This paper establishes a rigorous homogenisation process for elliptic phase-field functionals with linear growth, revealing how fine-scale oscillations influence the limit energy in image segmentation models.
Contribution
It introduces a novel homogenisation approach for linear growth phase-field functionals, extending classical results to include random integrands and jump-dependent surface energies.
Findings
01
Homogenisation results for linear growth functionals with explicit dependence on jump amplitude.
02
Extension of homogenisation theory to stationary random integrands.
03
Identification of the limit energy as a free-discontinuity energy with jump-dependent surface term.
Abstract
We propose a first rigorous homogenisation procedure in image-segmentation models by analysing the relative impact of (possibly random) fine-scale oscillations and phase-field regularisations for a family of elliptic functionals of Ambrosio and Tortorelli type, when the regularised volume term grows \emph{linearly} in the gradient variable. In contrast to the more classical case of superlinear growth, we show that our functionals homogenise to a free-discontinuity energy whose surface term explicitly depends on the jump amplitude of the limit variable. The convergence result as above is obtained under very mild assumptions which allow us to treat, among other, the case of \emph{stationary random integrands}.
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Full text
Homogenisation of phase-field functionals
with linear growth
Francesco Colasanto
DiMaI U. Dini, Università di Firenze, V.le G.B. Morgagni 67/A, 50134 Firenze, Italy
We propose a first rigorous homogenisation procedure in image-segmentation models by analysing
the relative impact of (possibly random) fine-scale oscillations and phase-field regularisations for a family of elliptic functionals
of Ambrosio and Tortorelli type, when the regularised volume term grows linearly in the gradient variable.
In contrast to the more classical case of superlinear growth, we show that our functionals homogenise to a free-discontinuity energy whose surface term explicitly depends
on the jump amplitude of the limit variable. The convergence result as above is obtained under very mild assumptions which allow us to treat, among other, the case of stationary random integrands.
1. Introduction
In this paper we study the combined effect of homogenisation and elliptic regularisation for phase-field functionals of the form
[TABLE]
where ε>0 describes both the oscillation and the regularisation scale, and f grows linearly in the gradient variable. In (1.1) A⊂Rn is open, bounded, with Lipschitz boundary, u is a vector-valued function which belongs to W1,1(A,RN), while v is a phase-field variable lying in W1,2(A).
As mentioned above, we require that the integrand f:Rn×RN×n→[0,+∞) obeys linear growth and coercivity conditions in the second variable; that is
[TABLE]
for every (x,ξ)∈Rn×RN×n and for some C∈(0,+∞). Besides (1.2), we work under very mild assumptions on f which do not include any spatial periodicity (cf. Definition 2.4). Working in such a general setting allows us to prove a homogenisation result which also covers the case of random stationary integrands, as we are going to explain below.
The elliptic functionals in (1.1) are reminiscent of the celebrated phase-field model given by
[TABLE]
which was proposed by Ambrosio and Tortorelli in the seminal works [10, 11] to approximate the (relaxed) Mumford-Shah functional [38]. The latter was introduced in the 2d framework of image segmentation to recover shapes in noisy images via curve evolution. In this setting the Ambrosio-Tortorelli functional is employed for implementation by gradient descent, where curves are replaced by a continuous edge-strength function (1−v in our notation) which gives the probability of an object boundary to be present at any point in the image domain. Then, the actual shape boundaries are determined in the form of geodesics defined in a metric determined by v itself (cf. [43, 46]).
After the revisitation of Griffith’s brittle-fracture theory due to Francfort and Marigo [34] (see also [19, 18]),
a number of variants of the Ambrosio-Tortorelli model have been proposed and extensively used also to approximate brittle fracture models [12, 13, 16, 21, 25, 33], just to mention few examples.
The advantage of this kind of approximations is twofold: on the one hand they establish a rigorous connection between variational fracture models and gradient-damage models [40, 39], on the other hand, in most of the cases, they provide efficient algorithms for numerical simulations [18, 19, 34].
If instead in (1.1) we choose f(x,ξ)=∣ξ∣, the corresponding phase-field functionals
were originally proposed by Shah [44, 45] as possible regularisations of
an image-segmentation model, alternative to the Mumford-Shah’s functional, which provides a common framework for image segmentation and isotropic curve evolution in Computer Vision. Moreover, Shah’s functional overcomes a number of limitations of the earlier models. Loosely speaking, in this framework the domain A is interpreted as a Riemannian manifold endowed with a metric defined by the image properties so that the image-segmentation problem amounts to finding a minimal cut in a Riemannian manifold (cf. [47]).
The main difference between the Ambrosio-Tortorelli functionals (and their more “classical” variants)
and (1.1)-(1.2) rests on the growth of the function f: superlinear in the former versus linear in the latter.
Such different behaviours lead to some structural differences in the corresponding, attainable limit models. In fact, the weaker gradient penalisation in (1.2) allows for an
interaction between the two competing terms in (1.1), as it also typical of free-discontinuity functionals in the linear setting [17, 24].
As a result, the surface energy densities obtained in this case are of cohesive type as proven in [7], in the scalar isotropic case, and in [8], in the vector-valued anisotropic case. That is, the resulting limit surface integrands in the linear setting are bounded, increasing, and concave functions of the jump amplitude [u] of the (possibly discontinuous) limit variable u, moreover they exhibit a linear growth at the origin. We observe though, that the linear growth of f
for large gradients is not justified in the applications to Fracture Mechanics, so that more recently other variants of the Ambrosio-Tortorelli functional related to the gradient-damage models in [40, 39] were designed to provide a variational approximation of cohesive energies (cf. [27, 49, 48, 32, 28, 29, 35, 4, 26]).
It is also worth mentioning that in these models the parameters can be tuned to approximate prescribed cohesive laws (satisfying suitable assumptions) as shown in [5] (see also [6] for applications to an engineering problem).
Furthermore, we observe that the coercivity assumption in (1.2) yields the “weaker” lower bound
[TABLE]
where the functionals on the left-hand side are those proposed by Shah and studied in [7]. Hence, from (1.3) and the analysis in [7] (see also [8]) we readily deduce that if (uε)⊂W1,1(A,RN) is a sequence with equi-bounded energy which additionally satisfy
supε∥uε∥Lq<+∞, for some q>1, then (up to subsequences) uε→u with respect to the strong L1(A,RN)-convergence, for some u∈(G)BV(A,RN). Therefore, in the linear setting, the limit functional shall contain a term depending on the Cantor part of the measure derivative Du.
These features are in sharp contrast with the case where f grows superlinearly in the gradient variable. Indeed in this case the limit functional is defined on the smaller space (G)SBV(A,RN). Additionally, the superlinear growth of f in ∣∇u∣ makes it energetically unfavourable to approximate a pure jump function with elastic deformations, so that the only surface energy densities which can be obtained in the limit are necessarily independent of the jump amplitude of u, as recently proven in [15, 14, 16].
Motivated by the applications to anisotropic curve evolution [44, 45, 47], in this paper we study the homogenisation of the phase-field functionals in (1.1) which encompass the case of highly oscillating, possibly random metrics.
Moreover, since image-segmentation models are highly sensitive to the presence of heterogeneities in regions or objects due to noise, it is in general of great importance to incorporate a homogenisation procedure in these models and in their phase-field counterparts. ln fact, the presence of noise can cause random variations in the image intensity values, which in turn produce false detections in the image so that homogenisation may help to reduce the impact of noise, shadows, and changes in the illumination intensity, which usually make it difficult to accurately segment the image into its relevant parts. Therefore, in practice, by removing such, it can be easier to detect boundaries between different objects in the image, and to distinguish between foreground and background regions.
More specifically, in the present work we rigorously analyse the interplay between fine-scale oscillations and phase-field approximations in linear models as in (1.1). Due to the presence of microscopic heterogeneities, as ε tends to zero we expect to obtain an effective model where the (cohesive) energy density depends both on the homogenised integrand fhom (through its recession function) and on the regularised surface-term in (1.1). On the other hand, on account of the analysis in [7, 8] we also expect a limit volume energy which only depends on the first term in (1.1) and therefore in this case on fhom. A central feature of our analysis is that we study the homogenisation of Fε without imposing any periodicity of f in the spatial variable. In fact, in the same spirit as in [22, 24], we work under more general assumptions which, notably, are satisfied in the random stationary case.
Finally, it is also worth noticing that the homogenisation problem analysed in this paper can be seen as a case study of a homogenisation problem for the gradient-damage models proposed in [27, 49, 48, 32, 28, 29, 35, 4, 26] to approximate cohesive energies in Fracture Mechanics. Indeed, on account of the analysis performed in these papers, also in this case we expect effective surface integrands defined by asymptotic minimisation problems in which all the terms in the approximating functionals interact with one another. Moreover, when working with such approximations, a more technically demanding analysis shall be expected
due to the superlinear growth of the bulk energy density and to the more complex, parameter-dependent, choice of the degenerate function
multiplying f.
Below we briefly outline the proof strategy leading to our homogenisation result. Our approach is inspired by [22, 24], where the authors extend to the setting of free-discontinuity functionals the seminal work of Dal Maso and Modica [30]. In that foundational contribution, ergodic theory is combined with Γ-convergence for the first time, in the context of volume functionals. We also refer to [1] for a related homogenisation result concerning volume functionals with linear growth.
