Characterization of generalized Young measures generated by $\mathcal A$-free measures
Adolfo Arroyo-Rabasa

TL;DR
This paper characterizes generalized Young measures generated by a-free and b-gradient measures using duality and separation properties, revealing insights into a- and b-operator related compactness and rigidity phenomena.
Contribution
It provides duality-based characterizations of a-free and b-gradient Young measures for operators satisfying constant rank, with applications to a- and b-operator measure inclusions.
Findings
Characterizations of a-free and b-gradient Young measures via Hahn--Banach separation.
Examples showing failure of a- and b-compactness with mass concentration.
Density results for measure inclusions in a- and b-operator contexts.
Abstract
We give two characterizations, one for the class of generalized Young measures generated by -free measures, and one for the class generated by -gradient measures . Here, and are linear homogeneous operators of arbitrary order, which we assume satisfy the constant rank property. The characterization places the class of generalized -free Young measures in duality with the class of -quasiconvex integrands by means of a well-known Hahn--Banach separation property. A similar statement holds for generalized -gradient Young measures. Concerning applications, we discuss several examples that showcase the rigidity or the failure of -compensated compactness when concentration of mass is allowed. These include the failure of -estimates for elliptic systems and the failureā¦
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MnLargeSymbolsā164 MnLargeSymbolsā171
Characterization of generalized
Young measures generated by
-free measures
Adolfo Arroyo-Rabasa
Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK
[email protected],[email protected]
Abstract.
We give two characterizations, one for the class of generalized Young measures generated by -free measures and one for the class generated by -gradient measures . Here, and are linear homogeneous operators of arbitrary order, which we assume satisfy the constant rank property. The characterization places the class of generalized -free Young measures in duality with the class of -quasiconvex integrands by means of a well-known HahnāBanach separation property. A similar statement holds for generalized -gradient Young measures. Concerning applications, we discuss several examples that showcase the rigidity or the failure of -compensated compactness when concentration of mass is allowed. These include the failure of -estimates for elliptic systems and the failure of -rigidity for the two-state problem. As a byproduct of our techniques we also show that, for any bounded open set , the inclusions
[TABLE]
are dense with respect to the area-functional convergence of measures.
Key words and phrases:
-free measure, compensated compactness, generalized Young measure, concentration, oscillation, two-state problem, PDE constraint, constant rank operator.
2010 Mathematics Subject Classification:
Primary 49J45, 49Q15; Secondary 46G10, 35B05.
Contents
-
1.3.2 Area strict density of absolutely continuous -free measures
-
1.3.3 Characterization of generalized -gradient Young measures
-
3.1 Young measures generated by full-rank elliptic operators
1. Introduction
The last decades have witnessed an extensive development of the study of non-convex variational energies related to equilibrium configurations of materials in a wide range of physical models (such as the study of crystalline solids and thermoelastic materials, linear elasticity, perfect plasticity, micro-magnetics, and ferro-magnetics, among othersĀ [BallJames1987, chipot1988, desinone1993, james1992]). Often, these models consist in a minimization principle for integrals of the form
[TABLE]
where is an open and bounded set, satisfies a uniform -growth condition , and the configurations obey a set of physical laws determined by a system of linear PDEs, where, depending on the particular model, either
[TABLE]
We shall refer to the first scenario as the -free framework and to the latter as the potential or -gradient framework. In order to keep the exposition as simple as possible, we shall henceforth adopt the -free perspective.
In these circumstances, designs with near to minimal energy exhibit compatible equilibrium behavior at microscopical scales, while, at larger scales, configurations adapt by gluing together the low energy patterns allowed by the governing equations inĀ (2)/(3). This interplay conveys the formation of finer and finer oscillations, often resulting in some form of -weak convergence when , or weak- convergence (in the sense of measures) when [ambrosio1992-On_the_relaxation, baia2013lower-semiconti, fonseca2004mathcal-a-quasi, fonseca1993relaxation-of-q, kristensen2010relaxation-of-s, kristensen2010characterizatio, barroso2000a-relaxation-th, arroyo-rabasa2017lower-semiconti, rindler2011lower-semiconti, rindler2012lower-semiconti]. In general, such weak forms of convergence are incompatible with the lower semicontinuity of the energy, which is usually the starting point for minimization principles. Additionally, the case may be ill-posed in the sense that, independently of the PDE-constraint, a solution to the minimization problem may fail to exist. The reason is that is not reflexive and it naturally lacks of compactness properties that guarantee the existence of minimizers. To solve this, one relaxes the variational settingĀ (1)-(2)/(1)-(3) to the minimization of the extended energy functional
[TABLE]
defined for measure-valued configurations (or for some potential ). Here, is a regularization at infinity called the strong recession function of , which is defined (provided that it exists) as
[TABLE]
In this paper we focus on the case , which requires a careful study of oscillations and concentrations occurring along weak- convergent sequences of measures satisfyingĀ (2)/(3). In this regard, an equivalent approach towards the understanding ofĀ (1)-(2) consists of characterizing all generalized Young measures (seeĀ [diperna1987oscillations-an]) generated by sequences . Let us recall that, formally, a generalized Young measure associated to a sequence is a triple conformed by a non-negative measure and two families , of probability measures over the target space , satisfying the fundamental property that
[TABLE]
for all sufficiently regular integrands with linear growth at infinity.
The main result of this paper is contained inĀ TheoremĀ 1.1 and states that a generalized Young measure , with zero boundary-values , is generated by a sequence -free measures if and only if (see DefinitionĀ 1.4)
[TABLE]
This separation result implies that the class of generalized -free Young measures is a convex set characterized by duality in terms of all -quasiconvex integrands. In addition to this duality characterization, we give a characterization in terms of the blow-up properties of generalized Young measures (see TheoremĀ 1.2). More precisely, we prove that as above is generated by a sequence of -free measures if and only if its tangent cones almost always contain a generalized Young measure that is generated by -free measures. Lastly, in TheoremĀ 1.3, we establish the following approximation result: if is a bounded -free measure, then there exists a sequence of -free functions that converges to in the sense of the generalized area functional, i.e.,
[TABLE]
[TABLE]
We also prove analogous results in the -potential settingĀ (1)-(3), for generalized measures generated by sequences of the form . These are contained in TheoremĀ 1.5, TheoremĀ 1.4 and TheoremĀ 1.6.
1.1. State of the art
The work of Young [young1937generalized-cur, young1942generalized-sur, young1942generalized-surII] and the use of (classical) Young measures plays a fundamental role in representing solutions of optimal control problems. The study of Young measures, from the point of view of partial differential equations, started with the work of Tartar & Murat, who, motivated by problems in continuum mechanics and electromagnetism, introduced the theory of compactness by compensationĀ [arroyo-rabasa2017lower-semiconti, murat1978compacite-par-c, tartar1979compensated-com, tartar1983the-compensated, murat1985optimality-cond]. The first characterization of Young measures in the PDE-constrained context is due to Kinderlehrer & PedregalĀ [kinderlehrer1991characterizatio, kinder1994] for the potential configuration , of a Sobolev function with . This characterization of -gradient Young measures accounts for the validity of Jensenās inequality between gradient Young measures and (curl-)quasiconvex integrands.111The importance of quasiconvexity in the calculus of variations was first observed by MorreyĀ [Morrey1, Morrey2], who showed quasiconvexity is a sufficient and necessary condition for the lower semicontinuity ofĀ (1)-(3), when is the gradient operator. More precisely, the authors showed that a (purely oscillatory) family of probability distributions on the space of matrices is a Young measure generated by a -equi-integrable sequence of gradients if and only if
[TABLE]
for all quasiconvex integrands with -growth at infinity. The characterization also covers the case , but only when the generating sequences are assumed to be equi-integrable. The extension of this result to generalized Young measures generated by gradients, which is instead associated to the space of functions of bounded variation, is due to Kristensen & RindlerĀ [kristensen2010characterizatio]. There, the authors show that a generalized Young measure is generated by a sequence of gradient measures if and only if a version ofĀ (6) holds for the absolutely continuous part of , that is,
[TABLE]
for all quasiconvex integrands with linear-growth at infinity, where . Somewhat surprisingly, this conveys that the nonlinear moments of the purely concentration part of are fully unconstrained. (This is a consequence of Albertiās rank one theoremĀ [Alberti] and a recent rigidity result for positively homogeneous rank-one convex functions established by Kirchheim & KristensenĀ [kirchheim2016on-rank-one-con].)
The efforts to establish an -free variational theory for Young measures initiated with the work of DacorognaĀ [dacorogna1982weak-continuity], who studied -free functions that are represented by potentials where is a suitable first-order operator. However, it was the seminal work of Fonseca & Müller that laid the foundations for an -free setting under the more general assumption of satisfying the constant rank property; seeĀ (8) below.222A recent result of RaitaĀ [raitua2019potentials], crucial to this work, establishes that Dacorognaās assumption and the constant rank assumption are locally equivalent, up to considering of higher-order (see LemmaĀ 5.1). The authors generalized Morreyās notion of quasiconvexity to the -free setting and showed that the necessary and sufficient condition for the lower semicontinuity ofĀ (1)-(2), under -growth and -equi-integrability assumptions, was precisely the -quasiconvexity of the integrand. Fonseca & Müller also extended KinderlehrerāPedregalās characterization theorem to the -free setting by showing that a family of probability distributions is a Young measure generated by a -equi-integrable sequence of -free maps if and only if the following two conditions hold:
- (i)
there exists such that and
[TABLE] 2. (ii)
at -almost every , Jensenās inequality
[TABLE]
holds and all -quasiconvex integrands with -growth at infinity.
The generalization of this result to generalized Young measures without the -equi-integrability assumption in the range was later established by Fonseca & KružĆkĀ [kruzik]. In the generalized Young measure framework for , the only characterization results are restricted to two well-known potential structures, gradients Ā ([kristensen2010characterizatio]) and symmetrized gradients ([de-philippis2017characterizatio]).333During the peer revision process of this work, Kristensen & RaitaĀ [kristensen2019oscillation, ThmĀ 1.1] have proposed an interesting alternative proof of the characterization of -free generalized Young measures (a version of TheoremĀ 1.1), which seems to appeal to different methods to the ones presented here. The well-established proofs for the case when cited above rely on the strong rigidity properties that gradients and symmetric gradients possess. However, such properties are not known to hold for general higher-order operators. Up to now, the only -free result in the generalized setting was a partial characterization due to BaĆa, Matias & SantosĀ [baia2013]. There, the authors characterize all generalized Young measures generated by -free measures under the following somewhat restrictive assumptions: (a) The operator is assumed to be of first-order. This implies that its associated principal symbol map is a linear map. In turn, this allows for rigidity and homogenization-type arguments which unfortunately fail for higher order operators. (b) The characterization is restricted to Young measures generated by sequences , where the limiting measure satisfies the following Morrey-type bound
[TABLE]
This upper-density bound on is in general too restrictive for applications as it rules out -rectifiable measures. For instance, every non-degenerate closed smooth curve defines a divergence-free measure by setting .
The purpose of this work is to give a full characterization of all generalized Young measures generated by -free measures, as well as a characterization of generalized Young measures generated by -gradients, for operators and satisfying the constant rank property. Therefore, we extend the aforementioned results into a unified general setting that allows for the appearance of mass concentrations in the case . Our strategy departs from previous ones (even in the case of gradients) in the sense that we do not work with averaged Young measure approximations nor rely on the rigidity of PDE-constrained measures. Instead, we work with Lebesgue-point continuity properties and the gluing of local generating sequences at the level of potentials; it is for this last point that the constant rank property is fundamental because it guarantees Sobolev-type regularity estimates when the kernel of (or ) is removed. It is worth to mention that the characterization for -free measures presented here does not deal with characterizations up to the boundary. The main assumption being that a generating sequence does not concentrate mass on the boundary . In this regard, the work of BaĆa, Krƶmer & KružĆkĀ [BKK18] addresses the characterization of generalized gradient Young measures up to the boundary; such results for general operators are yet to be explored.
1.2. Comments on the constant rank assumption
It is worthwhile to briefly discuss the role that the constant rank assumption plays for both the -free setting and the -potential setting. On the one hand, potentials allow for localizations of the form . In the case of gradients, these localizations are stable thanks to PoincarĆ©ās inequality . For general , this type of PoincarĆ© estimates only holds after removing the kernel of , i.e., , where is the (-)projection onto . At the time the Fonseca-Müller characterization was given, one of the challenges was the lack of a potential structure for -free fields. In this regard, Fonseca and Müllerās strategy in the -free setting departs from the one of Kinderlehrer and Pedregal, because localizations had to be carried out at the level of the -free field . In order to handle this localization, the authors relied on the use of the equivalent estimate , often referred as the Fonseca-Müller projection in the calculus of variations (it is, in fact, a CalderónāZygmund-type bound). In either case, the constant rank property is a sufficient and necessary condition for the boundedness of both PoincarĆ©ās and FonsecaāMüllerās estimates (seeĀ [guerra]).
While most of the physically relevant applications are modeled by operators that do satisfy the constant rank property (see Section 2), the variational theory in the setting (1)-(2)/(1)-(3) is not restricted to operators satisfying the constant rank property. Notably, Müller [muller_diagonal] characterized all (classical) Young measures generated by diagonal gradients. This setting is associated to the operator , which is one of the simplest examples of an operator that does not satisfy the constant rank property (see [tartar1979compensated-com]). Other related work about the understanding of PDE-constraints where the constant rank property is not a main assumption include [de-philippis2017characterizatio, arroyo-rabasa2018dimensional-est, tartar], and more recently [new].
1.3. Set-up and main results
We assume throughout the paper that is an open set, and that is an open and bounded set satisfying . Here, denotes the -dimensional Lebesgue measure.
