( ^ ) , and its norm || -||m,2,n as ||- || m > n . Let, also, W™'p(tt) be the closure of Cg°(fi) in Wm^(n), and write Equipped with the norm || • || m , p ,Q, the spaces W m ' p (f2) and their subspaces W™,P(Q) are called Sobolev spaces. Theorem B.4.1, (Properties of Sobolev Spaces) (i) Wrni'p(Q) (1 < p < oo) are Banach spaces. In particular, when p — 2, Wrn'2(Ql) = Hm(ft) are Hilbert spaces, with inner products (*>*L.n-
£ f D«u-D^dx, 0<M
u,veH™(tt).
(ii) Wm>p(Q) (1 < p < oo) are separable. (iii) Wm>P(Sl) (1 < p < oo) are reflexive. (iv) W rm,p (^) (1 < p < oo) are closures of the sets {ueC™^)
|
|M|m,Pin
(v) (The coordinate transform) Let y = 3>(:r) be a transform that maps region ft one-to-one to region G in the same space RN. If y — <£(x) and its inverse x = ^(y), as well as all their partial derivatives up to order m, are continuous and hounded, with Jacohian det&(x) ^ 0 for all x € ft, then under this transform, functions ofWrn>p(ft) and functions
334
Appendix of Wm'P{G), 1 < p < oo, have one-to-one correspondence. their norms are equivalent.
B
Moreover,
B.4.2 Interpolation inequality of intermediate derivatives and the density of CZ°(RN) in Wm
X )J2$<8 ^ < 5 - 2oXo»,
6v = F(£i,---,&v-i), F(£i, •••,&,-!),
7= 1
where fe0 > 0 and F satisfies the following Lipschitz condition: >. 1 / 2
,( N-l
\F(&---,&-l)-Ffflr..,&_1)\
\S1 ?
5 S>AT—1/
\S1 ?
5 S»JV—1/ | —
I
/
-j V^j
{ 1=1
N-l
EKf, 1= 1
^j )
\
,
'
J
N-l
EK)'
for a constant L > 0. In addition, for a small enough constant a > 0,
B t= (f,...f„ll *={(&.-,60l
Vf?<«!. £^
F A • • • .t*, A <■ P^ <■ F P. . . . fi„ F(tl,--,tN-i)
,\ -t-n eSl, K r O
^T ={(€i,-,6.) | £ 3 < « 2 . , ? r --ii))--aa << ^e <J VF
The boundary < dQ F( 9fi of region 0 is said to belong to Cr, if the function F(£i, • • •, •«,6,) •AT6I) has r-times continuouo partial dlrivatives. Theorem B.4.2. (Interpolation Inequality of Intermediate Derivatives) Let ftbea flbea bounded, L-type region in RN, and let m > 1, 1 < p < oo
335
5o6o/et; Sobolev Spaces
and £0 > 0. Then there exists a constant K = K{p, ft, m, e 0 ) > 0 such that for any u e Wm'*(Q) and 0 < e < e0, Mk, n
fe/(m fc) + Ks-htf£^m-^\u\ -ovn,MolP,n,fc
where
{
Q
0 , l •, •. .•,. m , m-- l1,, k = 0,1, \ i/p
EEll^llS.p.nf ll^ «HSlP>n |
l|a|=fe \a\=k \a\=k
JJI
•
Using this theorem, it is easy to derive the following result. Proposition B.4.1. Let m > 1 and 1 < p < oo. derivatives Dau € Lp(ft), sequence {u,} c Cg°(RN)
ft be a bounded, L-type region in RN, and let O let mth-order generalizeo If u € Lp(ft) has all the mth-order generalized |a| m, then u e W VFmm
l l « , - - « l k p , no - 0
(i-oo).
Consequently, C^(RNN)) C§°(R
= Wm'P(n), 'p(tl),
with respect to norm | | - | U | m,,pp, ,nn-.
Corollary B.4.1. For any region (need not be bounded L-type) ft C RN, m > 1, and 1 < p < oo, if u e £p(ft) nas has all the mth-order generaliz generalized a derivatives D u € £p(ft), |a| = m, then it has all lower-order generaliz \a\ = generalized derivatives Dau e £P(ft), where 1 < \a\ < m -1, and there exists a sequer sequence {«j}cC§°(n) such that a Q Z)»Uj. _ D D Uj -> L>au «
(j-*oo), (i (j -» -> oo),
| a | < m, 0 < |a| \a\ m,
in £ p (ft).