Loosely speaking, our strategy consists of two main steps: a purely deterministic one, where we devise sufficient conditions (on f) leading to homogenisation and a probabilistic step, where we show that if f is a stationary random variable, then the sufficient conditions mentioned above are indeed fulfilled. Therefore a stochastic homogenisation result readily follows as a corollary of the deterministic analysis.
1.1. Deterministic homogenisation
Here we assume that f satisfies the assumptions listed in Definition 2.4. Besides (1.2) these require that
the recession function f∞ is defined at every point. We stress here that we do not require any continuity of f in the spatial variable, since this would
be unnatural for the applications.
Under these general assumptions, using the localisation method of Γ-convergence [31], we can
prove the existence of a subsequence (εj) such that, for every A⊂Rn open and bounded, the functionals Fεj(⋅,⋅,A)Γ-converge to an
abstract functional F(⋅,⋅,A). Furthermore, the latter has the property that for every u∈BVloc(Rn,RN) the set function A↦F(u,1,A) is the restriction to the open subsets of Rn of a Borel measure (cf. Theorem 5.2). We observe that since we do not assume any spatial periodicity of f, the continuity of z↦F(u(⋅−z),1,A+z) may fail and therefore we cannot directly use the integral representation result in BV [17] to deduce the form of F. Our integral representation result is then obtained under some additional assumptions,
which are however more general than periodicity. We require that the limits of some scaled minimisation
problems, defined in terms of f and f∞, exist and are independent of the spatial variable. These
limits will then define the volume and surface integrands of F. Eventually, the Cantor integrand will be automatically identified due to the lower semicontinuity of F.
Specifically, we make the two following assumptions. If Qr(rx) denotes the open cube with side-length r centred at rx and ℓξ(x)=ξx, the first assumption amounts to asking that for every ξ∈RN×n the limit
[TABLE]
exists and it is independent of x∈Rn. The value of (1.4) is denoted by fhom(ξ).
Moreover, if Qrν(rx) denotes the open cube with side-length r centred at rx, one side orthogonal to ν∈Sn−1, and
[TABLE]
we also require that for every ζ∈RN and ν∈Sn−1 the limit
[TABLE]
exists and is independent of x∈RN. The value of (1.5) is denoted by ghom(ζ,ν).
It is worth mentioning here that fhom and ghom satisfy a number of properties (cf. Section 4) which ensure, in particular, that they are Borel measurable.
Then, assuming (1.4) and (1.5) we resort to the blow-up technique in BV [17] to show that for every u∈BV(A,RN) the following identities hold true
[TABLE]
In their turn, these allow us to represent F in an integral form first on BV, and then by standard truncation arguments on the domain of the Γ-limit, that is, on GBV.
Furthermore, since in the equalities above the right-hand side does not depend on the subsequence (εj), under assumptions (1.4) and (1.5) we obtain a Γ-convergence result for the whole sequence (Fε) (see Theorem 5.1).
1.2. Stochastic homogenisation
Here we consider an underlying complete probability space (Ω,T,P) endowed with a group of P-preserving transformations, and allow the integrand f to additionally depend on ω∈Ω, in a suitable measurable way. Then,
if f is a stationary random integrand in the sense of Definition 2.7, we show that assumptions (1.4) and (1.5) are automatically satisfied for P-a.e. ω∈Ω, that is, almost surely. As it is by-now costumery (see [22, 24]) this is done by appealing to the Ackoglu and Krengel Subadditive Ergodic Theorem [2].
More specifically, the proof that (1.4) holds is standard and follows as in [42]. On the other hand, the verification of (1.5) is highly non trivial, as it is always the case when working with “surface terms” where there is a dimensional mismatch between the domain of integration and the scaling, and, moreover, a boundary datum which is inherently inhomogeneous (cf. 1.5).
Once (1.4) and (1.5) are shown to hold (cf. Proposition 6.1 and Proposition 6.3) we can immediately resort to the deterministic analysis to deduce that the random functionals
[TABLE]
homogenise, almost surely, to the random, autonomous, free-discontinuity functional
[TABLE]
if u∈GBV(A,RN) and v=1Ln-a.e in A, where fhom and ghom are defined, respectively, by (1.4) and (1.5) while fhom∞ is the recession function of fhom (cf. Theorem 3.3 and Theroem 3.4). Eventually, if f is stationary with respect to an ergodic group of P-preserving transformations on (Ω,T,P), then the homogenisation procedure becomes effective and thus Fhom is deterministic.
2. Preliminaries and set up
2.1. Notation
We introduce some notation which will be used throughout the paper.
(a)
Let n,N∈N be fixed with n≥2. For x,y∈Rn and ζ∈RN, x⋅y:=x1y1+⋯+xnyn
is the euclidean scalar product of x and y, while ζ⊗x:=(ζixj)ij∈RN×n is the tensor product of ζ and x.
2. (b)
For x∈Rn and ν∈Sn−1, we set
Πν:={y∈Rn:y⋅ν=0} and Πxν:=x+Πν.
3. (c)
For ξ∈RN×n, ℓξ denotes the linear function from Rn to RN with gradient ξ.
4. (d)
For k∈N and x=(x1,…,xk)∈Rk, ∣x∣:=x12+⋯+xk2 is the euclidean norm of the vector x. Sk−1:={x∈Rk∣∣x∣=1} is the k−1-dimensional sphere centered in the origin and S^±k−1:={x∈Sk−1∣±xi(x)>0}, where i(x) is the largest i∈{1,…,k} such that xi=0. Note that Sk−1=S^+k−1∪S^−k−1 and S^±k−1 is a Borel set.
5. (e)
For ν∈Sn−1, let Rν be an orthogonal n×n matrix such that Rνen=ν; we assume that the restriction of the function ν↦Rν to the sets S^±n−1, defined in (d) of the notation list, are continuous and that R−νQ1=RνQ1; moreover we assume that Rν∈Qn×n if ν∈Qn. A map ν↦Rν satisfying these properties is provided in [23, Example A.1 and Remark A.2].
6. (f)
For x∈Rn and ρ>0 we set Bρ(x):={y∈Rn:∣y−x∣<ρ} and Q_{\rho}(x):=\{y\in\mathbb{R}^{n}\colon\;|(y-x)\cdot e_{i}|<\rho/2\textup{ for i=1,\dots,n}\}, where {e1,…,en} is the standard basis of Rn. Moreover Bρ and Qρ stand, respectively, for Bρ(0) and Qρ(0).
For x∈Rn, ρ>0, and ν∈Sn−1 we set
[TABLE]
For k∈N we define the rectangle
[TABLE]
where Qρν,k:=Rν((−2kρ,2kρ)n−1×(−2ρ,2ρ)). Moreover we set
[TABLE]
[TABLE]
7. (g)
A and A∞ denotes the collection of all bounded open sets and of all bounded open Lipschitz sets of Rn respectively; if A,B∈A, by A⊂⊂B we mean that exists a compact set K such that A⊂K⊂B. For every C∈A, we define A(C):={A∈A∣A⊆C} and A∞(C):={A∈A∞∣A⊆C}.
8. (h)
For every topological space X, B(X) denotes its Borel σ-algebra. For every integer k≥1, Bk is the Borel
σ-algebra of Rk, while BSn denotes the Borel σ-algebra of Sn−1.
9. (i)
Lk and Hk−1 denote respectively the Lebesgue and the (k−1)-dimensional Hausdorff measure on Rk.
10. (j)
Let μ and λ two Radon measures on A∈A, with values in a finite dimensional real vector space X and in [0,+∞], respectively; then dλdμ:=dλdμa∈Lloc1(A,X), where μa≪λ, μa+μs is the Radon-Nykodym decomposition of μ respect to λ and μa(B)=∫Bdλdμadλ for every Borel set B⊆A.
11. (k)
For u∈BV(A,RN), with A∈A, the jump of u on the jump set Ju is denoted by [u]:=u+−u−, while νu denotes the normal to Ju. The distributional gradient Du, is a RN×n-valued Radon measure on A, whose absolutely continuous part with respect to Ln, denoted by Dau, has density ∇u∈L1(A,RN×n) (which coincides with that approximate gradient of u), while the singular part Dsu can be decomposed as Dsu=Dju+Dcu where the jump part Dju is given by Dju=[u]⊗νuHn−1\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptJu,
and the Cantor part Dcu is a RN×n-valued Radon measure on A which vanishes on all Borel sets B⊆A with Hn−1(B)<+∞.
We refer to the book [9] for all the properties of (G)BV and (G)SBV functions, giving precise references.
12. (l)
For x∈Rn, ζ∈Rm, ν∈Sn−1 and ε>0 we define the function ux,ζ,ν,ux,ζ,νε:Rn→RN as
[TABLE]
where u:R→[0,1] is a fixed smooth cut-off function such that u≡1 on [1/2,+∞) and u≡0 on (−∞,−1/2].