We work with a homogeneous partial differential operator (or ), from to (or to ), of the form
[TABLE]
where (and ) are finite dimensional inner product euclidean spaces. Here is a multi-index with modulus and represents the distributional derivative . Our main assumption on (and ) is that it satisfies the following constant rank property: there exists a positive integer such that
[TABLE]
where the tensor-valued -homogeneous polynomial
[TABLE]
is the principal symbol associated to the operator . Here, . We also recall the notion of wave cone associated to , which plays a fundamental role for the study of -free fields, as discussed in the work of Murat & TartarĀ [murat1978compacite-par-c, tartar1979compensated-com, tartar1983the-compensated, murat1985optimality-cond]:
[TABLE]
The wave cone contains those Fourier amplitudes along which it is possible to construct highly oscillating -free fields. More precisely, if and only if there exists such that for all .
Let us begin our exposition by introducing a few concepts about the theory of generalized Young measures (as introduced inĀ [diperna1987oscillations-an], and later extended inĀ [alibert1997non-uniform-int]):
Definition 1.1** (Generalized Young measure).**
A triple is called a locally bounded generalized Young measure on , with values in , provided that
- (i)
is a weak- measurable map, 2. (ii)
is a non-negative Radon measure on , 3. (iii)
is a weak- -measurable map, where is the unit sphere in , and 4. (iv)
the map x\mapsto\langle|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|,\nu_{x}\rangle belongs to .
If moreover,
- (iv)
the map x\mapsto\langle|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|,\nu_{x}\rangle belongs to , and 2. (v)
is a finite measure,
then we say that is a generalized Young measure. We write to denote the set of locally bounded generalized Young measures, and to denote the set of generalized Young measures.
Notation. In the following and when no confusion arises, we will often refer to generalized Young measures simply as Young measures. We will also write
[TABLE]
Definition 1.2**.**
We say that a sequence of measures generates the Young measure if and only if
[TABLE]
for all integrands ; see SectionĀ 4.2 for the precise definition of . In this case we write
[TABLE]
Next, we incorporate the PDE constraint into the concept of generalized Young measure. Let us recall that for all . Here, is the dual exponent of and is the closure of with respect to the -norm.
Definition 1.3** (Generalized -free Young measure).**
A Young measure is called a generalized -free Young measure if there exists a sequence such that
[TABLE]
and
[TABLE]
We write to denote the set of such Young measures.
1.3.1. Characterization of -free Young measures
Let us begin by recalling the definition of -quasiconvexity, which will be a necessary concept to state the main characterization theorem.
Definition 1.4**.**
A locally bounded Borel integrand is called -quasiconvex if
[TABLE]
for all periodic fields satisfying
[TABLE]
We will also require to define a weaker notion of recession function. For a Borel integrand with linear growth at infinity, we define its upper recession function as
[TABLE]
Differently from , the upper recession function always exists and defines an upper semicontinuous and positively -homogeneous function on .
We are now in position to state our main characterization results. The first result extends the HahnāBanach-type characterizationĀ [fonseca1999mathcal-a-quasi, TheoremĀ 4.1] to sequences of weak- convergent measures:
Theorem 1.1**.**
*Let . Then, is a generalized -free Young measure if and only ifĀ *
- (i)
there exists satisfying
[TABLE]
and
[TABLE]
- (ii)
at -almost every , the Jensen-type inequality
[TABLE]
holds for all -quasiconvex upper-semicontinuous integrands with linear growth at infinity, and
- (iii)
at -almost every ,
[TABLE]
Remark 1.1**.**
If is defined in its essential domain, i.e.,
[TABLE]
then the purely singular part of is unconstrained since then (iii) is equivalent to the trivial set inclusion
[TABLE]
In SectionĀ 2, we shall revise a few examples of operators that satisfy this property.
Remark 1.2**.**
The condition at regular points, embodied by property (ii), conveys a similar constraint for the supports of and on a set of full -measure. The results contained in CorollaryĀ 4.1 imply that is the translation of a probability measure supported on , i.e.,
[TABLE]
The same corollary also conveys that property (iii) holds -a.e., that is,
[TABLE]
On the other hand, the property at singular points (iii) is equivalent to the complementary Jensenās inequality
[TABLE]
This follows directly from the structure theorem for -free measuresĀ [de-philippis2016on-the-structur, TheoremĀ 1.1] and the rigidity results established inĀ [kirchheim2016on-rank-one-con].
Our second result characterizes generalized -free Young measures in terms of their tangent cone (in the spirit ofĀ [rindlerlocal]); definitions of tangent Young measures will be postponed to SectionĀ 4.2.
Theorem 1.2**.**
Let . Then, is a generalized -free measure if and only if
- (i)
there exists satisfying
[TABLE]
and
[TABLE]
- (ii)
at -almost every , there exists a tangent Young measure
[TABLE]
such that for all open and Lipschitz subsets with .
We close the characterization of -free Young measures with an application of the methods developed in this paper, which allows us to re-define -free measures in terms of a pure -free constraint:
Corollary 1.1**.**
Let . The following are equivalent:
- (i)
* is a generalized -free Young measure,*
- (ii)
* is generated by -free measures.*
1.3.2. Area strict density of absolutely continuous -free measures
Independently of the characterization of -free Young measures, our methods allow us to show that an -free measure defined on an open and bounded domain can be approximated in the area-strictly sense of measures, by a sequence of -free functions. This approximation result is of relevance to certain minimization principles involving the relaxation of functionals of the form
[TABLE]
Frequently, it has been accepted to impose a geometric assumption on that guarantees the approximation of -free measures by -integrable -free fields in the strict sense of measures (see for instanceĀ [muller1987homogenization-, arroyo-rabasa2017relaxation-and-, arroyo-rabasa2017lower-semiconti]). More precisely, that is a strictly star-shaped domain, i.e., there exists such that
[TABLE]
The approximation result contained in TheoremĀ 1.3 below allows, in particular, to dispense with this assumption on the geometry of . In order to state this result we need to introduce the following basic concept. The area functional of a measure is defined as
[TABLE]
In addition to the well-known weak- convergence of measures, we say that a sequence converges in area to in if
[TABLE]
This notion of convergence turns out to be stronger than the conventional strict convergence of measures, which requires . The usefulness of this form of convergence rests in the fact that the functional
[TABLE]
is area-continuous on for all integrands such that the strong recession function exists on (seeĀ [kristensen2010characterizatio, TheoremĀ 5]).
We have the following area-convergence approximation result (see SectionĀ 4.2 for the definition of elementary Young measures ):
Theorem 1.3**.**
Let be an open and bounded set and let be a bounded -free measure. Then there exists a sequence , satisfying
[TABLE]
[TABLE]
and
[TABLE]
Remark 1.3**.**
Notice that we do not require to be Lipschitz nor . The regularity of the recovery sequence can be lifted to be of class for any .
1.3.3. Characterization of generalized -gradient Young measures
In this section we state the characterization results that belong to the potential settingĀ (1)-(3).
Let be a homogeneous linear operator of arbitrary order, from to , and assume that satisfies the constant rank propertyĀ (8). Let us first introduce the notion of -gradient Young measure:
Definition 1.5**.**
A Young measure is called a generalized -gradient Young measure if there exists a sequence such that and
[TABLE]
We write to denote the set of these Young measures.
Remark 1.4**.**
We do not require that the sequence of generating potential measures is uniformly bounded. However, of course, the sequence must be uniformly bounded since it generates .
Since is satisfies the constant rank property, the results inĀ [raitua2019potentials] (see also SectionĀ 5) yield the existence of an annihilator operator for . More precisely, there exists from to as inĀ (7) such that
[TABLE]
A localization argument and an application of the Fourier transform imply that -gradients are -free fields and therefore, in this case,
[TABLE]
A more interesting question in this context is to understand how far is a generalized -free measure from being a generalized -gradient Young measure. The first step to answer this question is to notice that, by a slight modification of the proof of TheoremĀ 1.2, we obtain the following local characterization:
Theorem 1.4**.**
Let . Then, if and only if
- (i)
there exists such that
[TABLE]
- (ii)
at -almost every , there exists a tangent Young measure
[TABLE]
such that for all open Lipschitz sets with .
Now, before stating the analog of TheoremĀ 1.1 for -gradients, we will need to adapt some of the preliminary definitions of the -framework into the -framework. In the case of potentials, the role of the wave cone is replaced by the image cone
[TABLE]
which contains the set of -gradients in Fourier space. The exactness propertyĀ (11) has two direct consequences: Firstly, it implies (seeĀ [raitua2019potentials, CorollaryĀ 1]) the equivalence between -quasiconvexity and -gradient quasiconvexity:
Definition 1.6**.**
A locally bounded Borel integrand is called -gradient quasiconvex if
[TABLE]
and all .
Secondly, the wave cone of coincides with the image cone of (i.e., ). These two observations and TheoremĀ 1.2 imply that and are structurally equivalent, except at their associated barycenter measures:
Theorem 1.5**.**
Let . Then, if and only if
- (i)
there exists such that
[TABLE]
- (ii)
at -almost every ,
[TABLE]
for all upper-semicontinuous -gradient quasiconvex integrands with linear growth at infinity, and
- (iii)
at -almost every , it holds
[TABLE]
We close this section with the analog of TheoremĀ 1.3 for -gradients:
Theorem 1.6**.**
Let be a bounded open set and let be such that is a bounded Radon measure. Then, there exists a sequence satisfying
[TABLE]
and
[TABLE]
2. Examples
In this section we review, with concise examples, a few of the most well-known -free and -gradient structures; most of which āwith the exception of (e)ā satisfy the spanning property
[TABLE]
Let us recall that, in this case, the point-wise relation (iii) of the singular part in TheoremsĀ 1.1 andĀ 1.5 is superfluous (cf. RemarkĀ 1.1). In the following list of examples, the labels ā-freeā or āpotentialā indicate the setting on which the operator is considered:
- (a)
Gradients (potential). Let be the gradient operator acting on functions . Clearly, is first-order operator from to . Moreover, the set of gradients in Fourier space is
[TABLE]
which is a generating set of . 2. (b)
Higher order gradients (potential). In the same context as the last point, the -gradient operator
[TABLE]
is a -th order operator from to , where is the space of -th order symmetric tensors. The set of -th order gradients in Fourier space is the set
[TABLE]
A standard polarization argument implies that indeed spans . 3. (c)
Symmetric gradients (potential). The symmetric gradient of a vector field is defined as as . Clearly, defines a first-order operator from to . The space of Fourier symmetric gradients is given by
[TABLE]
which, again by a polarization argument, can be seen to generate . 4. (d)
Deviatoric operator (potential). The operator that considers only the shear part of the symmetric gradient is given by
[TABLE]
where is the identity in . Therefore, is a first-order operator form to . The set of shear symmetric gradients in Fourier space is the set
[TABLE]
This set contains all the tensors of the form and for , which conform a basis of the trace-free symmetric tensors. 5. (e)
The Laplacian (-free and potential). An interesting case is the Laplacian operator
[TABLE]
The Laplacian is a 2nd order operator from to . The -free perspective of the Laplacian corresponds to the variational properties of the harmonic functions. The first statement of LemmaĀ 3.1 gives and
[TABLE]
This says that there are no concentration nor oscillation effects occurring along sequences of uniformly bounded harmonic maps. Of course, this is not surprising since harmonic functions satisfy local -estimates.
The -potential perspective is completely opposite (). Indeed, since is a full-rank elliptic operator, then the second statement in LemmaĀ 3.1 implies that
[TABLE]
which says that being generated by the Laplacian of a sequence of functions represents no constraint. Heuristically, this is also not surprising due to existence of a fundamental solution for the Laplacian. 6. (f)
Solenoidal measures (-free). Let us consider the scalar-divergence operator
[TABLE]
This defines a first-order operator from to . It is straightforward to verify
[TABLE]
In particular, every div-quasiconvex function is convex (cf. SectionĀ 4.3). This, implies that both the constitutive relations of the absolutely continuous and singular parts of solenoidal Young measures are fully unconstrained:
[TABLE]
where [\bm{\nu}]=\bigl{\langle}\operatorname{id}_{\mathbb{R}^{d}},\nu\bigr{\rangle}+\lambda\bigl{\langle}\operatorname{id}_{\mathbb{R}^{d}},\nu^{\infty}\bigr{\rangle} is the barycenter of . 7. (g)
Normal currents (-free and potential). The following framework has recently received attention in light of the new ideas proposed to study certain dislocation models, which are related to functionals defined on normal -currents without boundary (boundaries of normal -currents). For a thorough understanding of these models, we refer the reader toĀ [conti2015dislocations, hudson2018existence] and references therein.
Let be an integer. The space of -dimensional currents consists of all distributions . The boundary operator acts (in the sense of distributions) on -dimensional currents as
[TABLE]
Therefore is first-order operator from to . De Rhamās theorem implies that is a constant rank operator. Indeed, for all . Hence is continuous on the sphere, and thus also constant. The space of -dimensional normal currents is defined as the space of -currents , such that both and can be represented by measures:
[TABLE]
We say that is a current without boundary provided that . In this context, we say that
- (i)
is an -current Young measure without boundary, 2. (ii)
is an -boundary Young measure.
Notice that the symbol of acts on -vectors precisely as the interior multiplication . If is a basis of , then for all and all . In particular
[TABLE]
If we consider as a potential, then De Rhamās theorem gives
[TABLE]
3. Applications
In this section we discuss some applications of the dual characterizations. First, we give an explicit description of the Young measures, both from the -free and potentials perspectives, associated to full-rank elliptic systems. The remaining sections are devoted to discuss, mostly via abstract constructions, the failure of classical compensated compactness results in the setting.