B.4.3 Boundary values of functions in WWmm>P{Q,) 'P(il) Let ft C RN be a bounded region, with boundary adft n belonging to C 1 , and 1 < P < oo. The boundary values of a function u € W W^P(ft) ^ ( f t ) on dft, denoted u |\dn W^ft) is dense in W W^ft), ^(ft), a n, , is understood as follows. Since C°°(ft) n W^Sl) 1 we can take a sequence {«,-} {«.,•} CC C°°(ft) C°°(ft) nn VK W^ft) -P(n) such such that that lI lhK «-j--«u«|l|lii,,PPP,,,nn - 0
( j' --^oooo) . O
since 0ft is bounded and 9U C\1 , we can partition 9ft Since <9ft belongs to C dft 9 0 in such a 9ft par ,vay that every piece, S, of dft 9fi can be represented via a suitable orthogonal way coordinate coordinate system (&, • • • ,£N), with the origin located in S, as follows: ZN = *F(t &r ■u(..-,£„-,), &,•--.^-i),
( £eii, -, -"--, ,6^v - 1i ))€€LD> ,
336
Appendix B
where D is a bounded region in RN~\ F 6 C\D), and 8F/d£k is bounded on D, k = 1, • • •, N - 1. Moreover, for small enough o > 0,
{ ( & ,,--,,& r - -l I, f, o&r0) | €N
D, ( €€ il , -- ,, ^^ -- il )) €€ D
? cv
For any 6 8e€ (0,o), (0,o),let let (£i, AN-I,r *■(&, Ffa, - i )++«) ••,£w-i) SSs = 1{ V?i''"'?JV-i)(6, • •• ••,6v-i, l€?Z?} .} . ^ss = = ^ i ' " "•■ ' ?•J■•,6v-i) V• -,i6; v-ro) | 6)|^ |I ,(&, - -(£i, - ,•? •J• V -•I,;6tv -ui )e t. s «,• ._ or ((4i, & , •• •• ••,,4iv-ij Civ-i) the Let, also, oruA^u « ,(&, fe,•••■••••,, 4Cw-i, &v_i, CJV-I) + + ) denote Let, also, Uj UJ I\log N - I , rFF(£u + «) ^J aenote the tne restricrestricQ or Uj tion of of Uj wj on on the the (N (N -- l)-dimensional l)-dimensional manifold manifold Sg. Ss. It It can can then then be be verified verified tion tion of UJ on the (N - l)-dimensional manifold Ss. It can then be verified that when when j -> oo, oo, {Uj |\sg } } converges in uniformly with with respect respect to to that in L LPP{D) {D) uniformly that when jj -» -> oo, {w^{ \s } converges converges in L P{D) uniformly with respect to 6 € (0, a) and its limitUjis independent of the selection of {u } This limit can o6 f€- i\) (0, ci) a) ano and ITS its limit IITTIIT IS is iTioeDeiioeTir independent OT of the rne selection seiecnon of 01 {u \ u ■} r This i mslimit liiiiiLcan can be "considered to be the value of u on the manifold Ss, and is denoted u \ss or be "considered to be the value of u on the manifold Ss, and is denoted it or u \s \sss or U(€I,---,£N-I,F(£I, ■■-,&-!)+6). It can also be verified that u \ is uni ^ 6 , - ' - , £ A r - i , F ( £ i , - -■■-,&-!)+6). - , £ A r - i ) + £ ) . It can also be verified that u \\sSs U(€I,---,£N-I,F(£I, 6 is uni Ss formly continuous in L {D) with respect to .5 € (0, a), so that when 6 -► 0, formly continuous in Lpp(D) e (0, a), so that when « 0, {D) with respect to 6 .5 € 6 -* -► 0, {u ||s,} converges in LP(D), and its limit can can be be considered considered as the the value of of u {w (D), and its limit {u |s,} LPP(D), its as value of uu 5 , } converges in L on S, denoted u \ or «(&, • • • ,&r-i,F *"(£I, • • • ,6v-i))S, denoted u u \sss or or «(&, u(£u • •••,•Civ-i, on S, , C A T - I (, ^f i(,6 ,• •••,• CAT-I))• • ,^JV-I))Combining all the values of u on the pieces S 5 of dQ, a n , we can obtain the Combining all the values of w u on the pieces S 5 of a n , we can obtain the value of u on the entire boundary, denoted u \dQ. Clearly, u |\dn e Lp{dQ). an € value of u on the entire boundary, denoted u \dQ. Clearly, u \dn (dQ). dQ e LLpp(an). Hence, if the boundary of a bounded region ft belongs to C\ C \ then the func Hence, if theXboundary of a bounded region tt C\\ then the funcQ belongs to C func tions u in W^P{Q) 1 <
J
[v~dx=-fu-^-dx+[ f v~dx=uvnkkds, ds, v — d x = -[ uu^-dx+ — dx+ f uvn Jn dxk Jn dxk J9Q an
n
k=l,---,N, k=l,---,N, k=\,---,N,
= («i, (nu ■■ where n = • ■ ■, •, nN dQ, w ) is the unit outer-normal vector on the boundary dft, and the u in the the boundary integral is the the boundary value of u belonging to
Lp(an). Lp(dn).