We also use the shorthand notation uζ,ν:=u0,ζ,ν, ux,ζ,ν:=ux,ζ,ν1 and uζ,ν:=u0,ζ,ν.
13. (m)
We define the truncation functions Tk∈Cc1(RN,RN) satisfying
[TABLE]
and
[TABLE]
for some diverging and strictly increasing sequence of positive numbers (ak).
14. (n)
Given h:RN×n→[0,+∞] its recession function h∞:RN×n→[0,+∞] is defined as
[TABLE]
We will quote the book [31] for all the results on the abstract
theory of Γ-convergence needed in what follows.
2.2. The subadditive ergodic Theorem
In this subsection we recall a variant of the pointwise subaddtive ergodic Theorem of Ackoglu and Krengel [2, Theorem 2.7] which is useful for our purposes (cf. [37, Theorem 4.1]).
Let d∈N. Let (Ω,T,P) be a probability space and let τ:=(τz)z∈Zd denote a group of P-preserving transformations on (Ω,T,P), that is, τ is a family of measurable mappings τz:Ω→Ω satisfying the following properties:
•
τzτz′=τz+z′, τz−1=τ−z, for every z,z′∈Zd;
•
τ preserves the probability measure P; i.e., P(τzE)=P(E), for every z∈Zd and every E∈T;
If in addition every τ-invariant set E∈T, i.e. τzE=E for every z∈Zd,
has either probability [math] or 1, then τ is called ergodic.
For every a,b∈Rd with ai<bi for i=1,…,d, we define
[TABLE]
and we set
[TABLE]
Definition 2.1** (Subadditive process).**
Let τ:=(τz)z∈Zd be a group of P-preserving transformations on (Ω,T,P).
A d-dimensional subadditive process is a function μ:Ω×Id→R satisfying the following properties:
(a)
for every A∈Id the map ω↦μ(ω,A) is T-measurable;
2. (b)
for every ω∈Ω, A∈Id, and z∈Zd we have μ(ω,A+z)=μ(τzω,A);
3. (c)
for every A∈Id and for every finite family (Ai)i∈I in Id of pairwise disjoint sets such that ∪i∈IAi=A, we have
[TABLE]
for every ω∈Ω;
4. (d)
there exists c>0 such that
[TABLE]
for every ω∈Ω and every A∈Id.
Definition 2.2** (Regular family of sets).**
A family of sets (At)t>0 in Id is called regular with constant M∈(0,+∞) if there exists another family of sets (At′)t>0 in Id such that:
•
At⊂At′* for every t>0;*
•
As′⊂At′* whenever 0<s<t;*
•
0<Ld(At′)≤MLd(At)* for every t>0;*
•
⋃t>0At′=Rd.
Theorem 2.3** (Subadditive Ergodic Theorem).**
Let τ=(τz)z∈Zd be a group of P-preserving transformations on (Ω,T,P). Let μ:Ω×Id→[0,+∞) be a d-dimensional subadditive process. Then there exist a T-measurable function φ:Ω→[0,+∞) and a set Ω′∈T with P(Ω′)=1 such that
[TABLE]
for every regular family of sets (At)t>0 in Id and for every ω∈Ω′. If in addition τ is ergodic, then φ is constant P-a.e.
2.3. Assumptions
In this subsection we introduce the class of the admissible random integrands.
Definition 2.4** (Admissible integrand).**
Let C≥1 and α∈(0,1) be given, then F(C,α) denotes the collection of all functions f:Rn×RN×n→[0,+∞) with the following properties:
(f1)
(measurability)* f is Bn⊗BN×n-measurable;*
2. (f2)
(linear growth)* for every x∈Rn and every ξ∈RN×n*
[TABLE]
3. (f3)
(continuity)* for every x∈Rn the maps
ξ↦f(x,ξ) and ξ↦f∞(x,ξ)
are continuous;*
4. (f4)
(recession function)* for every x∈Rn every ξ∈RN×n and every t>0*
[TABLE]
Remark 2.5**.**
Let f∈F(C,α), then thanks to (f2) and (f4), for every x∈Rn and every ξ∈RN×n we have that there exists the limit
[TABLE]
and
[TABLE]
Moreover, for every L>0 there exists M>0 such that for every x∈Rn, ξ∈RN×n with ∣ξ∣=1 and t>L we have that
[TABLE]
Definition 2.6** (Random integrand).**
A function f:Ω×Rn×RN×n→[0,+∞) is called a random integrand if
(s-f1)
f* is T⊗Bn⊗BN×n-measurable;*
2. (s-f2)
f(ω,⋅,⋅)∈F(C,α)* for every ω∈Ω, where F(C,α) is as in Definition 2.4.*
If f is a random integrand then f∞:Ω×Rn×RN×n→[0,+∞) is given by
[TABLE]
where the existence of the limit above is ensured by the very definition of random integrand together with Remark 2.5.
Definition 2.7** (Stationary random integrand).**
A random integrand f is stationary if there exists τ=(τz)z∈Znn-dimensional group of P-preserving transformation on (Ω,T,P) such that
[TABLE]
for every ω∈Ω, x∈Rn, z∈Zn, and ξ∈RN×n.
If in addition τ is ergodic we call f an ergodic random integrand.
3. Statements of the main results
Let f be a given stationary random integrand. For ε>0 we consider the phase-field functionals Fε(ω):Lloc1(Rn,RN+1)×A⟶[0,+∞] defined as
[TABLE]
Remark 3.1**.**
For v∈W1,2(A) set v~:=min{max{0,v},1}. We notice that for every ε>0, ω∈Ω there holds
[TABLE]
for every (u,v)∈W1,1(A,RN)×W1,2(A) and A∈A.
Therefore it is not restrictive to assume that the phase-field variable v satisfies the pointwise bounds 0≤v≤1 for Ln-a.e. x∈A.
Remark 3.2** (Equi-coercivity).**
The coercivity assumption in (f2) immediately gives that
[TABLE]
where the functionals on the left-hand side are those studied in [7] (see also [8]). Hence, up to considering the perturbed functionals
[TABLE]
for some q>1, we can appeal to [8, Lemma 7.1] to deduce that if (uε,vε)⊂W1,1(A,RN)×W1,2(A,[0,1]) satisfies
[TABLE]
then, up to subsequences, (uε,vε)→(u,1) strongly in L1(A,RN+1) for some u∈GBV(A,RN).
For this reason, in what follows we are going to study the Γ-convergence of Fε with respect to the strong L1-convergence.
Before stating our main results we need some additional notation. Let h:Rn×Rn×N→[0,∞) satisfy (f2) and (f1). For A∈A∞ and (u,v)∈W1,1(A,RN)×W1,2(A,[0,1]) consider the following auxiliary integral functionals
[TABLE]
and
[TABLE]
Moreover, let w∈BVloc(Rn,RN) and define the minimisation problems
[TABLE]
and
[TABLE]
where u=w on ∂A has to be intended in the sense of traces and inner traces for u and w, respectively.
If A⊆Rn is a set such that intA∈A∞ then we use the following convention mbh(w,A):=mbh(w,intA) and msh(w,A):=msh(w,intA).
The main result of this paper is contained in Theorem 3.4, below, and provides an almost sureΓ-convergence result for the functionals Fε defined in (3.1).
In order to state this result we preliminarily need to state a theorem which guarantees the almost sure existence of the integrands of the Γ-limit. Namely, the next theorem establishes the existence and spatial homogeneity of the limits defining the asymptotic cell formulas appearing in Theorem 3.4 below.
Throughout the paper we adopt the following shorthand notation.
[TABLE]
Theorem 3.3** (Homogenisation formulas).**
Let f be a stationary random integrand. Then there exists Ω′∈T with P(Ω′)=1, such that for every ω∈Ω′
(i)
every x∈Rn, ν∈Sn−1, k∈N, and ξ∈RN×n, the limit
[TABLE]
exists and it is independent of x,ν and k;
(ii)
every x∈Rn, ζ∈RN, and ν∈Sn−1, the limit
[TABLE]
exists and it is independent of x.
More precisely there exist a T⊗BN×n-measurable function fhom:Ω×RN×n→[0,∞) and a T⊗BN⊗BSn-measurable function ghom:Ω×RN×Sn−1→[0,+∞) such that for every ω∈Ω′, x∈Rn, ξ∈RN×n, ζ∈RN, and ν∈Sn−1
[TABLE]
[TABLE]
[TABLE]
where fhom∞ denotes the recession function of fhom.
If we additionally assume that f is ergodic, then fhom and ghom are independent of ω and
[TABLE]
[TABLE]
[TABLE]
We are now in a position to state the main result of this paper.
Theorem 3.4** (Almost sure Γ-convergence).**
Let f be a stationary random integrand. For ε>0 and ω∈Ω let Fε(ω) be the functionals defined in (3.1). Then, there exists Ω′∈T with P(Ω′)=1 such that
for every ω∈Ω′, A∈A, and (u,v)∈Lloc1(Rn,RN+1) we have
[TABLE]
where Fhom(ω):Lloc1(Rn,RN+1)×A⟶[0,∞] is defined as
If in addition f is ergodic, then the functional Fhom is deterministic.
The proof of Theorem 3.4 will be carried out in a number of steps in the next sections.