3.1. Young measures generated by full-rank elliptic operators
We show that, for a full-rank elliptic operator, we can give a simple characterization of the -constrained Young measures. Let us define first define ellipticity:
Definition 3.1**.**
We say that a homogeneous linear operator of order , from to , is elliptic if there exists such that
[TABLE]
If moreover , then we say that is a full-rank elliptic operator.
The following result says that the sets of -free and -gradient generalized Young measures are trivial for (full-rank) elliptic operators:
Lemma 3.1**.**
Assume that is an elliptic operator from to . Then,
[TABLE]
If moreover is a full-rank elliptic operator, then also
[TABLE]
Proof.
Let us prove the first statement. Let us fix . The ellipticity of implies that the only mean-value zero -free smooth -periodic map is the zero function. Indeed, if is -free, then applying the Fourier transform (on the torus) to the equation gives
[TABLE]
If moreover has mean-value zero, this shows that for all . Or equivalently, . Therefore, by definition, every integrand is -quasiconvex. Since separates (see LemmaĀ 4.1), then properties (i)-(iii) in TheoremĀ 1.1 imply that must be an elementary Young measure, i.e.,
[TABLE]
The ellipticity of implies that and henceĀ [de-philippis2016on-the-structur, TheoremĀ 1.1] implies that . This proves that \bm{\nu}=(\delta_{w},0,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,) for some -free integrable map .
We now show the statement for the potential perspective when is a full-rank elliptic operator. If , then is equivalent to the operator acting on real-valued functions of one-variable. Therefore, in the case , the second statement follows directly from the compactness properties of -functions and existence of primitives on open intervals of the real-line (quasiconvexity is equivalent to convexity in this case). We shall focus on the case . Since is a full-rank elliptic operator, the algebraic equation , is soluble for all . Therefore, if with , then
[TABLE]
belongs to and satisfies . Here \widehat{\,}\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\, denotes the Fourier transform on the -dimensional torus. This observation and a density argument convey that a function is -gradient quasiconvex if and only if is constant. This, in turn, conveys that (ii)-(iii) TheoremĀ 1.5 hold trivially for all . Now, we show that property (i) is also holds trivially. Since is onto for all non-zero frequencies, then exists and is homogeneous of degree on . ByĀ [HormanderBook, Thms.Ā 3.2.3 and 3.2.4], extends to a distribution \mathbb{T}^{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,}\in\mathcal{D}^{\prime}(\mathbb{R}^{d};\mathrm{Lin}(X,W)) satisfying p\mathbb{T}^{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,}=(p\mathbb{T})^{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,} for all homogeneous polynomials of degree . Moreover \mathcal{F}\mathbb{T}^{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,} is smooth on (here is the Fourier transform on ). Setting K_{\mathcal{A}}\coloneqq\mathrm{i}^{k}\mathcal{F}\mathbb{T}^{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,} we find that if , then satisfies (here we are using that is a tensor-valued homogeneous polynomial of degree ). Thus, inverting the Fourier transform, we find that
[TABLE]
Moreover, since , then up to a complex constant,
[TABLE]
for all multi-indexes such that . The multiplier is homogeneous of degree zero and smooth on . Therefore, by an application of the Mihlin multiplier theorem, we deduce the bound
[TABLE]
Here, in passing to the last equality we have used that so that the Riesz potential norm \|\mathcal{F}^{-1}(|\xi|^{-1}\mathcal{F}(\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,))\|_{\mathrm{L}^{q}} is an equivalent norm for .
Now, let be an arbitrary bounded measure and let be its trivial extension by zero on . Define and observe that the bound above and LemmaĀ 4.2 imply that for all . Moreover, by construction,
[TABLE]
We conclude that if , then there exists such that (i) in TheoremĀ 1.5 holds. Since (ii)-(iii) are trivially satisfied, TheoremĀ 1.5 implies that . This proves that indeed
[TABLE]
This finishes the proof. ā
3.2. Failure of -compactness for elliptic systems
In this section we collect some results and examples that showcase the lack of rigidity occurring along sequences of -free functions due to concentration effects. To account for this, let us recall that sequence of functions is said to converge weakly in if and only if there exists such that
[TABLE]
We write in . Notice that in general does not imply weak convergence in . This owes to concentrations that diffuse into an absolutely continuous part. In the generalized Young measure context, this corresponds to the analysis of on points where is non-zero and
[TABLE]
The Dunford-Pettis theorem gives the following criterion to rule out the appearance of diffuse concentrations: a sequence is sequentially weak pre-compact in if and only if is equi-integrable, i.e., for every there exists some such that for any Borel set with it holds
[TABLE]
The examples given below are intended to exhibit how classical compensated compactness assumptions fail to prevent the lack of equi-integrability of PDE-constrained sequences. We begin with the following general result, which exploits the unconstrained behavior of the singular part of -free Young measures:
Lemma 3.2**.**
Let be an arbitrary finite measure. For any fixed vector and any probability measure satisfying
[TABLE]
there exists a sequence of functions such that
[TABLE]
In particular,
[TABLE]
and
[TABLE]
Proof.
Let be sufficiently large so that . Let be the trivial extension by zero on of the measure . Define also if and if . Then, since is an open set, the triple satisfies the weak- measurability requirements to be Young measure in . We claim that is an -free measure. According to TheoremĀ 1.1 and RemarkĀ 1.1 it suffices to show that (a) , which follows by the assumption on ; and (b) that for all -quasiconvex integrands with linear growth at infinity. The latter follows from RemarkĀ 1.2 and the fact that that the restriction of to is convex at zero, i.e., for all probability measures satisfying (seeĀ [kirchheim2016on-rank-one-con]). Therefore, for -a.e. . Then, from CorollaryĀ 1.1 we deduce the existence of a sequence of -free measures that generates . By the theory discussed in SectionĀ 4.2 and a standard mollification argument we conclude that there exists a sequence (where faster than ) such that
[TABLE]
The first two statements then follow by setting . That is not equi-integrable on open neighborhoods of follows follows fromĀ [alibert1997non-uniform-int, TheoremĀ 2.9]. ā
Remark 3.1**.**
The previous result also holds if
[TABLE]
and for some (seeĀ [kirchheim2016on-rank-one-con]).
A direct consequence of this lemma is the following failure of the -rigidity for elliptic systems (cf.Ā [MullerBook, SectionĀ 2.6] andĀ [new]) for -free measures.
Corollary 3.1**.**
Let be a non-trivial subspace of and assume that has no non-trivial -connections, i.e.,
[TABLE]
Then, there exists a sequence of -free measures satisfying
[TABLE]
but
[TABLE]
Proof.
The assumption on is equivalent to requiring that . Since the class of probability measures satisfying , and is non-empty, we may chose at least one with such properties. The previous lemma implies that the triple is a generalized -free Young measure, generated by a sequence of -free measures . The first and the last two statements of the corollary follow from this observation. To prove that in , let us consider the positively -homogeneous growth integrand f=|\operatorname{id}_{W}-\pi_{L}[\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,]|=\operatorname{dist}(\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,,L), where is the linear orthogonal projection onto . Clearly and the fact that generates implies
[TABLE]
Here, we used that and . ā
The version of this result for constant rank potentials is the following:
Corollary 3.2**.**
Let be a non-trivial space satisfying
[TABLE]
Then there exists a sequence such that
[TABLE]
but
[TABLE]
The proof of this corollary follows from a version of LemmaĀ 3.2 for -gradient Young measures, which we shall not prove, but that follows by similar arguments (to ones in the proof of LemmaĀ 3.2) by using TheoremĀ 1.5 instead.
Remark 3.2**.**
In order to add some perspective to these results, let us recall a well-known result of Müller (see [MullerBook, Lemma 2.7]) that states the following: if is a space of matrices containing no rank-one connections and
[TABLE]
then in measure. This may be understood as an -rigidity for gradients. The previous corollary shows that even under -perturbations of elliptic systems, one cannot hope for sequential weak -compactness for gradients. (Here, one should not confuse weak -convergence with convergence in .)
3.3. Failure of -compactness for the -state problem
In the context of the rigidity properties for gradients, ŠverÔk [sverak] showed that if is set of matrices such that , then every sequence with uniformly bounded Lipschitz constant satisfies the following compensated compactness property:
[TABLE]
In particular, the restriction on prevents the formation of any non-trivial microstructures. Å verĆ”kās proof also implies that if is -uniformly bounded and
[TABLE]
then, up to taking a subsequence,
[TABLE]
Notice however that neither of these compensated compactness results allows for concentrations. The first one assumes a uniform Lipschitz bound and the latter (implicitly) assumes equi-integrability since in .
For the two-state problem, Garroni & NesiĀ [garroni] have shown a similar result for divergence-free fields. More recently, De Philippis, Palmieri and RindlerĀ [palmieri] have extended this to general operators . The precise statement is the following: if and is a sequence of -free functions satisfying
[TABLE]
then, up to extracting a subsequence,
[TABLE]
An interesting question to ask is what happens if we allow for concentrations, while still requiring the PDE constraint and requiring thatĀ (12) holds. The next two examples show that one cannot expect -compensated compactness if concentrations are allowed, even if the concentrations occur in the directions of .
Example 3.1**.**
If is a non-trivial operator, then there exist vectors with and a sequence such that
[TABLE]
Moreover, the sequence satisfies
[TABLE]
However, is not equi-integrable and, for any subsequence ,
[TABLE]
Similarly, we also have the following explicit example:
Example 3.2**.**
Assume that and consider the matrices
[TABLE]
Then, there exists a uniformly bounded sequence satisfying
[TABLE]
And, for any subsequence ,
[TABLE]
Both examples follow directly from the following result (and its corollary below):
Proposition 3.1**.**
Let be vectors satisfying
[TABLE]
Then, there exists a sequence of -free functions satisfying
[TABLE]
where
[TABLE]
[TABLE]
An analogous statement holds for -potentials.
Proof.
By assumption we may find constants as in the statement. The assertion then follows from LemmaĀ 3.2. ā
Remark 3.3**.**
The result of the corollary remains valid even if the vectors are mutually -disconnected, i.e.,
[TABLE]
Corollary 3.3**.**
Let be a direction in . There exists a sequence of -uniformly bounded -free measures such that
[TABLE]
In particular, is not equi-integrable on .
Notice that, if , then
[TABLE]
3.4. Flexibility of divergence-free Young measures
So far we have seen how the lack of strong constraints for the concentration part of -free measures is responsible for the lack of rigidity in a number of interesting scenarios.
Now, we review the case of the scalar divergence operator
[TABLE]
in the -free framework. As we have already seen, and hence
[TABLE]
Since condition (ii) in TheoremĀ 1.1 holds for all convex functions, and (iii) holds trivially in this case, divergence-free generalized Young measures are only constrained by the barycenter property (i). The following example exhibits howĀ (13) yields the existence of rather ill-behaved weak- convergent sequences of divergence-free fields:
Proposition 3.2**.**
Let be an arbitrary compactly supported function of bounded variation and let be an arbitrary probability measure. Define
[TABLE]
where
[TABLE]
is the fundamental solution of the scalar divergence operator. Then, for every open and bounded Lipschitz set with , there exists a sequence satisfying
[TABLE]
Proof.
Since is a compactly supported and is a Radon measure, Youngās inequality implies that . Moreover, by construction we find that the barycenter of is the Radon measure \mu=\langle\operatorname{id},\delta_{w}\rangle\,\mathscr{L}^{d}+\bigl{\langle}\operatorname{id},p\bigr{\rangle}\lambda=w\,\mathscr{L}^{d}+\langle\operatorname{id},p\rangle\lambda and hence
[TABLE]
Thus, satisfies (i)ā(iii) and hence it is an -free measure on . That can be generated on by a sequence of smooth divergence-free fields follows from the theory discussed in SectionĀ 4.2. ā
4. Preliminaries
The -dimensional torus is denoted by , and by we denote the closed -dimensional unit cube . We denote by the open cube with radius and centered at .
4.1. Geometric measure theory
Let be a locally convex space. We denote by the space of compactly supported and continuous functions on , and by we denote its completion with respect to the \|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,\|_{\infty} norm. Here, is the inductive limit of Banach spaces where are compact and . By the Riesz representation theorem, the space of bounded signed Radon measures on is the dual of ; a local argument of the same theorem states that the space of signed Radon measures on is the dual of . We denote by the subset of non-negative measures. Since is a Banach space, the BanachāAlaoglu theorem and its characterizations hold. In particular:
there exists a complete and separable metric . Moreover, convergence with respect to this metric coincides with the weak- convergence of Radon measures (see RemarkĀ 14.15 inĀ [mattila1995geometry-of-set]), that is,
[TABLE] 2. 2.
bounded sets of are -metrizable in the sense that induces the (relative) weak- topology on the unit open ball of .
In a similar manner, for a finite dimensional inner-product euclidean space , and will denote the spaces of -valued bounded Radon measures and -valued Radon measures respectively. The space is a normed space endowed with the total variation norm
[TABLE]
The set of all positive Radon measures on with total variation equal to one is denoted by
[TABLE]
the set of probability measures on . Here and all the follows we write
[TABLE]
to denote the open unit ball and the unit sphere on respectively. Rieszā representation theorem states that every vector-valued measure can be written as
[TABLE]
This decomposition is commonly referred as the polar decomposition of . The set of points where
[TABLE]
is satisfied, is called the set of -Lebesgue points. This set conforms a full -measure set of , i.e, . In what follows, we shall always work with good representatives of -integrable maps. If , then satisfies
[TABLE]
If are Radon measures over , and , then the Besicovitch differentiation theorem states that there exists a set of zero -measure such that
[TABLE]
where is the RadonāNykodým derivative of with respect to . Another resourceful representation of a measure is given by the RadonāNykodýmāLebesgue decomposition which we shall frequently denote as
[TABLE]
where as usual , .
