Journal of Function Spaces

Volume 2014 (2014), Article ID 435247, 9 pages

http://dx.doi.org/10.1155/2014/435247

Research Article

Nonlocal Variational Principles with Variable Growth

Yongqiang Fu and Miaomiao Yang

Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China

Received 17 January 2014; Accepted 6 March 2014; Published 7 April 2014

Academic Editor: Qingying Bu

Copyright © 2014 Yongqiang Fu and Miaomiao Yang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

This paper is concerned with the functional defined by , where is a regular open bounded set and is a real-valued function with variable growth. After discussing the theory of Young measures in variable exponent Sobolev spaces, we study the weak lower semicontinuity and relaxation of .

1. Introduction

In this paper, we are concerned with a type of variational integrals that can be written as

where is a regular open bounded set (), , and is Lipschitz continuous with . satisfies that and are measurable and and are continuous. is also assumed to satisfy the variable growth condition

for . Notice that

After Kováčik and Rákosník first discussed and spaces in [1], a lot of research has been done concerning these kinds of variable exponent spaces; for examples, see [2–6] for the properties of such spaces and [7–9] for the applications of variable exponent spaces on partial differential equations. These problems with variable exponent growth possess very complicated nonlinearities; for instance, the -Laplacian operator is inhomogeneous. In recent years, these problems have received considerable attention and raised many difficult mathematical problems. The theory on various mathematical problems with -growth conditions has important applications in nonlinear elastic mechanics, imaging processing, electrorheological fluids. and other physics phenomena (see [10, 11]).

The main goal of this paper is to study the weak lower semicontinuity and relaxation of the nonlocal variational problems. We will analyze these problems in terms of Young measures generated by sequences in variable exponent space. When is a constant function, Pedregal studied problem (1) in [12]. In connection with variational problems of nonlocal nature the reader can consult [13] for problems related to ferromagnetism, [14] about the regularization of a nonconvex problem, and [15–17] in order to analyze mechanical problems formulated in general context of nonlocal elasticity. In [18] some interesting tools to obtain a full relaxation of specific nonlocal variational problems have been analyzed, and [19] is also a remarkable work for a general class of nonlocal integral functionals. If convexity condition does not hold for , then we would like to have an equivalent variational principle in the sense that the infimum is preserved and the relaxed variational principle admits a minimizer. The usual way to proceed for local functionals is to replace by its convex hull. In nonlocal setting, there is no substitute for the convex hull. The only possible way to describe relaxation for these nonlocal variational principles is by using Young measures and a generalized functional defined on them (see [12, 20]).

This paper is organized as follows. In Section 2, several important properties on variable exponent spaces are recalled; in Section 3, we give some conclusions of Young measures in variable exponent spaces; in Section 4, we analyze the weak lower semicontinuity and relaxation of problem (1).

2. Preliminaries

In this section, we first recall some facts on variable exponent spaces and . See [1, 4–6] for the details.

Let be the set of all Lebesgue measurable functions , where is a nonempty open subset. Denote

where . The variable exponent Lebesgue space is the class of all functions such that for some . is a Banach space endowed with the norm (5). Equation (4) is called the modular of in .

For a given , we define the conjugate function as

Lemma 1 (see [6]). Let , then the inequality

holds for every , .

In the following parts of this section, for every , we assume .

Lemma 2 (see [5]). For any , we have

(1)if , then ;(2)if , then .

Lemma 3 (see [5]). If , is reflexive, and the dual space of is .

Lemma 4 (see [1]). Let , where denotes the Lebesgue measure of , and ; then the necessary and sufficient condition for is that for almost every , and in this case the embedding is continuous.

Next is a given positive integer. Given a multi-index , we set and , where is the generalized derivative operator.

The variable exponent Sobolev space is the class of functions on such that for every multi-index with . is a Banach space endowed with the norm

By we denote the subspace of which is the closure of with respect to the norm (8).

For any , define

Then is an equivalent norm of . If is a bounded domain, is an equivalent norm of .

Lemma 5 (see [1]). The spaces   and are separable. Furthermore they are reflexive if .

Denote the dual space of by ; then we have the following.

Lemma 6 (see [1]). Let . Then for every , there exists such that

The norm of is defined as

Lemma 7 (see [4]). Let be a domain in with cone property. If is Lipschitz continuous and , is measurable and satisfies for almost every ; then there is a continuous embedding .