4. Properties of the homogenized integrands
In this section we prove a number of structural properties of the homogenized integrands fhom and ghom.
For later use, it is convenient to work in a deterministic framework where the dependence of fhom and ghom on ω is not taken into account. Then, as a consequence, we need to assume that the limits defining fhom and ghom exist and are spatially homogeneous.
We start with fhom.
Proposition 4.1**.**
Let f∈F(C,α) and assume that for every x∈Rn and ξ∈RN×n the limit
[TABLE]
exists (and is independent of x).
Then, fhom satisfies the following properties:
(i)
fhom* is quasi-convex;*
2. (ii)
for every ξ1,ξ2∈RN×n
[TABLE]
where K is a constant that depends only on n,N and C;
3. (iii)
for every ξ∈RN×n
[TABLE]
Proof.
(i) The quasi-convexity of fhom defined as in (4.1) is shown in [42, Proposition 5.5 Step 2].
(ii) Let ξ1,ξ2∈RN×n and r>0 be fixed. For every u∈BV(Qr,RN) and A∈A(Qr) consider the auxiliary functional defined as
[TABLE]
as well as J(⋅,A):=sc−(L1)J(⋅,A).
By (f2) we have that J(u,A)≤C(∣Du∣(A)+Ln(A)), therefore thanks to [17, Lemma 3.1 and Lemma 4.1.2] we get
Below we prove that fhom∞ can be equivalently expressed as the limit of suitable (scaled) minimisation problems. To prove it we make use of the following lemma.
Lemma 4.2**.**
Let g∈F(C,α), A∈A, (u,v)∈W1,1(A,RN)×W1,2(A,[0,1]), then for every t>0 we have that
[TABLE]
where K is a positive constant depending only on C and α.
Let f∈F(C,α) and assume that for every x∈Rn, ν∈Sn−1, k∈N, and ξ∈RN×n
[TABLE]
where fhom is as in (4.1).
Let fhom∞ be the recession
function of fhom, then for every x∈Rn, ξ∈Rn×N, ν∈Sn−1 and k∈N we have
[TABLE]
hence, in particular, fhom∞=(f∞)hom.
Proof.
Let x∈Rn, ξ∈Rn×N, ν∈Sn−1, k∈N and η∈(0,1) be fixed. By (3.4), for every r>0 there exists ur∈W1,1(Qrν,k(rx)) with ur=ℓξ on ∂Qrν,k(rx), such that
[TABLE]
and
[TABLE]
In particular, by Lemma 4.2, for every t≥1 we obtain
[TABLE]
where K^ depends only on C, α and ξ. Hence, for t≥1,
[TABLE]
where ft(y,ξ):=tf(y,tξ) and consequently, by (4.5),
[TABLE]
Observing that mbft(ℓξ,Qrν,k(rx))=t1mbf(ℓtξ,Qrν,k(rx)), thanks to the linearity of ξ↦ℓξ, we get
[TABLE]
by (4.4). Hence, from (4.6) and (4.7), letting η→0, we have
[TABLE]
Exchanging the role of ft and f∞ and arguing analogously, we obtain
[TABLE]
To prove the properties satisfied by ghom, we first establish some technical results in the spirit of [17, Section 3].
Lemma 4.4**.**
Let x∈Rn, r>1, ν∈Sn−1, and w1,w2∈BVloc(Rn,RN), then we have that
[TABLE]
Proof.
First we observe that for every w∈BVloc(Rn,RN), x∈Rn,
ν∈Sn−1, and r>1 there holds
msf∞(w,Qrν(rx))=msf∞,∗(w,Qrν(rx)),
where
[TABLE]
with Sf∞ defined in (3.3).
In fact, given η∈(0,1), u∈W1,1(Qrν(x),RN) and v∈W1,2(Qrν(x),[0,1]), vη:=v∨η∈W1,2(Qrν(x),[0,1]) with vη=1 on ∂Qrν(x), and
[TABLE]
and
[TABLE]
Let v∈W1,2(Qrν(x),[0,1]) with v=1 on ∂Qrν(x) and
v≥η for some η∈(0,1). Define the functional Fv:BV(Qrν(x),RN)×A(Qrν(x))⟶[0,+∞] as
[TABLE]
Consider its relaxation Fv:=sc−(L1)Fv:BV(Qrν(x),RN)×A(Qrν(x))→[0,+∞].
[17, Lemma 3.1 and Lemma 4.1.2] and Fv(u,B)≤C∣Du∣(B) imply that
[TABLE]
where for every w∈BV(Qrν(x),RN)
[TABLE]
In addition, mFv(wi,Qrν(x))=mFv(wi,Qrν(x)) for i∈{1,2} by [17, Lemma 4.1.3], where mFv(⋅,Qrν(x)) is defined as mFv(⋅,Qrν(x)) with the functional Fv replaced
by Fv.
Therefore, using (4) we can rewrite
msf∞(w,Qrν(rx)) as
We are now in a position to establish some properties satisfied by ghom.
Proposition 4.7**.**
Let f∈F(C,α) and assume that for every x∈Rn, ζ∈RN, and ν∈Sn−1 the limit
[TABLE]
exists (and is independent of x).
Then, ghom satisfies the following properties:
(i)
for every ζ1,ζ2∈RN and every ν∈Sn−1
[TABLE]
(ii)
ghom:RN×S^±n−1→[0,+∞)* is continuous;*
(iii)
for every ζ∈RN and every ν∈Sn−1
[TABLE]
(iv)
for every ζ∈RN and every ν∈Sn−1
[TABLE]
Proof.
To prove (i) fix ν∈Sn−1 and ζ1,ζ2∈RN×n. Thanks to Lemma 4.4 we get
[TABLE]
By the definition of uζ,ν we have
[TABLE]
Then we conclude by (4.14) also noticing that by Corollary 4.5 we have
[TABLE]
for every x∈Rn, ζ∈RN, and ν∈Sn−1.
To prove (ii) we preliminarily show that ghom(ζ,⋅):S^±n−1→[0,+∞) is continuous for every ζ∈RN. Fix ζ∈RN, ν∈S^±n−1 and a sequence (νj)j∈N in S^±n−1 such that νj→ν as j→+∞. For every δ∈(0,1/2), by the continuity of the map ν↦Rν on S^±n−1
(cf. (e) of the notation list), there exists jδ such that for every r>0 and every j≥jδ
[TABLE]
Setting κj:=max{∣Rνj(ei)⋅ν∣:i=1,…,n−1}, we have that κj→0 as j→+∞, by the continuity of the map ν↦Rν on S^±n−1. Letting y∈Qr(1+δ)νj, then y=y′+(y⋅νj)νj where
[TABLE]
In particular (y⋅νj)(ν⋅νj)=y⋅ν−y′⋅ν and thus, if ∣y⋅ν∣≤21 and j is large enough, we get
[TABLE]
where K(δ):=2(1−δ)(n−1)(1+δ). Applying Lemma 4.6 with R=K(δ)rκj+1, we deduce
[TABLE]
where K~ depends only on n and C. Consequently, letting the r→+∞, appealing to (4.14) and to Corollary 4.5, we get
[TABLE]
Taking the limsup for j→+∞ we have
[TABLE]
thus letting η,δ→0 we obtain
[TABLE]
An analogous argument, using the cube Q(1−δ)rνj, shows that
[TABLE]
and hence the claim.
To establish the continuity with respect to both variables, consider a sequence (ζj)j∈N in RN×n such that ζj→ζ.
Thanks to (4.15), we have that
[TABLE]
and therefore we get (ii).
To prove (iii) fix ζ∈RN and ν∈Sn−1, and recall that by (4.14) and the spatial homogeneity of ghom
we have that
[TABLE]
We notice that for every r>0 and M∈N we have
[TABLE]
Indeed, assume for simplicity ν=en, then if (u,v) is a competitor for msf∞(uζ,en,Qren) then
(uM,vM) defined by (u,v)(x−ri) for x∈ri+Qren, for i∈Zn−1×{0} with components in [−M+1,M−1],
and equal to uζ,en otherwise on QMren is a competitor for msf∞(uζ,en,QMren)
with
Sf∞(uM,vM,QMren)=Mn−1Sf∞(u,v,Qren).
Thus, we infer that
[TABLE]
Moreover, by (f2) and C≥1,
recalling the definiton in (3.3),
we have that
Eventually, (iv) is a direct consequence of the identity Rν(Q1)=R−ν(Q1) and of the fact that
u=u−ζ,−ν on ∂Qrν if and only if u+ζ=uζ,ν on ∂Qrν for every ζ∈RN, ν∈Sn−1, r>0, and u∈W1,1(Qrν,RN).
∎
5. Deterministic homogenisation
To prove the stochastic homogenisation result in Theorem 3.4 we follow the same proof strategy as in [22, 24].
To this end, we preliminarily work in a deterministic framework (where ω∈Ω is regarded as fixed) and prove a homogenisation result without assuming any periodicity of the integrand. Then, in Section 6, the deterministic homogenisation result at fixed ω will be used in combination with the Subadditive Ergodic Theorem, Theorem 2.3, to derive an almost sure Γ-convergence result for the random functionals Fε(ω).