4.1.1. Push-forward measures
If is Borel measurable, the image or push-forward of under is defined by the formula
[TABLE]
If is a Borel map, then
[TABLE]
whenever the integrals above exist or if is integrable.
4.1.2. Tangent measures
In this section we recall the notion of tangent measure as introduced by PreissĀ [preiss1987geometry-of-mea]. Let and consider the map , which blows up , the open ball around with radius , into the open unit ball . The push-forward of under is given by the measure
[TABLE]
A non-zero measure is said to be a tangent measure of at , if there exist sequences and such that
[TABLE]
in this case the sequence is called a blow-up sequence. We write to denote the set of all such tangent measures.
Using the canonical zero extension that maps the space into the space we may use most of the results contained in the general theory for tangent measures when dealing with tangent measures defined on smaller domains. The following theorem, due to Preiss, states that one may always find tangent measures.
Theorem 4.1** (TheoremĀ 2.5 inĀ [preiss1987geometry-of-mea]).**
If is a Radon measure over , then for -almost every .
This property of Radon measures measures will play a silent, but fundamental role, in our results. We shall use it to āamendā the current lack of a PoincarĆ© inequality for general domains; this, becauseĀ (14) acts as an artificial extension operator for tangent measures restricted to the unit cube . Returning to the properties of tangent measures, one can show (see Remark 14.4 inĀ [mattila1995geometry-of-set]) that, for a tangent measure , it is always possible to choose the scaling constants in the blow-up sequence to be
[TABLE]
for any open and bounded set containing the origin and with the property that , for some positive constant ; this process may involve passing to a subsequence. Then, fromĀ [preiss1987geometry-of-mea, ThmĀ 2.6(1)] it follows that at -almost every we can find as the weak- limit a blow-up sequence of the form
[TABLE]
Yet another special property of tangent measures is that at, -almost every , it holds that
[TABLE]
which in particular conveys that tangent measures are generated by strictly-converging blow-up sequences. If are two Radon measures with , i.e., that is absolutely continuous with respect to , then (see Lemma 14.6 ofĀ [mattila1995geometry-of-set])
[TABLE]
Then, a consequence ofĀ (15) and Lebesgueās differentiation theorem is that
[TABLE]
In fact, if , then it is an simple consequence from the Lebesgue Differentiation Theorem that
[TABLE]
4.2. Integrands and Young measures
Bounded generalized Young measures conform a set of dual objects to the integrands inĀ . We recall briefly some aspects of this theory, which was introduced by DiPerna and Majda inĀ [diperna1987oscillations-an] and later extended inĀ [alibert1997non-uniform-int, kristensen2010characterizatio].
Notation. We remind the reader that denotes an open set and denotes an open an bounded set with .
For ) we define the transformation
[TABLE]
where denotes the open unit ball in . Then, . We set
[TABLE]
Heuristically, is isomorphic to the continuous functions on the compactification of that adheres to it each direction at infinity. In particular, all have linear growth at infinity, i.e., there exists a positive constant such that for all and all . With the norm
[TABLE]
the space turns out to be a Banach space and is an isometry with inverse
[TABLE]
Also, by definition, for each the limit
[TABLE]
exists and defines a positively -homogeneous function called the strong recession function of . Moreover every satisfies
[TABLE]
In particular, there exists a modulus of continuity , depending solely on the uniform continuity of , such that
[TABLE]
For an integrand and a Young measure , we define a duality paring between and by setting
[TABLE]
The barycenter of a Young measure is defined as the measure
[TABLE]
The generation of a Young measure is (cf. DefinitionĀ 1.2) a local property in the sense that
[TABLE]
for all open Lipschitz sets with . In many cases it will be sufficient to work with functions that are Lipschitz continuous and compactly supported on the -variable. The following density lemma can be found inĀ [kristensen2010characterizatio, LemmaĀ 3].
Lemma 4.1**.**
There exist countable families of non-negative functions and Lipschitz integrands such that, for any given two Young measures ,
[TABLE]
Remark 4.1**.**
Bounded sets of are metrizable with respect to the weak- topology (seeĀ [BrezisBook, Theorem 3.28]).
Since is contained in the dual space of via the duality pairing \llangle\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,\rrangle, we say that a sequence of Young measures weak- converges to , in symbols , if
[TABLE]
Fundamental for all Young measure theory is the following compactness result, seeĀ [kristensen2010characterizatio, Section 3.1] for a proof.
Lemma 4.2** (compactness).**
Let be a sequence of Young measures satisfying
- (i)
the family \Bigl{\{}\,\bigl{\langle}|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|,{\nu}_{j}\bigr{\rangle}\ \textup{{:}}\ j\in\mathbb{N}\,\Bigr{\}} is uniformly bounded in ,
- (ii)
.
Then, there exists a subsequence (not relabeled) and such that in .
The RadonāNykodýmāLebesgue decomposition induces a natural embedding
[TABLE]
via the identification . Notice that a sequence of measures generates the Young measure in if and only if
[TABLE]
for all Lipschitz subdomains with .
Remark 4.2**.**
For a sequence that area-strictly converges to some limit , it is relatively easy to characterize the (unique) Young measure it generates. Indeed, an immediate consequence of the Separation LemmaĀ 4.1 and a version of Reshetnyakās continuity theorem (seeĀ [kristensen2010characterizatio, TheoremĀ 5]) is that
[TABLE]
Since tangent Young measures are only locally bounded, it will also be convenient to introduce a concept of locally bounded -free Young measure:
Definition 4.1**.**
A Young measure is called a locally bounded generalized -free Young measure if there exists a sequence such that
[TABLE]
and
[TABLE]
for all Lipschitz open sets with .
The proof of the following result follows the same principles used in the proof ofĀ [arroyo-rabasa2017lower-semiconti, Lem.Ā 2.15] with .
Proposition 4.1**.**
Let be a Young measure generated by a sequence of the form . If there exists another sequence that satisfies
[TABLE]
then
[TABLE]
The following notion of translation or shift of a Young measure will be used to deal with the fact that might be in fact larger than in the proof of TheoremĀ 1.1.
Definition 4.2** (-shifts).**
We define the -shift of a generalized Young measure , with respect to , as
[TABLE]
Notice that if , then
[TABLE]
For a subset we write
[TABLE]
4.2.1. Tangent Young measures
Similarly to the case of measures, we can define the push-forward of Young measures. If is Borel, the push-forward of under is the Young measure acting on as
[TABLE]
Suppose that . A non-zero Young measure is said to be a tangent Young measure of at if there exist sequences and such that
[TABLE]
for all with . The set of tangent Young measures of at will be denoted as . Since Young measures can be seen, via disintegration, as Radon measures over , the property of tangent measures contained in TheoremĀ 4.1 lifts to a similar principle for tangent Young measures:
Proposition 4.2**.**
If is a Young measure, then
[TABLE]
Young measures also enjoy a Lebesgue-point property in the sense that a tangent Young measure truly represents the values of around . More precisely, we have the following localization principle for -almost every : every tangent measure is a homogeneous Young measure of the form
[TABLE]
We state two general localization principles for Young measures, one at regular points and another one at singular points. These are well-established results, for a proof we refer the reader toĀ [rindler2011lower-semiconti, rindler2012lower-semiconti]; see also the Appendix inĀ [arroyo-rabasa2017lower-semiconti].
Proposition 4.3**.**
Let be a generalized Young measure. Then for -a.e.Ā there exists a regular tangent Young measure , that is,
[TABLE]
Proposition 4.4**.**
Let be a generalized Young measure. Then there exists a set with such that for all there exists a singular tangent Young measure , that is,
[TABLE]
This properties tell us that certain aspects of the weak- measurable maps and belonging to can be effectively studied by looking at tangent measures of itself. In a similar fashion toĀ (14), at every where PropositionĀ 4.3 holds, we may find a tangent Young measure as inĀ (21) with
[TABLE]
and is generated by a blow-up sequence as inĀ (20) where
[TABLE]
in any case can be taken to be (\llangle|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|,\bm{\nu}\mathbin{\vrule height=6.88889pt,depth=0.0pt,width=0.55974pt\vrule height=0.55974pt,depth=0.0pt,width=5.59721pt}Q_{r}(x)\rrangle)^{-1}. At singular points we may assume without loss of generality that
[TABLE]
4.3. -quasiconvexity
We write to denote the -dimensional flat torus. We this convention we have . For a function , we write
[TABLE]
In all that follows we shall write to denote the subspace of smooth, -valued periodic functions with mean-value zero. We recall, from the theory discussed inĀ [arroyo-rabasa2017lower-semiconti, SectionĀ 2.5], that maps
[TABLE]
This set contention will be crucial for the proof of TheoremĀ 1.1.
Definition 4.3** (-quasiconvex envelope).**
If is a locally bounded Borel integrand, we define its -quasiconvex envelope as
[TABLE]
If is a locally bounded Borel integrand, we define its -quasiconvex envelope as
[TABLE]
Below we recall some well-known convexity and Lipschitz properties of -quasiconvex functions.
Let be a balanced cone of directions in , that is, we assume that for all and every . A real-valued function is said to be -convex provided its restrictions to all line segments in with directions in are convex. We recall the following -convexity property of -quasiconvex functions contained in lemma fromĀ [fonseca1999mathcal-a-quasi, PropositionĀ 3.4] for first-order operators and inĀ [arroyo-rabasa2017lower-semiconti, LemmaĀ 2.19] for the general case:
Lemma 4.3**.**
If is locally finite and -quasiconvex, then is -convex.
In SectionĀ 9, we will require to work around the fact that may not necessarily be equal to . The following definition and propositions will play an important role in this regard.
Definition 4.4**.**
For a Borel integrand , we define the integrand given by
[TABLE]
where is the canonical linear projection onto .
If , we also write to denote the integrand
[TABLE]
Proposition 4.5**.**
Let be a locally bounded Borel integrand. The following holds:
- (a)
, 2. (b)
if is -quasiconvex, then is -quasiconvex, 3. (c)
if is -convex, then is -convex, 4. (d)
if is -convex with linear growth constant . Then is globally Lipschitz with
[TABLE]
for some constant .
Proof.
Property (a) is a direct consequence ofĀ (25) and the definition of (\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)\,\tilde{}ā. Property (b) follows directly from (a). Property (c) follows from LemmaĀ 4.3, property (b) and the fact that is invariant on -directions. Finally, we prove (d). Up to a linear isomorphism we may assume that contains an orthonormal basis basis of . Of course, the change of variables carries a constant in the desired Lipschitz bound, but that constant depends solely on . The difference between two points can be written as
[TABLE]
where the constant of the last estimate depends solely on . Property implies that is -convex. Since moreover is a spanning set of directions of , thenĀ [kirchheim2016on-rank-one-con, LemmaĀ 2.5] implies that
[TABLE]
An iteration of this identity yields the upper bound
[TABLE]
Since , we may further estimate this difference by
[TABLE]
Reversing the roles of and gives the desired Lipschitz bounds. ā
Corollary 4.1**.**
Let and let , be two probability measures satisfying
[TABLE]
for all -quasiconvex upper semicontinuous integrands with linear growth. Then,
[TABLE]
and
[TABLE]
Proof.
If , then we have nothing to show. Else, let and let be an arbitrary integrand. We also define . It follows from PropositionĀ 4.5(a) that . If we choose , then and the assumption on yields
[TABLE]
where is the push-forward of with respect to . Since separates , this implies that . In particular
[TABLE]
This proves that , and therefore also
[TABLE]
A similar argument and the previous identity further imply
[TABLE]
In particular, testing with g=|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|_{X}, we conclude that, either , or . This proves that , as desired. ā
The next two propositions will be used to address some technical details involving the proof of TheoremĀ 1.1 and RemarkĀ A.1:
Proposition 4.6**.**
Let and assume that there exists a dense set such that
[TABLE]
Then
[TABLE]
for some constant depending on and .
Proof.
Since , there exists a constant such that . It follows from the definition of -quasiconvexity (testing with the field ) that
[TABLE]
It follows from PropositionĀ 4.5(c) and a suitable version ofĀ [kristensen1999, Lemma 2.5] that, if , then
[TABLE]
where . The cited result and its proof are originally stated for quasiconvex functions. However, a similar argument can be given for -convex functions where is a spanning balanced cone. This shows that the restriction of on has linear growth at infinity. We shall prove now that is finite for all . Let us assume that there exists with . Let us fix be a large real number. By our assumption on , we may find a smooth field satisfying
[TABLE]
The density of allows us to find a sequence satisfying . We use once again the fact that to deduce that is uniformly continuous on where . Hence, we may use a standard modulus of continuity argument to conclude that
[TABLE]
Letting we conclude that for sufficiently large. This poses a contradiction to the boundĀ (26). Repeating the first step with , we find that
[TABLE]
This finishes the proof. ā
Proposition 4.7**.**
Let be locally bounded and assume that is locally finite. Fix , and let be an -free field satisfying
[TABLE]
where \tilde{f}^{\varepsilon}\coloneqq\tilde{f}+\varepsilon|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|. Then,
[TABLE]
for some constant depending on and the linear growth constant of .
Proof.
Since is finite, then it has linear growth with a constant that depends solely on and the linear growth constant of (cf. LemmaĀ 4.6). The same holds for since up to taking instead. Using the assumption we get
[TABLE]
The conclusion follows directly from this estimate. ā
Proposition 4.8**.**
Let be such that \mathcal{Q}_{\mathcal{A}}f(x,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)>-\infty for all . Fix . Then, there exists a modulus of continuity such that
[TABLE]
for all and . The modulus of continuity depends on , the linear growth constant of and the modulus of continuity of .
Proof.