Lemma 8 (see [4]). Let be a domain in with cone property. If is continuous and , then for any measurable function defined in with for almost every and , there is a continuous compact embedding .

Lemma 9 (see [6]). Let ; then the Hardy-Littlewood maximal operator is bounded on .

3. Young Measure Generated by Sequences in Variable Exponent Space

Weak convergence is a basic tool of modern nonlinear analysis because it has the same compactness properties as the convergence in finite dimensional spaces (see [21]). But this notion does not behave as we desire with respect to nonlinear functionals and operators. Young measures are a device to overcome these difficulties. For the details we refer to [21–24]. Inspired by these works, we will discuss Young measures in variable exponent spaces. In some references Young measures are called parameterized measures. Here we take the two terms as equivalent. First, we recall the definition and some Lemmas on Young measures.

Definition 10 (see [21]). Assume that the sequence is bounded in . Then there exist a subsequence and a Borel probability measure on for a.e. , such that for each we have

where

We call the family of Young measure associated with the subsequence .

Lemma 11 (see [22]). Let be Lebesgue measurable (not necessarily bounded) and , , be a sequence of Lebesgue measurable functions. Then there exists a subsequence still denoted as and a family of nonnegative Radon measures on , such that

(i) for almost every ;(ii) weakly* in for any , where and ;(iii)if for any

Then for almost every , and for any measurable there holds weakly in for continuous provided that the sequence is weakly relative compact in .

Lemma 11 is the fundamental theorem of Young measure. A family satisfying (i)-(ii) always exists, and is a Young measure if (14) holds. The proof and complete analysis of Lemma 11 can be found in [20, 23]. According to the comments there, we give some remarks.

Remark 12. Ball showed in [23] that under hypothesis (14) for any measurable

for every Caratheodory function such that is sequentially weakly relative compact in .

Remark 13. It was shown in [20] that, in order to identify the Young measure associated with a particular sequence of functions , it is enough to check

for every . It is even enough to have

for and belonging to dense, countable subsets of and , respectively.

Lemma 11 has useful applications in nonlinear partial differential equation theory. The following lemmas are useful for us.

Lemma 14 (see [20]). Let be a uniformly bounded sequence in . Then there exist a subsequence (not relabeled), a nonincreasing sequence of measurable subsets of with as , and such that

for all .

Lemma 15 (see [20]). Let be a sequence of vector-valued functions with associated Young measure . If, for , a nonnegative Carathéodory function, we have

then

for any measurable subset and for any in the space

Lemma 16 (see [20]). If is a sequence of measurable functions with associated parameterized measure ,

for every nonnegtive Carathéodory function and every measurable subset .

Lemma 17 (see [25]). If the sequence is bounded in , then there is a Young measure generated by satisfying , and the weak -limit of is .

Lemma 18 (see [25]). Let . If in , then the sequence generates the Young measure . Moreover, for almost every , is a probability measure and satisfies .

By Lemmas 3.8 and  3.9 in [25], we know that if a sequence is bounded in , then can generate a family of Young measures. Now we can define -Young measure for a sequence of functions in .

Definition 19. is a family of probability measures supported in . is called a -Young measure if it can be generated by gradients of a bounded sequence of functions in .

Theorem 20. Assume that the sequences and are bounded in . We have

(a)if as , then the Young measures for both sequences are the same;(b)if as , then the Young measures for both sequences are the same.

Proof. (a) By Remark 13, it suffices to prove that the limits of and are the same for every and every . We conclude the result from

as .

(b) For any and , we have

Since , as , there exists a subsequence still denoted as such that , for almost every , as . Then , for almost every , as . By dominated convergence theorem, we get

Example 21. Assume that is a bounded sequence in and let be its associated Young measure. Consider the truncation operators

By Lemma 2, there exists a constant such that . Then for any subsequence as ,

Thus the Young measure corresponding to is also .

Theorem 22. Let be a bounded sequence in such that the sequence generates the Young measure . Then we have

(a)there exists such that ;(b)there exists a new sequence bounded in such that generates the same Young measure and for all . Moreover if is equi-integrable, so is .

Proof. (a) Since is a bounded sequence in , by Lemma 5, there exists a subsequence still denoted as such that in for some . Moreover in . By Lemmas 17 and 18, in . Thus .