The main result of this section is stated in the following theorem.
Theorem 5.1** (Deterministic homogenisation).**
Let f∈F(C,α) and consider the phase-field functionals
Fε:Lloc1(Rn,RN+1)×A⟶[0,+∞] given by
[TABLE]
Assume that
(i)
for every x∈Rn, ξ∈RN×n, ν∈Sn−1 and k∈N the limit
[TABLE]
*exists and is independent of x,ν and k; *
2. (ii)
for every x∈Rn, ζ∈RN and ν∈Sn−1 the limit
[TABLE]
exists and is independent of x.
Let, moreover, fhom∞ be the recession function of fhom. Then, for every A∈A and every (u,v)∈Lloc1(Rn,RN+1) we have
[TABLE]
where Fhom:Lloc1(Rn,RN+1)×A⟶[0,+∞] is the functional defined by
[TABLE]
if u∈GBV(A,RN) and v=1Ln-a.e in A, Fhom(u,v,A)=+∞, otherwise.
To prove Theorem 5.1 we use a standard approach in homogenisation theory based on the compactness of Γ-convergence and on the so-called localization method (cf. [20, 31]). Namely, we first show that for every
infinitesimal sequence (εj)j∈N, up to a subsequence, the functionals Fεj, defined in (5.1), Γ-converge to some abstract functional F. Then, we prove
that F admits an integral representation as in (5.4) on BV(A,RN), for every A∈A. Eventually, thanks to (5.2) and (5.3) we deduce that
F does not depend on the extracted subsequence, and hence the homogenisation result for (Fε) follows by the Urysohn property of Γ-convergence.
We start by proving the following abstract Γ-convergence result.
Theorem 5.2** (Γ-convergence and properties of the Γ-limit).**
Let f∈F(C,α) and Fε be as in (5.1), then there exists a subsequence (εj)j∈N and a functional F:Lloc1(Rn,RN+1)×A⟶[0,+∞] such that, for every A∈A and every u∈Lloc1(Rn,RN) with u∈BV(A,RN)
[TABLE]
Moreover F satisfies the following properties:
(i)
(locality) F(u1,1,A)=F(u2,1,A) for every A∈A and every u1,u2∈Lloc1(Rn,RN) such that u1=u2Ln-a.e in A;
2. (ii)
(semicontinuity) for every A∈A the functional F(⋅,1,A):Lloc1(Rn,RN)⟶[0,+∞] is lower semicontinuous;
3. (iii)
(upper bound) for every A∈A and every u∈Lloc1(Rn,RN) with u∈BV(A,RN) there holds
[TABLE]
4. (iv)
(lower bound) for every M>0 there exists CM>0 such that for every A∈A and every u∈Lloc1(Rn,RN) with u∈BV(A,RN) and ∥u∥L∞(A,RN)≤M we have
[TABLE]
5. (v)
(measure property) for every A∈A, every u∈Lloc1(Rn,RN) such that u∈BV(A,RN), the set function F(u,1,⋅):A(A)→[0,+∞] is the restriction of a finite Radon measure on A;
6. (vi)
(translation invariance in u) for every A∈A and every u∈Lloc1(Rn,RN) we have
[TABLE]
for every z∈RN.
Proof.
Given any sequence of positive real numbers decreasing to zero [31, Theorem 16.9] provides us with a subsequence (εj) such that
[TABLE]
where F:Lloc1(Rn,RN+1)×A⟶[0,+∞] is increasing, inner regular, and superadditive as a set function and lower semicontinuous in Lloc1(Rn,RN+1) as a functional. By definition of Γ-convergence, we have
[TABLE]
where
[TABLE]
and
[TABLE]
The locality property and the translation invariance of F are direct consequences of (5.8), and of the locality and translation invariance of F′ and F′′.
Arguing exactly as in [8, Lemma 5.1], for every A∈A, every u∈Lloc1(Rn,RN) such that u∈BV(A,RN), every A′,A′′∈A(A) and every B′⊂⊂A′, with B′∈A(A) we can obtain that
[TABLE]
from which we can easily deduce that the inner regular envelope F−′′(u,1,⋅) is subadditive on A(A). Therefore, thanks to the De Giorgi-Letta Criterion, we infer that the set function F(u,1,⋅):A(A)→[0,+∞] is the restriction to the open sets of a Borel measure on A.
For every A∈A, and every u∈Lloc1(Rn,RN) with u∈BV(A,RN), in view of (f2), we obtain
The latter eventually provides the Γ-convergence statement in (5.5).
To prove the lower bound inequality in item (iv) we argue as follows.
By (f2), a comparison argument and [8, Proposition 4.1]
(see [8, Remark 3.5]) we infer that
[TABLE]
where g(s)=s+22s for all s≥0 (cf. (4.21)).
Finally, note that for every M>0 there is CM>0 such that
g(s)≥CMs for every s∈[0,2M], and the conclusion follows at once.
∎
The next three subsections are devoted to the proof of
Theorem 5.1. Namely, in subsections 5.1 - 5.3 we identify, respectively, the three measure derivatives
[TABLE]
In fact, we will prove that under the assumptions of Theorem 5.1, for every A∈A and
u∈BV(A,RN) the following three equalities hold:
[TABLE]
Since in the equalities above the right-hand sides do not depend on the subsequence (εj)j∈N, we will be able to conclude that F is subsequence independent and therefore the Γ-convergence result holds for the whole sequence (Fε) (cf. Theorem 5.1).
The strategy to prove the identities above uses, on one hand, the global method for relaxation in BV [17] and, on the other hand, a direct (although involved) comparison argument.
For later use it is useful to recall the following notation: let U∈A∞ and let G:BV(U,RN)×A(U)⟶[0,∞);
for every (w,A)∈BV(U,RN)×A∞(U) set
[TABLE]
In addition, we use the notation sc−(L1)G for the relaxation of G with respect to the L1 convergence, namely
sc−(L1)G(u,A):=Γ(L1)-limjG(u;A) (cf. [31]).
In what follows we will use in several instances a truncation lemma that follows from De Giorgi’s slicing and averaging argument on the codomain
(see for instance [8, Proposition 6.2] and [28, Proposition 3.2]). We give here a detailed proof of it since the statement is slightly
different from the standard one. In particular, in Propositions 5.4 and 5.9 we
choose v≡1, while in Proposition 5.7 it is important that the constant γ in
the growth condition below equals [math]. We recall the notation Tk for the smooth truncation operators and ak for the related sequence
introduced in (m).
Lemma 5.3**.**
Let A∈A and G:GBV(A,RN)×L1(A,[0,1])→[0,∞] be the functional defined by
[TABLE]
where g:Rn×RN×n→[0,∞) is a Borel function for which there exists γ∈[0,∞) such that
[TABLE]
for every (x,ξ)∈Rn×RN×n, and for some c>0.
Then for every M∈N and (u,v)∈GBV(A,RN)×L1(A,[0,1]) there exists k∈{M+1,…,2M} such that Tk(u)∈BV∩L∞(A,RN) with ∥Tk(u)∥L∞≤ak+1, Hn−1(JTk(u)∩A)≤Hn−1(Ju∩A) and
[TABLE]
Proof.
Let us fix M∈N and (u,v)∈GBV(A,RN)×L1(A,[0,1]) with G(u,v)<∞, otherwise the claim follows trivially.
By averaging, there exists k∈{M+1,…,2M} such that
[TABLE]
By the properties of GBV functions and the very definition of Tk, we have that Tk(u) belongs to BV(A,RN)∩L∞(A,RN) with ∥Tk(u)∥L∞≤ak+1, JTk(u)∩A⊆Ju∩A and ∇(Tk(u))(x)=∇Tk(u(x))∇u(x) for Ln-a.e. x∈A. Furthermore, being Lip(Tk)≤1, we can check for every y,v∈RN with ∣v∣=1 that ∣(∇Tk(y))v∣=∣∂vTk(y)∣≤1 that provides ∥∇Tk(y)∥2≤1 for every y∈RN (here ∥⋅∥2 stands for the matrix norm on RN×N induced by ∣⋅∣ on RN) and consequently
[TABLE]
In particular, in virtue of Tk(y)=y on {∣y∣<ak} and Tk(y)=0 on {∣y∣≥ak+1}, we obtain
[TABLE]
where in the first inequality we used (5.10), in the second one (5.12), and finally in the last one (5.10) and (5.11).
∎
5.1. Identification of the volume term
This section is devoted to identify the measure derivative
dLndF(u,1,⋅) with fhom.
To prove Proposition 5.4, we need the two following technical lemmas.
Lemma 5.5**.**
Let g∈F(C,α) be given and define g^:Rn×RN×n→[0,∞) as
[TABLE]
Let A∈A∞ and let Eg(⋅,A) and Eg^(⋅,A) be defined as in
(3.2) with h replaced by g and g^, respectively. Moreover, consider the functionals
Fg,Fg^:L1(A,RN)⟶[0,∞] given by
[TABLE]
Then the following statements hold:
(i)
if g is 1-homogeneous in ξ, then the same holds for g^;
2. (ii)
there exists H⊆Rn with Ln(H)=0 such that for every x∈Rn∖H and every ξ∈RN×n
[TABLE]
3. (iii)
for every u∈W1,1(A,RN)
[TABLE]
4. (iv)
for every u∈BV(A,RN)
[TABLE]
5. (v)
for every u∈L1(A,RN)
[TABLE]
6. (vi)
for every ξ∈RN×n
[TABLE]
Proof.