We begin with two observations. First, that \mathcal{Q}_{\mathcal{A}}\tilde{f}(x,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,) is finite implies that it has linear growth and that is globally Lipschitz with constants that depend solely on and the linear growth constant of (cf. PropositionsĀ 4.5 andĀ 4.6). Now, let and let be such that (denoting H\coloneqq\mathcal{Q}_{\mathcal{A}}\tilde{f}^{\varepsilon}(x,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,))
[TABLE]
The previous proposition yields that . By definition, we get
[TABLE]
where
[TABLE]
The desired bound follows by letting and exchanging the roles of . ā
4.4. Sobolev spaces
In order to continue our discussion, we need to recall some facts of the theory of general Sobolev spaces. The following definitions and background results about function spaces and the Fourier transform can be found in the monographs of AdamsĀ [adamsbook, SectionĀ 1] and SteinĀ [steinbook, SectionĀ VI.5], as well as the full compendium of definitions and results contained in the book of TriebelĀ [triebelbook].
Recall that denotes the -dimensional flat torus. Let and let . The Sobolev space is the collection of -periodic functions all of whose distributional derivatives with belong to . The norm of is
[TABLE]
Remark 4.3**.**
.
Since the torus is a compact manifold, we also have . Calderón showed (see [adamsbook, Thm 1.2.3]) the equivalence between the classical Sobolev spaces and the Bessel potential spaces, which are defined as
[TABLE]
where and (\widehat{\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,}) denote the Fourier transform on periodic maps (see the next section). We shall henceforth make indistinguishable use of \|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,\|_{\mathrm{W}^{-\ell,p}} and \|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,\|_{\mathrm{L}^{-\ell,p}} as norms of . A standard Hahn-Banach argument (see for instanceĀ [BrezisBook, Prop. 9.20] for the case ) shows that if and only if there exists a family such that
[TABLE]
and
[TABLE]
Here . If is a family of standard mollifiers at scale , then the representation above implies that
[TABLE]
Remark 4.4**.**
This shows that
[TABLE]
under standard mollification.
Crucial to our theory are the following direct consequences of Morreyās embedding theorem (see CorollaryĀ 9.14 in Sec.Ā 9.3 and RemarkĀ 20 in SectionĀ 9.4 ofĀ [BrezisBook]):
Theorem 4.2**.**
Let and let be an open set or . Then
[TABLE]
Corollary 4.2**.**
Let be an open and bounded set or . Then
[TABLE]
Proof.
Notice that . Then, Morreyās embedding and AscoliāArzelĆ ās theorem convey the compact embedding . Since these are Banach spaces, the assertion follows directly fromĀ [BrezisBook, TheoremĀ 6.4]. ā
Remark 4.5**.**
Notice that it is not necessary to require that is Lipschitz or a domain with any type of regularity.
5. Analysis of constant rank operators
Let us recall that our main assumption is that is a linear operator of integer order , from to , that satisfies the constant rank condition
[TABLE]
In this section we shall assume that is a non-trivial operator, i.e., for otherwise all the results are trivially satisfied. The aim of this section is to give a simple extension of the well-known -multiplier projections for constant rank operators established by Fonseca & Müller in [fonseca1999mathcal-a-quasi]. The Fourier transform acts on periodic measures by the formula
[TABLE]
Smooth periodic functions are represented by through the trigonometric sum
[TABLE]
The choice to primarily work with Fourier series lies in the following characterization for constant rank operators due to RaitaĀ [raitua2019potentials, Thm.Ā 1] and its direct implication on periodic maps (see LemmaĀ 5.1 below): Let be an operator from to as inĀ (7). Then satisfies the constant rank condition if and only if then there exists a constant rank operator from to such that
[TABLE]
For the reminder of this section and will be assumed to satisfy the exactness relationĀ (28), we call an associated potential to (we call an associated annihilator of ).444The class of operators satisfyingĀ (28) may have more than element. Raita showed that every -free periodic field is the -gradient of a suitable potential. The following is a version for measures of the original statementĀ [raitua2019potentials, LemmaĀ 5]:
Lemma 5.1**.**
Let . Then satisfies
[TABLE]
if and only if there exists a potential such that
[TABLE]
5.1. -representatives
Denote by the orthogonal projection from to for all . A classical result of Schulenberger and WilcoxĀ [wilcox1, wilcox2] states that ifĀ (8) is verified, then the map is an analytic map on , homogeneous of degree 0. The Mihlin multiplier theorem implies that defines an multiplier on for all , and standard multiplier transference methods imply that if we set , for , and , then defines an -multiplier on via the assignment (see TheoremĀ 3.8, CorollaryĀ 3.16 and its remark below inĀ [steinweiss] for further details):
[TABLE]
By construction
[TABLE]
5.1.1. Sobolev estimates
It is well-known thatĀ (8) implies the map belongs to and is homogeneous of degree . Here, denotes the Moore-Penrose inverse of , which satisfies the fundamental algebraic identity . Partying from this identity and using that for all , one finds that
[TABLE]
The advantage of this perspective, is that it allows one to define in terms of rather than itself.555The fact that can be expressed as for some homogeneous multiplier of degree goes back to the seminal work of Fonseca & Müller [fonseca1999mathcal-a-quasi] on -free measures. The idea of exploiting the representation appeared in the work of Gustafson [gustafson] and more recently in the work of Raita [raitua2019potentials]. Recalling the seminal ideas of Fonseca and Müller [fonseca1999mathcal-a-quasi], we can exploit the representation in (31) to deduce Sobolev estimates on directly from the regularity of , as one would do for elliptic operators (see also the exposition in [raictua2018mathrm]). In order to proceed with this task let us define the auxiliary spaces
[TABLE]
where is a positive integer and . These are Banach spaces of distributions when endowed with the natural norm . Next, we show that the -representative operator can be extended to an operator with Sobolev-type properties on :
Lemma 5.2**.**
Let and let be a positive integer. There exists a continuous linear map with the following properties:
* for all ,* 2. 2.
there exists a constant such that
[TABLE] 3. 3.
* in the sense of distributions on , and* 4. 4.
.
Moreover, is well-defined with respect to the inclusions
[TABLE]
in the sense that is an extension of .
Proof.
Let us define on smooth maps as:
[TABLE]
so that property (1) follows fromĀ (31). In light of RemarkĀ 4.4, in order to prove that extends to with linear bound as in (2), it suffices to prove (2) for . Notice that once (2) has been established, it also suffices to verify that (3)-(4) hold for smooth maps; properties (3)-(4) for smooth maps follow fromĀ (29)-(30).
We shall therefore focus in proving (2) for smooth maps. Fix an integer and consider the multiplier
[TABLE]
where be a multi-index with . Consider the family defined by the rule for all and . Partial differentiation and the properties of the Fourier transform yield
[TABLE]
for all . Hence, inverting the Fourier transform at both sides of the equation gives
[TABLE]
We readily verify that is homogeneous of degree zero, analytic on . Then, in light of the transference of multipliers discussed above, the Mihlin multiplier theorem implies that the assignment extends to an -multiplier on . In particular,
[TABLE]
Here, in passing to the last equality we have used that the Mihlin multiplier theorem implies that the norms
[TABLE]
and
[TABLE]
are equivalent on . Running through all multi-indexes and using PoincarĆ©ās inequality for periodic mean-zero functions yields the sought assertion.ā
CorollaryĀ 4.2 and LemmaĀ 5.2 allow us to extend the notion of -representative to certain subspaces of measures:
Definition 5.1**.**
Let be an integer and let . If is a measure with , then by CorollaryĀ 4.2 we may define the -representative of as
[TABLE]
where is the linear map from LemmaĀ 5.2.
Notice that is well-defined regardless of the choice of , it has mean-value zero, it satisfies in and
[TABLE]
for some constant .
5.2. Localization estimates
We close this section with a useful observation for estimates concerning the localization with cut-off functions. Let . The commutator of on is the linear partial differential operator
[TABLE]
where acts as a multiplication operator. It acts on distributions as . Due to the Leibniz differentiation rule, is a partial differential operator of order from to , with smooth coefficients depending solely on the coefficients of the principal symbol and the first derivatives of . In particular, if satisfies , then by CorollaryĀ 4.2 we get
[TABLE]
and
[TABLE]
for all with .
6. Proof of the approximation theorems
6.1. Proof of TheoremĀ 1.3
Let us recall that we are given an -free measure , and we aim to find a sequence of -free measures that area-strict converges to . We may, without loss of generality assume that .
StepĀ 1. An asymptotically -free converging recovery sequence. Let . First, we show that there exists a sequence such that
[TABLE]
We give a variant of the construction given in StepĀ 2 ofĀ [arroyo-rabasa2017lower-semiconti, Sec.Ā 5.1]: Let be a locally finite partition of unity of . For a measure or function on , we set
[TABLE]
where \rho_{\varepsilon}=\varepsilon^{-d}\rho(\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,/\varepsilon) is a standard radial mollifier at scale . Let us begin with a few observations:
- (a)
Every is a compactly supported on . Therefore we may naturally consider each as an element of . 2. (b)
The -free constraint on implies that for all , where we recall that is a linear operator of order . 3. (c)
As is a locally finite partition, we can take linear operators inside and outside arbitrary sums subjected to it. In particular,
[TABLE]
By standard measure theoretic arguments we get that
[TABLE]
where in establishingĀ (39) we have used thatĀ (36) implies in (see CorollaryĀ 4.2) so that in . Then, In light ofĀ (36)-(39), for every we may choose such that (writing )
[TABLE]
Now, for a measure or function on let us define
[TABLE]
By construction we have
[TABLE]
which shows the first condition, that indeed on . In particular, the sequential lower semicontinuity of the area functional gives the lower bound
[TABLE]
Next, we prove the upper bound: We use that for all to deduce that (recall that )
[TABLE]
where the last inequality follows from the intermediate step
[TABLE]
Here, the passing to the second inequality follows from Jensenās inequality and the radial symmetry of . Hence, we conclude that
[TABLE]
This, together with the lower bound and the convergence imply that converges area-strictly to on . Lastly, we use the triangle inequality and the embedding to find that
[TABLE]
which shows that indeed strongly in .
StepĀ 2. Construction of the -free sequence. Let us fix . We write and . Then, in light of the estimates from LemmaĀ 5.2 and the triangle inequality we get
[TABLE]
This proves that in . Now, let us look at the translations . These are -free by construction, which lead us to define the following candidate for an -free recovery sequence:
[TABLE]
ClaimĀ 1. Each is -free. Indeed,
[TABLE]
ClaimĀ 2. The sequence area-strict converges to . Since already area-converges to , it suffices to show that and are asymptotically -close to each other (this is sufficient to ensure the asymptotic closeness of the area functional, which has a uniformly Lipschitz integrand). This is easily verified since
[TABLE]
This proves the second claim, which finishes the proof. ā
6.2. Proof of TheoremĀ 1.6
Let us recall that we are given with . We want to show there exists a uniformly bounded sequence such that
[TABLE]
Proof.
First we need to establish Sobolev estimates for the -representatives of localizations of an arbitrary potential .
In all that follows we may assume that . As in previous arguments, we shall indistinguishably identify compactly supported functions on with their periodic extensions on . Let be a nested family of equidistant Lipschitz open sets. By standard methods, we may find cut-off functions satisfying
[TABLE]
Let be such that . The main advantage of the potential framework is that we may localize inside the PDE: we define a sequence of smooth functions by setting . Computing the -gradient we find that, for it holds
[TABLE]
The idea now is to deduce Sobolev estimates for their -representatives following a standard bootstrapping argument: Since satisfies the constant rank condition, we may define . Then, by LemmaĀ 5.2, we deduce the a priori estimates
[TABLE]
where the constant may change from line to line and depends solely on , and . Iteration of this bounds until the th step yields
[TABLE]
for yet another constant . With these estimates in hand, the approximation argument follows almost the same lines as the one used in the proof of TheoremĀ 1.3. Therefore, we shall only give a sketch of the proof: Let be a locally finite partition of unity, and assume that so that we may apply the previous estimates on localizations of the form .
Set and . Then, first applying the bootstrapping argument above with , and subsequently with , conveys the estimate
[TABLE]
Here . 2. 2.
Similarly to the previous proof, we define
[TABLE]
where, for each , is chosen so that
[TABLE]
where . 3. 3.
It follows that
[TABLE]
This proves the convergence in . Moreover, the convexity of the area functional implies the lower bound
[TABLE] 4. 4.
We decompose , where
[TABLE]
Youngās inequality implies , and from the estimates of StepĀ 2 we deduce that
[TABLE]
Thus, the inequality implies the upper bound
[TABLE]
This proves that . We thus conclude that as desired.
This finishes the proof. ā
7. Helmholtz decomposition of generating sequences
In this section and are constant rank operators from to and to , of respective orders and . When we work in the -free context, will denote an associated potential of , which was discussed in the previous section (cf.Ā (28)) and for which LemmaĀ 5.1 holds. In all that follows is an open set and we assume that
[TABLE]
The following lemma establishes that oscillations and concentrations generated along -free sequences are, in fact, only carried by -gradients:
Lemma 7.1**.**
Let be a locally bounded -free Young measure and let be a Lipschitz open subset with . Then, on , the barycenter measure can be decomposed into the -gradient of a potential an -free field , i.e.,
[TABLE]
Moreover, there exists a sequence satisfying
[TABLE]
Lastly, if there exists such that , then may be chosen to be the zero function.
Proof.
Let be a cut-off function satisfying . Without loss of generality we may assume that . Let be a sequence of measures generating and satisfying in . We define a sequence of compactly supported measures on by setting and . Using the trivial extension by zero, we may regard each measure as an element of . For a function on the torus we write (if is a measure, we set ) to denote its mean-value. Next, define the sequence of mean-value zero maps as
[TABLE]
Indeed, thanks to LemmaĀ 5.2 and CorollaryĀ 4.2 we obtain
[TABLE]
Since in , it holds
[TABLE]
Indeed, in , while the convergence involving the commutator follows from the fact that (cf. CorollaryĀ 4.2) and that is an operator of order at most . Hence, it follows from the estimates in LemmaĀ 5.2 that
[TABLE]
This allows us to define an asymptotically -close sequence to by setting
[TABLE]
By construction is a sequence mean-value zero measures satisfying in , and hence also in . Moreover, is a sequence of -free measures since .