Sobolev Spaces
337
Let ft be a general region, m > 1, 1 < p < oo, w G W™'p(rj) and v € Wm^{ft), where p " 1 + g _ 1 = 1. Let {UJ} C Co°(ft) be such that I \Uj - u\ \mlP,n, -» 0
(j —► oo).
Then, letting j —> oo in / vDaUjdx=:
( - l ) l a | j UjDavdx,
j = l,2,-..,
we obtain / vl^tx dx = ( - l ) | a | / *xDa<; dx ,
|a| <
Comparing this equation with the general formula of integral by parts, we see that in some sense Dau = 0 on the boundary dft for 0 < |a| < m — 1. If ft is bounded, with a boundary belonging to C m , and if u e W™'p{ft), then Dau \dn = 0 for 0 < |a| < rn—I'm the sense discussed at the beginning of this section. Furthermore, if u e C111'1^) then Dau \dQ = 0 for 0 < \a\ < m - 1 in the usual sense. B.4.4 Embedding theorem Definition B.4.1. Let X\ and X2 be Banach spaces. X\ is said to be embedded into X2, denoted X\ <—> X%, if Xi C X2 and there exists a constant C 0 > 0 such that IMIx^ColMlxx,
VaxeXx.
The above condition implies that the identity operator / : X\ —► X2 is continuous, which is called the embedding operator, or simply, the embedding, and is denoted I: Xi —> X2. The following Embedding Theorem shows that if m is large enough, the functions in Wm,p(Q) are continuous, and even continuously differentiable, on ft. Theorem B.4.3. (Embedding Theorem) Suppose that ft C RN is a bounded, L-type region. Let fts (1 < s < N) be the intersection of an arbitrary s-dimensional hyperplane with ft, where ftN = ft. For m >1, 1
Wk*(fls),
338
Appendix
B
where q and s satisfy 1 < q < sp/(N - p(m - k)) and N - p(m - k) < s
wm>p{n)<->wk>q(ns), where q and s satisfy 1 < q < oo and 1 < s < N. embedding I: Wm*(n) -► Wk^{fts) is compact. (hi) If (m - k)p > N, then W™*^)
^
Moreover, the
Ck{Q).
Moreover, the embedding I: Wrn^p(ft) —► Ck(Tt) is compact. We remark that W™*(Q) <-+ Ck(tt) means that for each u G Wm>p(Sl\ there exists a ii € Ck(Q) such that u{x) = u(x) almost everywhere in Q. Moreover, ess sup Xen
^
\(Dau)(x)
| < CblML^.n ,
0<|a|
where CQ > 0 is a constant, independent of u e Wm,p(Q). There are more subtle results on embedding, which can be found in, for instance, [1, 16, 18].