Property (i) readily follows from the definition of g^.
Instead, (iii) and (iv) are a direct consequence of [17, Theorem 4.1.4].
To prove (ii) let ξ∈QN×n be fixed, by definition we get
[TABLE]
for every x∈Rn. Then, the Lebesgue Differentiation Theorem provides us with a set Hξ⊂Rn such that Ln(Hξ)=0 and g^(x,ξ)≤g(x,ξ) for every x∈Rn∖Hξ.
Therefore, we conclude by setting
[TABLE]
and invoking the continuity of g, (f3), and the lower
semicontinuity of g^ as the bulk energy density of the functional
sc−(L1)Fg^.
The proof of (v) follows straightforwardly from (ii) and (iii).
To conclude the proof, we are left to show (vi). We start noticing that in view of (ii) we only need to prove that
[TABLE]
for every ξ∈RN×n.
To prove the inequality above, fix ξ∈RN×n and let u∈W1,1(A,RN) satisfy u=ℓξ on ∂A. By (iii) we can infer the existence of a sequence (uj)j∈N⊂W1,1(A,RN) such that uj→u in L1(A,RN) as j→∞ and
[TABLE]
By [17, Lemma 2.6 and Remark 2.7] we can find a sequence (wj)j∈N⊂W1,1(A,RN) satisfying wj=ℓξ on ∂A such that wj→u in L1(A,RN) as j→∞ and
[TABLE]
therefore the claim follows by the arbitrariness of u.
∎
Using a classical argument of Ambrosio, in the following lemma we prove a truncation result in the same spirit as in [28, Lemma 4.4].
Lemma 5.6**.**
Let Fε be the functionals defined in (5.1). Then, for every δ∈(0,1), A∈A, and (u,v)∈Lloc1(Rn,RN+1) with u∈W1,1(A,RN)∩L∞(A,RN) and v∈W1,2(A,[0,1]), there exists uδ∈Lloc1(Rn,RN)∩SBV(A,RN) (also depending on A) such that for every ε>0
[TABLE]
where Hεδ:Lloc1(Rn,RN)×A⟶[0,+∞] is the functional given by
[TABLE]
with αδ,βδ>0 such that
[TABLE]
Moreover, if (uε,vε)→(u,1) in L1(A,RN+1) as ε→0, then the corresponding (uεδ) satisfies
[TABLE]
Proof.
Let δ∈(0,1), ε>0, A∈A, and (u,v)∈W1,1(A,RN)×W1,2(A,[0,1]) be given. We have
[TABLE]
where αδ:=t∈[δ2,1]mint2=δ4. Set
[TABLE]
By the Coarea Formula we can infer that
[TABLE]
therefore, there exists tδ∈(Φ(δ2),Φ(δ)) such that
[TABLE]
Set uδ:=uχ{v>Φ−1(tδ)}; we notice that uδ∈Lloc1(Rn,RN)∩SBV(A,RN) since {v>Φ−1(tδ)} is a set of finite perimeter in A and u∈L∞(A,RN).
Since by definition Juδ∩A⊆∂∗({Φv>tδ})∩A, (5.17) becomes
[TABLE]
where βδ:=Φ(δ)−Φ(δ2).
Moreover, by the strict monotonicity of Φ on [0,1], we get
Fix A∈A and u∈Lloc1(Rn,RN) with u∈BV(A,RN)∩L∞(A,RN). We divide the proof into two steps.
Step 1: We claim that
[TABLE]
In particular, we claim the previous equality to be true for every point
x∈A for which the conditions ρ−n∣Du∣(Qρ(x))→∣∇u(x)∣ and
ρ−n∣Dsu∣(Qρ(x))→0 as ρ→0, and the Calderón-Zygmund Theorem holds for x (cf. [9, Theorem 3.83]).
For every A∈A and q∈Q∩(0,1) set
Fq(u,A):=F(u,1,A)+q∣Du∣(A).
Thanks to [17, Lemma 3.5] we obtain that
for Ln-a.e. x∈A
[TABLE]
where
where mFq is as in (5.9).
Let x∈A be that (5.21) holds, and set ξ:=∇u(x).
In view of (4.1), for every ρ>0 we have
[TABLE]
Fix η∈(0,1). By (3.4), for every ρ,r>0 there exists wrρ∈W1,1(Qr(ρrx),RN) with wrρ=ℓξ on ∂Qr(ρrx), such that
Now, let (εj)j∈N be as in (5.5) and set r=εjρ. Define uεjρ:Rn→RN as
[TABLE]
therefore uεjρ∈Wloc1,1(Rn,RN) with uεjρ=ℓξ on Rn∖Qρ(x). Changing variables and again invoking (5.23), for every ρ>0 we get
[TABLE]
where we also used (f2), the fact that ∇uεjρ=ξ on Qρ(1+η)(x)∖Qρ(x), and (5.5).
Appealing to (5.24), (f2), and the Poincaré Inequality, for every ρ we can find a subsequence of (εj)j∈N (not relabeled) such that uεjρ converges in Lloc1(Rn,RN) to some uρ∈Lloc1(Rn,RN)∩BV(Qρ(1+η)(x),RN) with uρ=ℓξ on ∂Qρ(1+η)(x). Moreover, by (5.5), (5.24), and (f2), for every ρ>0, we have that
[TABLE]
Eventually, by (5.21) and taking the limit as ρ→0 we get
[TABLE]
hence the claim follows by letting η,q→0.
Step 2: We claim that
[TABLE]
Let A′∈A(A), by Theorem 5.2, we can find a sequence (uj,vj)j∈N∈Lloc1(Rn,RN) such that (uj,vj)∈W1,1(A′,RN)×W1,2(A′,[0,1]), (uj,vj)→(u,1) in Lloc1(Rn,RN+1), vj(x)→1 for Ln-a.e. x∈A′ as j→+∞ and
[TABLE]
Without loss of generality we may assume uj∈L∞(A′;Rn).
Indeed, it suffices to apply Lemma 5.3 for every j∈N to uj
with Mj→∞ and note that by construction
Tkj(uj)→u in Lloc1(Rn,RN),
and by (5.25)
where (ujδ)⊂SBV(A′,RN) with ujδ→u in L1(A′,RN). Therefore by (5.25) we get
[TABLE]
since (vj)j∈N converges in measure to 1 on A′.
We now consider the measures μjδ defined on A′ as follows
[TABLE]
Note that by (5.26), there is a subsequence (not relabeled) and a finite Radon measure μδ on A′ such that μjδ⇀∗μδ
as j→+∞.
Now let x0∈A′ be a point of approximate differentiability of u, and additionally assume that
[TABLE]
Such conditions determine a subset of full measure in A′. Then, consider the rescaled function uρ:Q1→RN given by
[TABLE]
thanks to [9, Remark 3.72] we have uρ→ℓξ in L1(Q1,RN), where ξ:=∇u(x0).
By the weak∗-convergence of μjδ towards μδ we have
[TABLE]
where I(x0):={ρ∈(0,n2dist(x0,∂A′)):μδ(∂Qρ(x0))=0}.
For every ρ and j, define the rescalings ujρ∈SBV(A′,RN) by
[TABLE]
then ujρ→uρ in L1(Q1,RN) as j→+∞. Furthermore, thanks to (5.28) we get
[TABLE]
Fix M∈N, for every ρ and j, we apply Lemma 5.3 with v≡1 so that there is kρ,j∈{M+1,…,2M} such that
u^jρ:=Tkρ,j(ujρ)∈SBV(Q1,RN),
[TABLE]
Up to subsequences (not relabeled) we can assume that kρ,j∈{M+1,…,2M} actually depends only on ρ. If we choose aM>supy∈Q1ℓξ(y) we get that
[TABLE]
and
[TABLE]
since we also have that ρ→0limj→+∞limujρ=ℓξ in L1(Q1,RN).
In particular, for M is large enough, by combining (5.29), (5.30), and (5.31) we can infer
[TABLE]
and
[TABLE]
since Tkρ,j∈C1(RN,RN), dLndμδ(x0) is finite, and βδ>0. Set
[TABLE]
then, ρ→0limj→+∞limτρ,j=0. Thus, for every ρ>0 small and every j large (depending on ρ) we have τρ,j∈(0,1).
Therefore, thanks to the Coarea formula and to the properties of the traces of BV functions on rectifiable sets (see [9, Theorem 3.77]), there exists r^ρ,j∈(1−τρ,j1/2,1) such that
[TABLE]
where (u^jρ)− is the inner trace of u^jρ on ∂Qr^ρ,j.