Next, we exploit the potential property of mean-value zero -free functions on the torus. PropositionĀ 5.1 yields potentials satisfying for all , each of which we may assume to be given by its own -representative, i.e., . Applying once more the estimates of LemmaĀ 5.2 (for instead of ), we find that
[TABLE]
Since , then is an -free measure on . We readily check, setting
[TABLE]
that
[TABLE]
This proves the first assertion on the decomposition of the barycenter on . Moreover, since , we obtain
[TABLE]
Therefore, using that strongly in , it follows from PropositionĀ 4.1 that
[TABLE]
We are left to see that we can adjust the boundary of to match the values of near . For a positive real we define . Fix to be a cut-off of with on , and such that . Let be an infinitesimal sequence of positive reals. We define a sequence with -boundary values by setting
[TABLE]
Fix . Since in , there exists such that
[TABLE]
In particular, setting , we can estimate the total variation of as
[TABLE]
Notice that this not only implies that is uniformly bounded, but also that the sequence does not concentrate mass on the boundary . Therefore, up to extracting a subsequence (which we will not relabel), the sequence generates a Young measure on which does not carry mass into the boundary, i.e.,
[TABLE]
On the other hand, our construction gives the equivalence of measures when these are restricted to the set . Since , we deduce fromĀ (42)-(43) that on , and therefore
[TABLE]
with on a neighborhood of .
The last statement follows by noticing that and hence we may simply re-define the sequence of potentials as . This finishes the proof of the lemma.ā
The proof of following lemma follows by verbatim from the first step of the proof of the lemma above:
Lemma 7.2**.**
Let be a sequence of -free measures satisfying
[TABLE]
Then, for a bounded open subset , there exist and such that
[TABLE]
Moreover, there exist sequences and such that
[TABLE]
and
[TABLE]
The following two results show that tangent -free Young measures and -gradient Young measures differ only by a constant shift:
Corollary 7.1** (decomposition of blow-up sequences).**
Let be an -free measure and let be a tangent Young measure. Then, for every Lipschitz domain with , there exist a potential and a vector such that
[TABLE]
*Moreover, there exists a sequence satisfying *
[TABLE]
Furthermore, if is a singular point of or if there exists such that , then .
Proof.
The locality propertyĀ (19) of Young measures and the local decomposition of generating sequences given in LemmaĀ 7.1 imply that it is enough to show the assertion when
[TABLE]
We consider two cases: when is a regular or a singular point of .
Regular points: Every tangent Young measure is generated by a sequence of the form
[TABLE]
Recall fromĀ (17) that
[TABLE]
Hence, from the linearity of the push-forward and the compactness of Young measures, it follows that (here we use that ).
[TABLE]
The assertion follows by taking . If , then a localization argument andĀ (25) imply that
[TABLE]
In particular, there exist and such that
[TABLE]
This allows us to construct a smooth primitive of as follows: Let and define
[TABLE]
By construction satisfies we have
[TABLE]
which implies that . Therefore, by LemmaĀ 7.1, can be taken to be the zero constant.
Singular points: This proof is easier since instead ofĀ (44)-(45) we have
[TABLE]
Recall however fromĀ (24) that
[TABLE]
Therefore, using the same arguments as before (with different normalization constants) yields . This completes the proof. ā
Corollary 7.2**.**
If is an -free Young measure, then
[TABLE]
and
[TABLE]
If moreover, there exists such that , then
[TABLE]
8. Proof of the local characterizations
8.1. Proof of TheoremĀ 1.2
Necessity. This is straightforward from the definition of -free Young measure, a blow-up, and a diagonalization argument. For further details we refer the reader toĀ [arroyo-rabasa2017lower-semiconti, SectionĀ 2.8].
Sufficiency. Let be the countable family from LemmaĀ 4.1 which separates . Let as in the assumptions of TheoremĀ 1.2 and let us write to denote the barycenter of . Consider also the positive measure
[TABLE]
It follows from the main assumption, that there exists a full -measure set with the following property: at every there exists a tangent Young measure satisfyingĀ (22) and (without carrying the -dependence on several of the following elements)
[TABLE]
In what follows we shall simply write when no possible confusion arises. Particular consequences of the convergence above are the following: at every we can find a blow-up sequence
[TABLE]
and (composing with the identity map ) also
[TABLE]
Applying LemmaĀ 7.2 on the sequence and the sets and , which yields (cf. CorollaryĀ 7.2)
[TABLE]
where and are such that
[TABLE]
StepĀ 1. Construction of a disjoint cover of . Fix and let . At every we define as the supremum over all radii (where is the sequence from the previous step at a given ) such that
[TABLE]
Next, define the cover (of open cubes) with centers in given by
[TABLE]
Notice that, since exists for all , then is a fine cover of and hence we may apply Besicovitchās Covering Theorem, with the measure , to find a disjoint sub-cover , where each is of the form for some
[TABLE]
and
[TABLE]
StepĀ 2. An adjusted generating sequence of . Let be fixed and let be the -free tangent Young measure from the beginning of the proof. Now, we apply CorollaryĀ 7.1 to find a sequence satisfying
[TABLE]
Since it will be of use later, let be sufficiently large so that
[TABLE]
We also consider be two cut-off functions (with disjoint support) that satisfy the following properties:
[TABLE]
[TABLE]
StepĀ 3. Boundary adjustment for generating sequences of . The next step is to define an -free sequence generating on , which also has a blow-up of as boundary values. This should allow us to freely glue each of this approximations together while keeping the -free constraint
Fix and let . We begin by constructing a sequence on , which we shall later translate to . Bearing in mind all the -dependencies that we have omitted in the previous steps, define the -free sequence
[TABLE]
Here, let us recall that the commutator [\mathbb{B},\chi]\coloneqq\mathcal{B}(\chi\,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)-\chi\mathcal{B} is a differential operator of order at most (with coefficients involving the coefficients of and the derivatives of of order less or equal than ). By this token, if , we may estimate the total variation of as
[TABLE]
whence it is established that is uniformly bounded in . In fact, we get that ; this follows from the property . Therefore, passing to further subsequence of the ās if necessary (not relabeled), we may assume that
[TABLE]
On the other hand, observe that and hence, by LemmaĀ 4.1 and the locality of Young measures, it must hold in . Since this holds for all and neither or charge the boundary , it follows that
[TABLE]
In particular, the uniform bound above andĀ (50) ensure that we may find another subsequence satisfying
[TABLE]
StepĀ 4.Ā Gluing together and generating . So far, we have constructed generating sequences for specific tangent Young measures of on every where there is a cube . The rest of the proof can be summarized in the following two steps: First, we construct an -free sequences by gluing together the push-forwards of each . Second, we show the new global sequence is uniformly bounded.
StepĀ 5a. Gluing the generating sequences. For and we define the map , which is defined for all . Fix a cube in and define an -free measure there by setting
[TABLE]
Notice that
[TABLE]
where is the concentric sub-cube of given by . Therefore, the measure defined as
[TABLE]
is well-defined in . Moreover, it is also -free on (cf.Ā (63)) and its total variation in can be controlled as follows (recall that the push-forward is mass preserving)
[TABLE]
StepĀ 4b. The new -free sequence generates . This last step consists of checking that is indeed an -free Young measure in . In light of the previous steps, it suffices to check that generates in . First, we estimate how close is from generating on . Fix . Every cube has diameter at most and therefore there exists a modulus of continuity (depending solely on ) such that for all ; the same bound holds for any dilation of on the corresponding dilation of .
Let and let to be the linear growth constant of . We define
[TABLE]
Let . Regarding as an element of through the trivial extension by zero, we obtain the estimate
[TABLE]
Therefore, adding up these estimates for each cube on yields
[TABLE]
This shows that as , and, in particular, this holds for for any .
Conclusion. Since the family separates , we conclude that the (uniformly bounded) sequence of -free measures generates , i.e.,
[TABLE]
This finishes the proof.ā
8.2. Proof of CorollaryĀ 1.1
If is such that , then from TheoremĀ 1.2 we may assume that there exist tangent -free measures of at -a.e. in . The proof follows from the sufficiency part of the proof above, in particular from StepĀ 4. The recovery sequence constructed there is -free and it also generates . ā
8.3. Proof of TheoremĀ 1.4
The necessity follows from TheoremĀ 1.2 and the fact that, if is an annihilator of , then
- (a)
-quasiconvexity is equivalent to -gradient quasiconvexity for locally bounded integrands, 2. (b)
.
Sufficiency. Due to a small clash of notation, we re-write assumption (i) as
[TABLE]
We will show that there exists a sequence with that generates . This will be deduced from the constructions contained in the proof of the sufficiency of TheoremĀ 1.2, but first we need to recall the following fact of blow-downs: if and , then the blow-down of , centered at and at scale , is given by
[TABLE]
Notice that and . Moreover, the mass preserving property of push-forwards gives
[TABLE]
We are now ready to prove the assertion. Let us recall from (b) that satisfies the sufficiency assumptions of TheoremĀ 1.2 and hence we may apply the elements contained in its proof to . In particular, the sequence (introduced inĀ (52)) has elements of the form . However, since by assumption , CorollaryĀ 7.2 says that we may assume inĀ (52). In particular, keeping the notation of the previous proof, the sequence (defined in StepĀ 3) is a sequence of -gradients. Indeed, since it follows that and by the (inverse) property of blow-downs we get
[TABLE]
It follows that the sequence (defined in in p. 44), which generates our Young measure , has the form
[TABLE]
where, according toĀ (65) and ignoring the -dependence, the are defined as
[TABLE]
In particular, the identity for blow-downs above implies that , where is the Radon measure given by
[TABLE]
By construction we have (as measures) on a neighborhood of . This compatibility across the partition ensures that
[TABLE]
defines a sequence of Radon measures in , with and such that
[TABLE]
This finishes the proof.ā
9. Proof of the dual characterizations
9.1. The convexity of
Let be an -free measure. We define the set
[TABLE]
The proof of the following proposition is contained in LemmaĀ 5.3 ofĀ [baia2013]. There the authors state their main results under additional assumptions. However, the proof of this specific proposition makes not use of such assumptions and can be worked out by verbatim in our context.
Proposition 9.1**.**
The set is weak- closed in .
The main in step towards the proof of the characterization result TheoremĀ 1.1 rests in showing the following convexity property. Once this is established the proof of TheoremĀ 1.1 follows by relaxation argument and the geometric version of HahnāBanachās Theorem argument.
Theorem 9.1**.**
The set is a convex set.
Proof.
Fix and let
[TABLE]
We also write . Our goal is to show that is an -free Young measure on . To show this we will construct a sequence of -free measures om which generate the functional .
Since this will be a fairly long and technical proof we will begin by describing a brief program of the proof. The foundation of our proof lies in a careful inspection of the infinitesimal qualitative behavior of points with respect to our Young measures . The qualitative understanding of the set of tangent Young measures of () at a given will be decisive in the choice of construction of an -free recovery sequence for about that point. Once every point and their local constructions are established, the idea is to use Besicovitchās covering theorem to build a partition of into disjoint tiles, each of which retrieves the infinitesimal properties of and hence the recovery sequences of about their center points. The one but last step is to glue the aforementioned -free recovery sequences from each tile into a globally -free sequence which generates an arbitrarily close a piece-wise constant approximation of . The conclusion of the argument then follows from a diagonalization argument between the larger scale of piece-wise constant approximations of where we glue the recovery sequences, and the smaller scale where the corresponding recovery sequences are effectively constructed.
StepĀ 1. Qualitative analysis of points.
Since we are trying to capture the fine properties of and simultaneously, it will be convenient to define the measure , which is a suitable substitute candidate to keep track of the interactions between singular points of and . We start by distinguishing regular points and singular points. It follows from the RadonāNykodým theorem that at -almost every one of the following properties hold: either
[TABLE]
is a regular point, or
[TABLE]
is a singular point. Throughout this proof we shall call points with the first property (which holds -almost everywhere) regular points, and points satisfying the second property (which holds -almost everywhere) will be called singular points; we shall only consider points that are either regular or singular points. In addition, we may assume without any loss of generality that the limits
[TABLE]
exist at every singular point . Next, we further partition into sets which render precise information about the size relation between and . More precisely, we split into sets , where
[TABLE]
and . If we set
[TABLE]
then, up to modifying , we may assume that are -measurably continuous and
[TABLE]
StepĀ 1a. Tangential properties of singular points. So far we have separated regular and singular points, and the latter by their weights with respect to and . The next step is to separate points in with respect to the qualitative behavior of .
- (1)
If there exists a tangent measure which does not charge points, i.e.,
[TABLE]
then we write . Every has the following property (see CorollaryĀ B.2): if , is a -measurable map, and is a -Lebesgue point of , then there exist (a) a sequence of infinitesimal radii and (b) a sequence of open Lipschitz sets satisfying
[TABLE]
and
[TABLE]
In particular, if , then
[TABLE] 2. (2)
If otherwiseĀ (1) does not hold for any tangent measure of at , we write . It follows from LemmaĀ B.3 and the fact that blow-ups of blow-ups are blow-ups (see TheoremĀ 2.12 in [preiss1987geometry-of-mea]) that
[TABLE]
StepĀ 1b. Selection of points with Lebesgue-type properties. We now turn to the selection of points which later shall be the centers of the tile partitions. As usual let be the family from LemmaĀ 4.1 which separates points in .