Subject Index A
coercive 186 coercive elliptic 72 V-elliptic 72 Continuous completely 164 demicontinuous 164 hemicontinuous 164 weakly 164 Continuously homotopic 126 Converge 3 pointwise 7 strongly 3 weakly 3 weak* 181, 309 Convex functional 178
Approximation scheme 3 solvability 3 Approximate-solvable strongly 3, 4 weakly 3, 4 Aubin-Nitsche approach 83 B Bochner integrable (B-integrable) 229 Boundary value problem 21, 36, 42, 60, 96, 202 C
D
C(tt)_294 Cm{n) 294 Cm{n) 297 C°°(«) 297 Cg°{tt) 297 C((a,b);H) 232 C 0 ((a,6);ff) 230 C°°{(a,b);H) 234 Cg°((a,6);ff)232 Completely homotopic 139 Condition boundary 150 Caratheodory 260
Degree topological 115, 121, 125, 137, 139 Brouwer 125 generalized topological 139 Leray-Schauder 137 Derivative (of operator) 165, 167 DifTerentiable (operator) Prechet 166 Gateaux 165 strongly 166 weakly 165, 166 339
Subject Index
340 Differential Gateaux 165 weak 165 E Eigenvalue 32 Eigenvector 32 Equation Bubnov-Galerkin 37 collocation 38 elliptic partial differential 100 evolution 227 fixed point 144 Predholm integral 36 Galerkin 37 operator 2 ordinary differential 42, 96, 218 parabolic 235, 259 variational 16 F Formula index 132 Lagrange mean value 173 Taylor expansion 173 Fourier expansion 47 Function abstract 228 Bochner integrable 229 Green 42 simple 228 strongly measurable 228 weakly measurable 228 G General coerciveness 186, 194 Generalized derivative 233, 295, 302, 326, 328
Generalized Priedrichs solvable extension 89 Generalized solution 16, 91, 196 271, 275 generalized strong 74 generalized weak 82 Gradient 173 H HHa,b)9 H*(a,b) 16 Hm(n) 294 if m ((a, 6); F ) 233 H-estimate 83 I Index (of isolated point) 131 Inequality Carding 104 Cauchy-Schwarz 293 TT
1
r\ >*9
Hardy 97 Holder 318 Minkowski 318 Poincare 296 triangular 293 variational 107 Initial-boundary value problem 235, 259 K Kernel continuous 29 degenerate 30 Schmidt 29 L Lp(fi) 294, 317
£p(ft) 324 L p((a,b);H) 229 p((a,b);H) 229 L^{(a,6);H)233 L^{(a,6);H)233
Subject Index Lemma of variational principle 323 Lax-Milgram 71 Lower semiboundedness 238 M Method Bubnov-Galerkin 5 collocation 5 continuous-time projection 237 discrete-time projection 252 finite element 4 Galerkin 4 Galerkin-Petrov 5 least-squares 5 moment 5 projective computational 4
341 K-symmetric 87 Lipschitz continuous 191 monotone 174, 194 anti-monotone 222 K-monotone 195 pseudo-monotone 222 strictly monotone 174, 194 strongly K-monotone 195 strongly monotone 183, 194 projection 6 quasi-bounded 221 regular 114 Schauder 134 semi-bounded 222 smoothing 231 topological 146 weakly continuous 65 Orthogonal projective approximation scheme 15
N Null set 6 O Operator A-proper 139 adjoint 311 closable 74 coercive 186, 194 compact 28 relatively compact 28 completely continuousr 28 definite 70 demicontinuous 164 dual 311 embedding 337 Predholm 29 general coercive 194 hemicontinuous 164 K-coercive 195 K-monotone 195 K-positive definite 87
P Point Chebyshev 41 critical 114 fixed 144 spectral 32 Positive definiteness 71 Principle Kronecker 125 Ler ay-Schauder 137 open-set invariant 146 Projection operator 6 Projective approximation algorithm 4, 7, 12 Projective computational method 4 Property of topological degree 123, 125, 137, 142 boundary value dependence 126 connectivity 126
Subject Index
342 continuous homotopyinvariant 126, 142 domain decomposition 125, 137,142 integer-valued 123 removability 126 shift-invariant property 125 solvability 142 stability 123, 125, 137 unity 123 R Regular value 32, 114 Riesz-Schauder theory 33 S Scheme approximation 3 orthogonal projective approximation 15 stable approximation 94 Set compact 133 kernel 145 null 6 precompact 133 relatively compact 133 sequentially compact 133 totally bounded 133 weak-(or weak*-) relatively sequentially compact 231 Solution classical 16, 82 generalized 16, 21, 196 generalized (strong) 74 generalized (weak) 82, 91 Space Banach 293 Hilbert 293 linear (vector, normed, topological) 292
Sobolev 17, 333 Spectrum continuous 32 residual 33
T Theorem Babuska 72, 105 Banach-Sake 304 Brouwer's fixed point 145 Browder 195 closed graph 301 composition 128 embedding 337 Predholm 313, 315 Hahn-Banach 308 Hilbert-Schmidt 315 inverse operator 300 Kolmogolov 319 Krasnosel'skii fixed point 148 Lax-Milgram 308 Leray-Schauder fixed point 148 modified Lax-Milgram 190 mean-value approximation 322 norm equivalence 218 open mapping 300 orthogonal projection 305 reduction 130 Riesz representation 306 Sard 122 Schauder fixed point 147 Scheclov 74 uniform boundedness 303 Weyl's comparison 53 U Ultimately dense 4, 7 Uniformly strong accreativity 238
343
Subject Index V V-elliptic condition 72 V-estimate 83 Value critical 114 eigen 32 regular 32, 114
Variation 173 w
Wm>P(n) 200, 333 W™'p{tt) 200, 333