Therefore, defining the functions wjρ∈SBV(Q1,RN) as
and, since ρ→0limj→+∞limr^ρ,j=1, from (5.32) we obtain
[TABLE]
Furthermore, thanks to (5.34), (2.2), and to the definition of u^jρ we can estimate the singular part of Dwjρ as follows
[TABLE]
Now, for every ρ> and j∈N, consider functional Fρ,j:L1(Q1,RN)⟶[0,∞] given by
[TABLE]
In view of Lemma 5.5 (iv), for every w∈SBV(Q1,RN) we have
[TABLE]
where fρ,j:=g^, with g(x,ξ):=f(εjx0+ρx,ξ) for every (x,ξ)∈Rn×RN×n
(cf. (5.13)).
By the definition of relaxed functional and correction of the boundary datum via [17, Lemma 2.6], for every ρ and j we can find w^jρ∈W1,1(Q1,RN) with w^jρ=ℓξ on ∂Q1 and such that
[TABLE]
In particular, from (5.36), (5.37) and (5.38)
and the equality fρ,j(y,ξ)=f^(εjx0+ρy,ξ)
which follows from formula (5.13), we infer
[TABLE]
Setting
[TABLE]
we have wjρ∈W1,1(Qrρ,j(ρrρ,jx0),RN) with wjρ=ℓξ−εj1x0 on ∂Qrρ,j(ρrρ,jx0) and
by letting M→∞. Hence, recalling (5.26), we deduce that
[TABLE]
Eventually, the claim follows by letting δ→0 and by the arbitrariness of A′∈A(A).
∎
5.2. Identification of the surface term
In this subsection we show that the Radon Nikodym derivative of F with respect to Hn−1\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptJu equals to ghom for every u∈BV.
To prove Proposition 5.7 we need a preliminary lemma which is an extension to our setting of some results contained in [17].
Lemma 5.8**.**
Let U∈A be fixed and let G:BV(U,RN)×A(U)⟶[0,∞) be such that
(1)
for every u∈BV(U,RN) the set function G(u,⋅) is the restriction to A(U) of a finite Radon measure on U;
2. (2)
for every A∈A(U) the functional G(⋅,A) is L1(A,Rn)-lower semicontinuous;
3. (3)
there exists K∈(0,∞) such that
[TABLE]
for every u∈BV(U,RN) and every A∈A(U).
4. (4)
For every M∈(0,∞) there exists KM∈(0,∞) such that
[TABLE]
for every u∈BV(U,RN) with ∥u∥L∞(U)≤M and every A∈A(U).
Then, if w∈BV(U,RN) is such that 2∥w∥L∞(U)≤M we have that for Hn−1-a.e. x∈Jw
[TABLE]
where
[TABLE]
Proof.
The proof follows by combining a number of arguments from [17, Section 3] which we briefly summarize.
Appealing to [17, Lemma 3.5 and formula (3.17) in Theorem 3.7] the equality in (5.40) can be established for functionals G satisfying assumptions (1)-(3) above,
and the stronger growth condition
[TABLE]
for every u∈BV(A,RN).
In their turn, [17, Lemma 3.5 and formula (3.17) in Theorem 3.7] are a consequence of [17, Lemmata 3.1 and 3.3].
Namely, [17, Lemmata 3.1] establishes the Lipschitz continuity of mG as in (5.9), with respect to the traces
and is stated under the sole positivity of G. It is easy to check that
an analogous result holds true for mGM as in (5.41).
Moreover, (5.42) is used in [17, Lemma 3.3]
to prove the equality G(u,A)=supδ>0mG,δ(u,A), where
[TABLE]
with μ:=Ln+∣Dsu∣.
Then to conclude we notice that the same identity holds true for mGM under the assumptions (1)-(4). In fact, one inequality is trivial, while the other
can be obtained by exhibiting a competitor with the same L∞ bound.
∎
By Lemma 4.2 and (5.47), given ρ>0, for every r large enough we have
[TABLE]
Therefore, recollecting (5.44), (5.2) and (5.2), for every ρ>0 we get the following
[TABLE]
where K~(M,ρ,η):=Kρ+KραC1−α(1+MC2)1−α(ghom(ζ,ν)+2η)1−α.
Given ε>0 and ρ>0, we define (u^ερ,v^ερ):Rn→RN+1 as follows
[TABLE]
with r=ερ. Thereby u^ερ∈Wloc1,1(Rn,RN) with ∥u^ερ∥L∞(Rn)≤a2M+1 and v^ερ∈Wloc1,2(Rn,[0,1]). Changing variables it is immediate to get
[TABLE]
where (εj)j∈N is the sequence in Theorem 5.2 along which the Γ-convergence of (Fε)ε>0 holds.
Moreover, we observe that
[TABLE]
Therefore, for every ρ, we have that
[TABLE]
From ∥u^εjρ∥L∞(Qρν(x))≤a2M+1 and [8, Lemma 7.1] there exists a subsequence (not relabeled)
of (εj)j∈N and uρ∈Lloc1(Rn,RN) such that (u^εjρ,v^εjρ)→(uρ,1) in Lloc1(Rn,RN+1), uρ∈BV(Qρ(1+η)ν(x),RN), uρ(y)=ux,ζ,ν(y) for Ln-a.e. y∈Rn∖Qρν(x). By assumption (ii) in Theorem 5.1 (cf. formula (5.5)), it follows that for every ρ
and thereby, letting M→+∞ and η→0, we can conclude.
Step 2: We claim that
[TABLE]
By Theorem 5.2 there exists (uj,vj)∈Lloc1(Rn,RN) with uj∈W1,1(A,RN) and vj∈W1,2(A,[0,1]), such that vj(x)→1 for Ln-a.e. x∈A as j→+∞,
[TABLE]
For Hn−1-a.e. x∈Ju∩A (cf. [9, Theorem 3.77 and Proposition 3.92]) we have
[TABLE]
[TABLE]
[TABLE]
Let us fix x∈Ju∩A such that (5.49)-(5.51) are satisfied,
and set ζ:=[u](x) and ν:=νu(x).
Using the lower bound inequality in the Γ-convergence of (Fε)ε>0 on Qρνu(x)(x) and
A∖Qρνu(x)(x), the super-additivity of the inferior limit operator implies that
j→+∞limFεj(uj,vj,Qρν(x))=F(u,1,Qρν(x))
for every ρ∈I(x):={ρ∈(0,n2dist(x,∂A)):F(u,1,∂Qρν(x))=0}.
Hence, we deduce that
[TABLE]
Now, we consider the rescalings (ujρ,vjρ),(uρ,vρ):Q1ν→RN+1 given by
[TABLE]
Then ujρ∈W1,1(Q1ν,RN), vjρ∈W1,2(Q1ν,[0,1]), uρ∈BV(Q1ν,RN), and
(ujρ,vjρ)→(uρ,1) in L1(Q1ν,RN+1),
uρ→uζ,ν in L1(Qν,RN) by (5.50),
and vjρ→1 in L2(Qν) for every ρ by(5.52).
Changing variables, formula (5.52) rewrites as
where K is a constant that depends only on C and α. Thanks to (5.51),
(5.53) and (5.54) we get
[TABLE]
where
[TABLE]
Now, for every ρ and j we consider the sequences (ajρ)j∈N,(bjρ)j∈N and (sjρ)j∈N given by
[TABLE]
where (wρ) is a sequence in W1,1(Q1ν,RN) such that wρ=uζ,ν on ∂Q1ν for every ρ,
[TABLE]
(see [17, Lemma 2.5]), where ⌊s⌋ denotes the integer part of s∈R.
Fix ρ small enough, such that ρ+∥uρ−wρ∥L1(Q1ν)21<41 and then fix j large enough such that 0<ajρ<21 and 2<bjρ. For every i=0,…,bjρ we define Qρ,j,iν as
[TABLE]
while for every i=1,..,bjρ we consider the cut-off function ϕj,iρ∈Cc∞(Qρ,j,iν) such that 0≤ϕj,iρ≤1, ϕj,iρ≡1 on Qρ,j,i−1ν and ∥∇ϕj,iρ∥L∞(Rn)≤2(sjρ)−1. Set for i=1,..,bjρ
[TABLE]
Then uj,iρ∈W1,1(Q1ν,RN), vj,iρ∈W1,2(Q1ν,[0,1]) with (uj,iρ,vj,iρ)=(uζ,ν,1) on ∂Q1ν.
Moreover, for every i=2,…,bjρ we have the following
[TABLE]
We estimate separately the terms appearing above. We start with
[TABLE]
Moreover, since
∇uj,iρ=ϕj,i−1ρ∇ujρ+(1−ϕj,i−1ρ)∇wρ+∇ϕj,i−1ρ⊗(ujρ−wρ),
we have that
[TABLE]
Analogously, we obtain
[TABLE]
Since ∇vj,iρ=ϕj,iρ∇vjρ+(vjρ−1)∇ϕj,iρ,
we have that
[TABLE]
In particular, thanks to the previous calculations and and recalling the definition of sjρ,
there exists ijρ∈{2,…,bjρ} such that
[TABLE]
Hence, by the definition of ajρ and bjρ in (5.56) we deduce that
[TABLE]
Thus, setting κρ=1−∥uρ−wρ∥L1(Q1ν), from (5.55) and (5.56) we obtain
[TABLE]
As wρ→uζ,ν strictly in BV (cf. (5.57)), we have that ∣Dwρ∣(Q1ν∖Qκρν)→0 as ρ→0, and thus
[TABLE]
By the change of variable and the 1-homogeneity of f∞ , we have
[TABLE]
where rρ,j:=εjρ, ujρ(y):=uj,ijρρ(rρ,jy−ρx) and vjρ(y):=vj,ijρρ(rρ,jy−ρx). In this way ujρ∈W1,1(Qrρ,jν(ρrρ,jx),RN), vjρ∈W1,2(Qrρ,jν(ρrρ,jx),[0,1]) with (ujρ,vjρ)=(uρrρ,jx,ζ,ν,1) on ∂Qrρ,jν(ρrρ,jx). In particular, by (5.58), the definition of msf∞ in (3.5) and the assumption (b) of Theorem 5.1 we obtain
[TABLE]
deducing the claim.