Up to removing a set of -measure zero, we may assume that every is a Lebesgue point of the maps
[TABLE]
About singular points , we shall be more careful and set to be the set of -Lebesgue points of the family of maps
[TABLE]
Each has full -full measure on and hence has full -measure on . Therefore, in what follows there will be no loss of generality in assuming that ; this union may not be disjoint.
StepĀ 2. Building a partition of cubes with good fine properties. Let , in this step we will address the construction of a full -measure partition of with -asymptotic approximation Lebesgue-type properties. To begin, let us define a fine cover of . At every we define
[TABLE]
A radius is said to satisfy provided the following continuity properties hold for and all indexes :
If , then
[TABLE]
If , then
[TABLE]
If , then we require
[TABLE]
If or , then we can only find satisfyingĀ (76) for and respectively.
Lastly, if , then
[TABLE]
where
[TABLE]
Moreover, can be chosen sufficiently small so that
[TABLE]
where is the decomposition provided by LemmaĀ 7.1 for on . Here we have used the short notation
[TABLE]
for the translations of a function .
Now, this is indeed a large amount of smallness conditions to keep track, but they are all fundamental if one wishes to avoid (trivial) partitions which do not reflect the behavior of appropriately.
ClaimĀ 1. for all .
Proof of ClaimĀ 1. Most of the properties are easy to check: PropertiesĀ (69)-(71) and Ā (72)-(75) follow directly from the construction and the Lebesgue properties discussed in StepĀ 1b. PropertyĀ (76) is a consequence of StepĀ 1a(1). We focus in showingĀ (77)-(78) which will follow from the fact that . Indeed, in this case we may a sequence of infinitesimal radii such that
[TABLE]
Then, by the strict convergence of the blow-up sequence we deduce that
[TABLE]
In particular, since , we conclude that
[TABLE]
Choosing in a way that satisfies the required properties for and (this can be done by slightly modifying each in the blow-up sequence), we exhibit an infinitesimal sequence (and their associated ) satisfyingĀ (77)-(78).
This proves the claim.ā
In particular, the cover
[TABLE]
conforms a fine cover of to which we may apply Besicovitchās Covering Theorem: There exists a sub-cover of disjoint cubes satisfying
[TABLE]
Here, we have set .
StepĀ 3. Piece-wise homogeneous approximations of . The idea behind defining is to construct a piece-wise homogeneous approximation of of order as follows: Fix and define, through duality, a sequence of functionals in acting as
[TABLE]
The fact that these functionals are in fact Young measures follows directly fromĀ (79), the weak- measurability properties of and , and the fact that simple Borel maps are measurable with respect to any Radon measure.
ClaimĀ 2. As it holds that
[TABLE]
Proof of ClaimĀ 2. Let (we shall simply write ). First, we show that
[TABLE]
We consider . We may estimate (cf.Ā (79)) the difference of the integrals above by the sum of the two non-negative quantities
[TABLE]
and
[TABLE]
UsingĀ (72) and the linear growth of |f|\leq M_{f}(1+|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|) we obtain
[TABLE]
It follows that .
On the other hand, we useĀ (70)-(71) to bound as
[TABLE]
This shows that , whenceĀ (80) follows.
To prove the claim we are left to show that
[TABLE]
We may estimate the integrand above, for fixed , by
[TABLE]
Since separates , this proves ClaimĀ 2.ā
StepĀ 4. Construction of a global -free recovery sequence. Let us fix . Next, we define candidate recovery sequences for on . This will be done depending on whether belongs to or where these sets are the ones defined in StepĀ 1a.
StepĀ 4a. Cubes centered at . We recall from stepĀ 1a andĀ (76) that, if , then there are open Lipschitz sets satisfying
[TABLE]
[TABLE]
[TABLE]
and
[TABLE]
On the other hand, since are -free Young measures on , we may apply LemmaĀ 7.1 to find sequences (to avoid adding unnecessary notation, we will omit the -dependence of these sequences) of -free measures and satisfying
[TABLE]
The same construction applies with for with the exception that we require to satisfy
[TABLE]
It follows from the uniformity of the Lebesgue measure that this can always be achieved for some open Lipschitz ; in this case the set can be chosen to be a strip of width or an open concentric cube of of side .
In what follows we shall write
[TABLE]
Notice that by construction the measures
[TABLE]
are -free on for all . Moreover, the ās can be extended by outside and particular this extension preserves the -free constraint. Moreover, in virtue ofĀ (85)-(86) and the locality of the weak- convergence of Young measures it holds that
[TABLE]
Therefore, upon re-adjusting the sequence we may assume that
[TABLE]
StepĀ 4b. Cubes centered at .
The constructions in these cubes will be completely different and it will consist of separating the generating sequences of locally. Once again, by LemmaĀ 7.1, we may find sequences of potentials such that
[TABLE]
where for some . Moreover,
[TABLE]
and
[TABLE]
Now, let be a cut-off function satisfying (here )
[TABLE]
Due to the -continuity of the translations, we may choose to be sufficiently large so that
[TABLE]
for all .
We are now in position to define our recovery sequence candidate for on by setting
[TABLE]
The purpose of this sequence is to shift and apart from each other, while preserving the -boundary conditions near (see FigureĀ 2 below). Clearly, is a sequence of -free measures on with on a neighborhood of and on . Notice that this construction differs from the previous one (when ) in the sense that the -weights are incorporated by simple multiplication. In general, this construction is too naive to work. However, in this case, it works because we have in .
Let us fix . Writing and adding a zero, we may express as
[TABLE]
where as usual the commutator [\mathbb{B},\chi]=\mathcal{B}(\varphi\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)-\varphi\mathcal{B} is a linear operator of order at most and whose coefficients depend solely on and the principal symbol . We obtain the following estimate for the total variation of :
[TABLE]
In particular, upon re-adjusting the sequence we may assume that
[TABLE]
and .
Observe that if with , then
[TABLE]
Hence, there exists such that (with )
[TABLE]
for all . An analogous estimate holds for , , and . Let us set R_{x}\coloneqq Q_{x}\setminus\big{(}(Q_{s_{x}}(x)-s_{x}e_{1})\cup(Q_{s_{x}}(x)+s_{x}e_{1})\big{)}. Then, by the definition of , a similar argument combined with the right translations yield (for )
[TABLE]
Combining these estimates we obtain upon re-adjusting the sequence of ās (recall that we had written )
[TABLE]
whenever .
StepĀ 4c. Gluing the local recovery sequences.
Every cube is centered at some and since
[TABLE]
the constructions in StepsĀ 4a andĀ 4b indeed cover all possible scenarios which can present. The next task is to glue the recovery sequences together to obtain an -free global recovery sequence of the -approximation of . For each , let us define the sequence
[TABLE]
Notice that by construction each is -free since each and is -free on and has -boundary values in an open neighborhood of .
StepĀ 4d. Generation of the -approximations of . Appealing to the locality of weak- convergence of Young measures, we show next that if , then (as )
[TABLE]
where is the Young measure which acts on by the representation formula
[TABLE]
Later, in the next step, we will show these Young measures are indeed -approximations of . This, together with a diagonalization argument withĀ (93) will imply that .
First, we show that the sequence has uniformly bounded total variation on . There is no loss of generality in assuming that f_{1,1}=\mathbbm{1}_{\Omega}\otimes|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|, and therefore
[TABLE]
This shows
[TABLE]
as desired.
Since is uniformly bounded on , the desired limit approximation inĀ (93) follows from 1) the locality of weak- convergence of Young measures, 2) the generation propertiesĀ (85)-(86) for points in , 3) the generation property at singular points in the Ā (92), and 4) the fact that is a full -partition of .
StepĀ 5. The sequence approximates . Next we show that
[TABLE]
Accordingly, fix and choose . Let us, for the sake of simplicity, write and . Due to the high amount of terms and estimates involving this argument, let us write
[TABLE]
where each term contains partial sums subjected to a decomposition of the mesh in the following way:
- (a)
the cubes around regular points . For , the corresponding partial sum is given by
[TABLE] 2. (b)
and now we cover the singular set , starting with the cubes around singular points
[TABLE]
In the first equality we have strongly used the -Lebesgue property for the sets which is justified in StepĀ 1a(1); the precise statement is contained in CorollaryĀ B.2. The same argument will be used in the estimates (c) and (d) below; 3. (c)
passing to points (in this case ). For the partial sum reads
[TABLE] 4. (d)
and to finally cover , the singular points : an analogous estimate to the one derived in (b) gives
[TABLE] 5. (e)
Lastly, the cubes with centers which by definition are simply given by
[TABLE]
Since the singular set can be split into the disjoint union
[TABLE]
and since every possible cube is centered at one (and only one) of the previous four sets, we deduce from inspecting the terms that
[TABLE]
Conclusion. Let us recall that
[TABLE]
where is the constant fromĀ (94). Returning to the estimateĀ (93), we may then, by a diagonalization argument, define a sequence of -free measures
[TABLE]
satisfying (cf. ClaimĀ 2 and StepĀ 5)
[TABLE]
Moreover, it follows from the compactness of Young measures and the separation LemmaĀ 4.1 that the convergence above implies (this may involve passing to a subsequence)
[TABLE]
This finishes the proof. ā
9.2. Characterization of singular Young measures
In this section we establish a criterion for a family to belong to . This family mimics the properties of singular tangent Young measures, and therefore this criterion will serve as a preparation for the proof of TheoremĀ 1.1.
Remark 9.1**.**
It is worthwhile to mention that our construction departs from the approach presented inĀ [kristensen2010characterizatio, de-philippis2016on-the-structur]. There, the authors are able to work with a family of Young measures that are one-directional. This, however, relies on the rigidity that gradients and symmetric gradients possess. In turn, this simplifies enormously the proof of the convexity of -free young measures at the level of tangent Young measures; it also allows for the creation of artificial concentrations (cf.Ā [de-philippis2017characterizatio, Lemma 3.5]), which is crucial for the separation argument. It is precisely for this reason that the convexity of had to be conceived globally rather than at the level of tangent -free Young measures.
Let us turn to the heart of the matter. Let and let
[TABLE]
We shall prove the following:
Proposition 9.2**.**
Let for some . Assume that
[TABLE]
and further assume that
[TABLE]
then .
Proof.
Let us write . The idea is to find a suitable convex subset that contains . The choice of is of course not unique, and is part of the problem in turn. We shall work with the following set:
Definition 9.1**.**
Let be the set of -free Young measures satisfying the following properties:
- (a)
, 2. (b)
for -almost every , 3. (c)
for -almost every .
Notice that is non-empty since it contains .
Remark 9.2**.**
Since properties (a)-(c) are convex properties, PropositionĀ 9.1 and TheoremĀ 9.1 imply that is a non-empty weak- closed convex subset of .
StepĀ 1. The separation property. Let us recall that, for every weak- closed affine half-space , there exists an integrand such that
[TABLE]
From the geometric version of HahnāBanachās it follows that, either , or there exists such that
[TABLE]
Since the former case is precisely what we want to prove, let us henceforth assume that the strictly separates and . By assuming this, we shall reach a contradiction.
StepĀ 2. Separation with . Let be the integrand defined as , where is the canonical linear projection onto . Notice that properties (b)-(c) and the properties of we get
[TABLE]
StepĀ 2. Boundedness of . The following version ofĀ [baia2013, LemmaĀ 5.5] states that the separation property with conveys the finiteness of the -quasiconvex envelope of :
Lemma 9.1**.**
Let be such that for all . Then, there exists a dense set such that, for every , it holds .
The proof follows by verbatim from the proof ofĀ [baia2013, Lemma 5.5]. The only difference is that, there, it is assumed that . However, this is of little importance in our setting due to properties (b) and (c), the properties of (cf. SectionĀ 4.3) and propertyĀ (25).
StepĀ 3. The contradiction: . For an integrand and , we define f^{\varepsilon}\coloneqq f+\varepsilon|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|. By construction, property (A) from RemarkĀ A.1 is trivially satisfied for the integrand and the domain . The finiteness of of and PropositionsĀ 4.5, 4.6 andĀ 4.8 imply that also satisfies property (B) from RemarkĀ A.1. Lastly, we recall that , which implies that (C) in RemarkĀ A.1 is also satisfied. With these considerations in mind, we may apply TheoremĀ A.1 to find a recovery sequence satisfying
[TABLE]
and attaining the so-called upper-bound property
[TABLE]
Passing to a further subsequence if necessary, we may assume that
[TABLE]
Claim. .
By construction, , and hence property (a) is satisfied. The theory developed in SectionĀ 7 implies that, on strictly contained sub-cubes , we may assume it holds
[TABLE]
where the elements of the sequence are mean-value zero -free measures in and . PropertyĀ (25) and a standard mollification argument gives . In particular, the expression for and the assumption gives , whence
[TABLE]
Since was arbitrarily chosen, this proves that and therefore properties (b)-(c) hold. This proves that and the claim is proved.
For the ease of notation, let us write for the next calculation. We use the main assumptions and , together with PropositionĀ 4.5 (recall that \mathcal{Q}_{\mathcal{A}}f(x,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,) is -convex) and RemarkĀ 1.2 to find that
[TABLE]
Here, in the one but last inequality we have dealt with the absolutely continuous part with the aid of the following property: if is a spanning cone of directions, then every -convex function with linear growth at infinity satisfies (see for instance LemmaĀ 2.5 inĀ [kirchheim2016on-rank-one-con])
[TABLE]
Hence, by combiningĀ (97)-(98) we conclude that
[TABLE]
Letting , we conclude fromĀ (96) that , which contradictsĀ (95). This proves that must indeed belong to . This completes the proof of the proposition.ā
9.3. Characterization of regular Young measures
Now, we prove the analog of PropositionĀ 9.2 for regular tangent Young measures. The proof follows the ideas of the original proof inĀ [fonseca1999mathcal-a-quasi], but it requires some minor changes to deal with the fact that and may not coincide.