(b) Let be a sequence of cut-off functions satisfying

(i) on ;(ii) in ;(iii) for some constant .

Consider the sequence

Clearly for all , , and

Notice that

Lemma 8 implies that as . Then we can choose a subsequence so that is bounded in and equi-integrable if is equi-integrable. Let be the sequence . Moreover

Thus by Theorem 20, and generate the same Young measure.

Theorem 23. Let be a bounded sequence in . Then there always exists another sequence of Lipschitz functions with for all such that is equi-integrable and the two sequences of gradients, and , generate the same -Young measure.

Proof. By Lemma 6, we can assume that in for some . By Theorem 22, we can assume that . Extend by 0 to all of . By density, we can find such that as . This implies that is a bounded sequence in . Consider the sequence , where

and is the Hardy-Littlewood maximal operator. By Lemma 9, is bounded in . Let be the corresponding Young measure (possibly for an appropriate subsequence). For fixed , is bounded in and for any ,

We can get by Dunford-Pettis and Lemma 11

By Levei theorem, we have

and . Moreover

Thus we can get

And we can find a subsequence as such that

By Lemma 15, let . For any , there exists a constant such that . We can take . Thus

That is, in . Let . Since is bounded in and as , . There exists Lipschitz function , such that in and for all . Because , by Theorem 20 again, and generate the same Young measure. Since , we have

It follows from the equi-integrability of that is equi-integrable. Take . Then the sequence verifies the conclusion of the theorem.

Theorem 24. Let be a family of probability measures supported in . is the Young measure generated by a sequence , where is a bounded sequence in . Then

where is the Young measure generated by the sequence of gradients .

Proof. Let and . We have

Remark 25. Concerning the above result it must be pointed out that we have the representation

for any continuous such that converges weakly in .

4. Weak Lower Semicontinuity and Relaxation

Theorem 26. Assume that (2) holds. is weakly lower semicontinuous in if and only if for any -Young measure ,

Proof. For any -Young measure , by Definition 19, can be generated by a bounded sequence in . Moreover we can assume that in (possibly for a suitable subsequence). By Lemma 18, we have . According to Theorem 22, there exists another sequence such that is weakly convergent in . and generate the same Young measure. Going if necessary to a subsequence, we can assume that is also weakly convergent to . Actually if , by Lemma 18, we have . Then we can take , and is also weakly convergent in . Since is weakly lower semicontinuous and (2) holds, we can get

On the other hand, if in , then by Lemma 18   can generate a family of -Young measure and . Thus (2) and Lemma 16 imply that

Theorem 27. Let in and be the -Young measure associated to (or possibly to a subsequence). Then

for all measurable , if and only if

Proof . In view of Theorem 26, we only need show the necessity. By Lemma 14, there exists a sequence of measurable sets such that for each , , and

in for all . By (47) and Lemma 11

Lemma 16 implies that and by (47) . Therefore

Moreover

Then we can get the conclusion.

In many models from mathematical physics we need to consider variational integrals like

where is some fixed function in . The energy of a Young measure is defined by

where is a -Young measure generated by a sequence of gradients in ; there exists , such that , . Let

Theorem 28. Let

Then and is indeed a minimum.

Proof. Consider the following steps.

Step  1. Equation (56) admits a minimizing sequence such that is weakly convergent in .

Let be a minimizing sequence for (56). By (2), is a bounded sequence in . By Lemma 17, let denote the Young measure associated to the sequence of gradients. According to Theorem 22, there exists another sequence such that is weakly convergent in and and generate the same Young measure. Going if necessary to a subsequence, we can assume that both and are weakly convergent to . If , by Lemma 18, we have . Then we can take , and is also weakly convergent in . By Theorem 22, there exists a sequence in such that for every . Moreover and generate the same Young measure and is also equi-integrable. Since and is weakly closed, we can get . Moreover . Since is a minimizing sequence for (56), we can get, by Lemma 16,

Then we can conclude that is also a minimizing sequence to (56).

Step  2 . From Step 1, we know that . And

On the other hand, for any , there exists a bounded sequence in such that for every . We can assume that and is equi-integrable. Thus

The arbitrariness of implies that .

Step  3. There exists such that

If is a minimizing sequence for (56), we can assume that is equi-integrable and the associated Young measure . Hence

Consequently, is a minimizer of (57).

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgment

This paper is supported by NSFC-11371110.

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