Let and consider the family of homogeneous Young measures defined as
[TABLE]
Here, the sub-index ā[math]ā in and denotes that and for all . This family mimics the properties of regular tangent measures (cf. PropositionĀ 4.3). As one would expect, for regular points it is property (ii) from TheoremĀ 1.1 that plays a fundamental role in the characterization of regular blow-ups:
Proposition 9.3**.**
Let and assume that
[TABLE]
for all upper-semicontinuous -quasiconvex integrands with linear growth at infinity. Then
[TABLE]
Proof.
The proof is considerably simpler than the one at singular points since, for the separation argument, it will suffice to consider the following family of homogeneous Young measures:
[TABLE]
The first step is to verify that is non-empty. Indeed, and therefore the elementary (purely oscillatory) homogeneous Young measure (\delta_{P_{0}},0,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,) belongs to .
Remark 9.3**.**
The properties that define are convex properties. Therefore, PropositionĀ 9.1 and TheoremĀ 9.1 imply that is a non-empty weak- closed convex subset of .
Step 1. The separation property. By the geometric version of Hahn-Banachās theorem it holds that, either , or there exists an affine weak- closed half-plane that strictly separates from , i.e., there exists such that
[TABLE]
We shall henceforth assume that strictly separates and .
Step 2. Separation with elements of . Consider the class
[TABLE]
For an integrand , let us consider the homogenized integrand defined as
[TABLE]
It is not hard to see that that (\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)^{\infty} commutes with (\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,)_{\hom} for such integrands. Indeed, for every ,
[TABLE]
In particular,
[TABLE]
Fubiniās theorem gives
[TABLE]
This tells us there is no loss of generality in assuming that .
StepĀ 3. Reduction to the case and separation with . At regular points, we may no longer use the property . This prevents us to argue in the same way as for singular points, that it indeed suffices to work with . There is turnaround to this issue by using the shifts introduced in DefinitionĀ 4.2:
Remark 9.4**.**
By CorollaryĀ 7.2, the shifted Young measure is an homogeneous -free Young measure with barycenter zero if and only if is an homogeneous -free Young measure with barycenter .
This remark implies that
[TABLE]
A Young measure in the latter set satisfies the crucial property that (and ) are contained in for -a.e. (-a.e.) ; this follows from the same argument used to prove the claim that in the singular pointsā case (here one uses that ). On the other hand, CorollaryĀ 4.1 implies that and also that, either , or . In particular, we get
[TABLE]
Therefore, there is no loss of generality in assuming that and .
StepĀ 3. The contradiction: . The argument is essentially the same as the one for singular points, which relies on the upper bound from the relaxation argument. The relaxation argument, however, is nowhere near as involved as the one contained in TheoremĀ A.1. First, we show that is finite with lower bound . Let . By a well-known homogenization argument (see for instanceĀ [fonseca1999mathcal-a-quasi, PropositionĀ 2.8]) the sequence generates the homogeneous purely oscillatory Young measure \bm{\theta}=(\overline{\delta_{w}},0,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,), where
[TABLE]
In particular , and hence
[TABLE]
Taking the infimum over all , we conclude that , as desired. Now, we are in position to useĀ (99) with to get (recall that is globally Lipschitz, see PropositionsĀ 4.5 andĀ 4.6):
[TABLE]
This poses a contradiction to inequalityĀ (100). This proves that , as desired. ā
9.4. Proof of TheoremĀ 1.1
Necessity. Property (i) is obvious since, by definition, an -free measure is generated by a uniformly bounded sequence of (asymptotically) -free measures, therefore its barycenter is an -free measure. Properties (ii)-(iii) have been established inĀ [arroyo-rabasa2017lower-semiconti]: condition (ii) is contained in PropositionĀ 3.1, and condition (iii) in LemmaĀ 3.2; condition (iiiā) is contained in PropositionĀ 3.3.
Sufficiency. The theory discussed in SectionĀ 4.2.1 implies that at -almost every there exists a regular or a singular tangent measure . The idea is to show that each of these tangent measures are in fact locally -free Young measures and argue by the local characterization from TheoremĀ 1.2. By the dilation properties of tangent Young measures, it suffices to show the following:
Proposition 9.4**.**
Let satisfy properties (i)-(iii) in TheoremĀ 1.1. Then,
[TABLE]
for -almost every .
Proof of the proposition.
As in the statement of TheoremĀ 1.1, let us write . According to PropositionĀ 4.4 andĀ [de-philippis2016on-the-structur, Theorem 1.1] we may find a full -measure set such that, if , then there exists satisfying the assumptions of PropositionĀ 9.2 (here we are using that satisfies (i)-(iii)). On the other hand, PropositionĀ 4.3 yields a full -measure set with the property that, if , then there exists satisfying the assumptions of PropositionĀ 9.3 (here we are using that satisfies (i)-(ii)). The sought assertion then follows from the conclusions of PropositionsĀ 9.2 andĀ 9.3. This proves the proposition. ā
Returning to the proof of TheoremĀ 1.1 we observe that since and by assumption (iii) also in the sense of distributions on , then TheoremĀ 1.2 implies that . This proves the sufficiency.
The proof is complete.ā
9.5. Proof of TheoremĀ 1.5
The necessity is a direct consequence of TheoremĀ 1.1 and (a)-(b) in SectionĀ 8.3. To prove the sufficiency of (i)-(iii) in TheoremĀ 1.5, notice that the same (a)-(b) and the sufficiency of TheoremĀ 1.1 imply that . Now, we make use of TheoremĀ 1.5(i) and the last statement of CorollaryĀ 7.2, to deduce that every tangent measure of is a tangent -gradient Young measure. Therefore, the local characterization TheoremĀ 1.4 implies that , as desired. ā
Appendix A An auxiliary relaxation result
Theorem A.1**.**
Let be a continuous integrand that is Lipschitz in its second argument, uniformly over the -variable. Assume also that has linear growth at infinity and is such that there exists a modulus of continuity satisfying
[TABLE]
Further suppose that the strong recession function exists. Then, for the functional
[TABLE]
the weak- (sequential) lower semicontinuous envelope defined by
[TABLE]
where is an -free measure with and , is given by
[TABLE]
Remark A.1** (on the assumptions of TheoremĀ A.1).**
The assumptions on TheoremĀ A.1 can be relaxed to the following set of assumptions:
- (a)
, 2. (b)
\mathcal{Q}_{\mathcal{A}}f(x,\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,) is globally Lipschitz, uniformly in , and satisfies
[TABLE] 3. (c)
the relaxation is restricted to weak- limit measures satisfying .
Let us briefly comment on how this is done. The proof ofĀ A.1 contained inĀ [arroyo-rabasa2017lower-semiconti] mainly consists in proving the upper-bound inequality
[TABLE]
First, one proves the relaxation for for some , and for the translation f_{\varepsilon}=f+\varepsilon|\,\begin{picture}(1.0,1.0)(-0.5,-2.0)\circle*{2.0}\end{picture}\,|, where is a small real number. One approximates by constants on small cubes centered at . The original argument crucially uses the -Lipschitz continuity of to approximate
[TABLE]
However, the argument also works for using that is uniformly continuous on compact subsets of . 2. 2.
At each cube , a standard homogenization argument is performed with the cell-problem approximation of the definition of -quasiconvexity:
[TABLE]
where are mean-value zero functions on . InĀ [arroyo-rabasa2017lower-semiconti], the fact that is crucial to show that is -uniformly bounded, therefore also weak- pre-compact However, (b) is enough to show this (cf. PropositionĀ 4.7). 3. 3.
Then, one glues the sequences into a global sequence satisfying
[TABLE]
so that
[TABLE] 4. 4.
The last step consists of showing that one can glue back together the piece-wise constant relaxed energies:
[TABLE]
The cited proof relies on the modulus of continuity (b) āwhich is proven for when ā and the fact that, since is Lipschitz, so it is (and their -translations as well). With our assumptions, the argument follows by using property (b) instead. 5. 5.
The previous steps proves that
[TABLE]
The upper bound inequality then follows by letting . 6. 6.
The upper bound inequality for general follows from TheoremĀ 1.3, RemarkĀ 1.3 and Reshetnyakās continuity theorem (cf.Ā (10)). 7. 7.
The lower bound inequality is addressed inĀ [arroyo-rabasa2017lower-semiconti, TheoremĀ 1.2(i)] under the assumption that . There, the positivity of is only used to prevent concentration of negative mass on the boundary. Assumption (c) allows us to dispense with this assumption.
Appendix B Technical lemmas for Radon measures
This section is devoted to address some technical results which are essential to the proof of TheoremĀ 9.1.
Lemma B.1**.**
Let be a probability measure on the unit open cube and assume that does not charge points in , that is, for all . Let , then there exists a convex Borel set satisfying
[TABLE]
and
[TABLE]
Proof.
In the case when we define the monotone non-decreasing map
[TABLE]
which in particular is a function of bounded variation. Notice that, in this case, the one dimensional -theory and the assumption on give
[TABLE]
This proves is in fact continuous in the interval . Therefore, since (again by assumption) and , then the Mean Value Theorem ensures there exists with .
The case requires a co-area-type argument. The first step is to define the map
[TABLE]
is monotone non-decreasing and satisfies and . In particular,
[TABLE]
Set . Clearly, if is lower semicontinuous at , then we can set which automatically satisfies the conclusions of the Lemma (in this case is not necessary to use the assumption that does not charge points). However, in general one cannot expect this as for instance there might be mass sitting on . We may then assume that and
[TABLE]
This will be our first approximation. The second step to carry the same approximation now on , the open -dimensional faces of , which are axis-directional translated -dimensional cubes (centered at the origin) in ; the number of faces will not be relevant for our construction. Define the maps
[TABLE]
Repeating the same procedure as in the first step on each of the faces simultaneously, we update the error of our estimate to
[TABLE]
where . Notice that
[TABLE]
where
[TABLE]
Moreover, by construction (since each one of the added faces are concentric to each face of ), is a (semi-open/semi-closed) convex set satisfying . There are two cases, either and then , or and we must keep adding bits of , which may require to perform a similar argument on the -dimensional concentric faces of and the -dimensional faces of each , . In general, the th step is to iterate this argument (when ) on all the possible -dimensional faces of and all the other -dimensional faces resulting of adding the previous -dimensional concentric cubical caps. The key part of the construction is that, at the end of the th step, one obtains a convex set satisfying and
[TABLE]
We now argue why there exists such that . If , then by the same argument that in the one-dimensional case we get that the maps are continuous, and hence it must be that reaches . If , then the maps of the third step are continuous and hence at most reaches . In general, the description of this procedure is tedious, but it is inductively natural and always reaches and endpoint (at most after -steps) where we find a convex set containing the origin and satisfying and
[TABLE]
This finishes the proof. ā
Corollary B.1**.**
Let be a probability measure on the unit open cube and assume that does not charge points in . Let and let . Then, there exists an open Lipschitz set satisfying
[TABLE]
Proof.
From the previous lemma we may find a set satisfying . Now, from the inner and outer regularity of Radon measures we may find a compact set and an open set such that satisfying
[TABLE]
Moreover, since , there exists a Lipschitz open set with . On the other hand, since is a Lipschitz compact set, the family of sets
[TABLE]
is a a family of open Lipschitz sets satisfying for some , where . Furthermore, if , then . In particular, since is a Radon measure, there exists a full -measure subset of such that
[TABLE]
Let us choose and recall from our construction that . Hence,
[TABLE]
This finishes the proof. ā
Lemma B.2** (shrinking sequence).**
Let be a positive Radon measure on and assume there exists a tangent measure which does not charge points on . Then, for every , there exists an infinitesimal sequence and a sequence of open Lipschitz sets satisfying
[TABLE]
and
[TABLE]
Proof.
Since belongs to for all , we may assume without any loss of generality that is a good blow-up as inĀ (14). That is, there exists an infinitesimal sequence such that
[TABLE]
By assumption and CorollaryĀ B.1 we may find a sequence of Lipschitz open sets satisfying for all . Moreover,
[TABLE]
Hence, for fixed , we deduce from the strict-convergence of the blow-up sequence that
[TABLE]
Moreover, up to a small re-scaling at each we may assume without loss of generality that . A standard diagonalization argument yields a subsequence such that
[TABLE]
By construction, the sequence of sets has the desired properties. ā
Corollary B.2**.**
Let be a positive Radon measure on and assume there exists a tangent measure which does not charge points. Let be a -measurable map and assume furthermore that is a -Lebesgue point of . Then, for every , there exist a sequence and a sequence of Lipschitz open sets satisfying
[TABLE]
and
[TABLE]
Proof.
The existence of the sequence of open Lipschitz sets satisfying the first two properties follows directly from the previous corollary. The third property follows from the estimate
[TABLE]
and the fact that is a -Lebesgue point of . ā
Lemma B.3**.**
Let be a positive Radon measure on and assume there exists such that . Then .
Proof.
Let and set . Since is a -cone, it is enough to show that when is a probability measure on . Moreover, we may also assume the blow-up sequence converging to has the form
[TABLE]
It follows from the strict-convergence on that
[TABLE]
Since is a probability measure on , this shows that as desired. ā
Acknowledgments
I would like to thank Bogdan Raita for fruitful conversations regarding the contents of SectionĀ 5. Special thanks go to Anna Skorobogatova, who kindly helped me to proofread the paper. Also I want to thank the reviewers for suggesting me to address relevant questions that were not contained in the original version of this paper. This project has received funding from the European Research Council (ERC) under the European Unionās Horizon 2020 research and innovation programme, grant agreement No 757254 (SINGULARITY).
References