∎
5.3. Identification of the Cantor term
Eventually, in this subsection we identify the density of the Cantor part of the Γ-limit F.
Proposition 5.9** (Homogenised Cantor integrand).**
Let f∈F(C,α) satisfy (4.4). Let F be as in (5.5).
Then for every A∈A and every u∈Lloc1(Rn,RN), with u∈BV(A,RN)∩L∞(A,RN), we have that
[TABLE]
where fhom∞ is the recession function of fhom as in (4.1).
Proof.
Let us fix A∈A and u∈Lloc1(Rn,RN) with u∈BV∩L∞(A,RN). We divide the proof into two steps.
Step 1: We claim that
[TABLE]
By Alberti’s Rank-one Theorem [3] we know that for ∣Dcu∣-a.e. x∈A we have
[TABLE]
where (a(x),ν(x))∈RN×Sn−1. By Theorem 5.2 and by [17, Lemma 3.9] we have that for ∣Dcu∣-a.e. x∈A there exists a doubly indexed positive sequence (tρ,k), with ρ∈(0,∞) and k∈N, such that for every k∈N
[TABLE]
and for every q∈Q∩(0,1)
[TABLE]
where for every A∈A and q∈Q∩(0,1) let Fq(u,1,A):=F(u,1,A)+q∣Du∣(A), and Qrν,k(z) is the parallelepiped defined in (f) of the notation list.
Let x∈A be such that (5.59)-(5.61) hold true, and set a:=a(x) and ν:=ν(x).
Thanks to Proposition 4.3, for every ρ>0 and every k∈N we have
[TABLE]
Let us fix η∈(0,1). By the very definition of mbf∞, for every k∈N, ρ∈(0,1) and r∈(0,∞)
there exists a function u^rρ,k∈W1,1(Qrν,k(ρrx),RN) with u^rρ,k=ℓa⊗ν on ∂Qrν,k(ρrx) such that
where K^ depends only on C, α and a. Collecting (5.62)-(5.64), we infer that
[TABLE]
For k∈N, ρ∈(0,1) and ε∈(0,∞) we define the function uερ,k:Rn→RN given by
[TABLE]
where r:=ερ. Thus uερ,k∈Wloc1,1(Rn,RN) with uερ,k=tρ,kℓa⊗ν on ∂Qρν,k(x) and changing variable we obtain
[TABLE]
since uερ,k coincides with tρ,kℓa⊗ν on Qρ(1+η)ν,k(x)∖Qρν,k(x). By (5.3) and Poincaré inequality, we can extract a subsequence (not relabelled) of (εj)j∈N, for every ρ∈(0,1) and k∈N, such that uεjρ,k→uρ,k in Lloc1(Rn,RN), where uρ,k∈BV(Qρ(1+η)ν,k(x),RN) with
uρ,k=tρ,kℓa⊗ν on Qρ(1+η)ν,k(x)∖Qρν,k(x). As a consequence of the Γ-convergence stated in Theorem 5.2, of the superadditivity of the inferior limit operator, of (f2) and of estimate (5.3) we obtain
[TABLE]
We can pass to the limit in the last inequality for ρ→0 and then for k→+∞, using (5.60)
and (5.61) we arrive to
[TABLE]
The claim follows by letting η and q→0.
Step 2: We claim that
[TABLE]
Let A′∈A(A), then by Theorem 5.2 we can find a sequence (uj,vj)j∈N∈Lloc1(Rn,RN+1) such that (uj,vj)∈W1,1(A′,RN)×W1,2(A′,[0,1]), (uj,vj)→(u,1) in Lloc1(Rn,RN+1), vj→1 for Ln-a.e. x∈A′ as j→∞ and
[TABLE]
Arguing as in Step 2 of the proof of Proposition 5.4 we may assume uj∈L∞(A′;RN).
Fix δ∈(0,1); by Lemma 5.6 we have
[TABLE]
where ujδ∈SBV(A′,RN) with ujδ→u in L1(A′,RN) as j→∞, and therefore
[TABLE]
Define on A′ the measures μjδ given by
[TABLE]
By definition of Hεδ and the compactness of Radon measures, there exists subsequence (not relabeled) of (εj)j∈N
and a finite Radon measure μδ on A′ such that μjδ→μδ weakly* in the sense of measures on A′ as j→∞.
For ∣Dcu∣-a.e. x∈A′ (cf. [9, Proposition 3.92 and Theorem 3.94]) there exists a(x)∈SN−1 and ν(x)∈Sn−1 such that for every k∈N we have
[TABLE]
[TABLE]
[TABLE]
[TABLE]
Fix now x0∈A′ such that (5.68)-(5.71) hold true and set a:=a(x0) and ν:=ν(x0). For k∈N and ρ set
[TABLE]
therefore
[TABLE]
and
[TABLE]
By the weak∗-convergence of (μεjδ)j∈N to μδ we infer that
[TABLE]
where I(x_{0}):=\{\rho\in(0,1):\,\mu^{\delta}(\partial Q^{\nu,k}_{\rho}(x_{0}))=0\text{ for every k\in\mathbb{N} s.t. }Q^{\nu,k}_{\rho}(x_{0})\subset\subset A^{\prime}\}.
Note that I(x0) has full measure in (0,1).
Fix k∈N and consider the rescaled functions ujρ,k,uρ,k:Qν,k→RN
[TABLE]
From now on we work at k∈N fixed and this will tend to ∞ only at the very end of the proof. Therefore, for those parameters infinitesimal
as j→∞ and ρ→0 the possible dependence on k will not be highlighted.
For every ρ small enough, depending on k, ujρ,k∈SBV(Q1ν,k,RN), uρ,k∈BV(Q1ν,k,RN),
ujρ,k→uρ,k in L1(Q1ν,k,RN) as j→∞, and the function uρ,k satisfies the following
By [28, Lemma 4.5] (see also [36, Lemma 5.1]) there exists a subsequence (not relabeled), depending on k, such that
uρ,k→uk in L1(Q1ν,k,RN) as ρ→0, where uk∈BV(Q1ν,k,RN),
uk(y)=χk(y⋅ν)a for every y∈Q1ν,k,
χk:[−1/2,1/2]→R is a nondecreasing function such that Dχk((−1/2,1/2))=χk(1/2)−χk(−1/2)=kn−11, −kn−11≤χk(−1/2)≤0≤χk(1/2)≤kn−11, and
[TABLE]
Furthermore, being χk continuous in −1/2 and 1/2, thanks to the trace’s properties of BV functions, we have that the inner trace of uk satisfies uk=ℓk on ∂⊥Q1ν,k (cf. (f) of the notation list) where
[TABLE]
To obtain a uniform L∞-bound on the scaled sequence, we let M∈N and use Lemma 5.3 with v≡1 to get
for every k∈N, every ρ small enough and every j (up to a subsequence), mρ∈{M+1,…,2M} such that
[TABLE]
where the γ-term in Lemma 5.3 disappears because ujρ,k→uk in L1(Q1ν,k;RN) and uk∈L∞. Furthermore
[TABLE]
where u^jρ,k:=Tmρ(ujρ,k)∈SBV(Q1ν,k,RN). Therefore, choosing M such that aM>∣a∣,
it follows from (5.72) and (5.3) that
[TABLE]
Next we change the boundary datum u^jρ,k on a neighborhood of ∂⊥Qν,k with uk.
For every ρ small enough and every j large enough (depending on ρ), we have that
[TABLE]
and thanks to Fubini’s Theorem and the trace properties of BV functions on rectifiable sets, there exists qρ,j∈(1/2−τρ,j1/2,1/2)
[TABLE]
where (u^jρ,k)− is the inner trace of u^jρ,k on Rν(Bρ,jk), where
Bρ,jk:=(−2k,2k)n−1×(−qρ,j,qρ,j) and Rν is the rotation in (e) of the notation list.
Defining the functions wjρ,k∈BV(Q1ν,k,RN) as
[TABLE]
we have that
[TABLE]
Since ρ→0limj→∞limLn(Q1ν,k∖Rν(Bρ,jk))=0,
we get from (5.75)
In addition, thanks to Lemma 4.2 and (5.78) we deduce that
[TABLE]
We now change the boundary datum wjρ,k on a neighborhood of ∂∥Q1ν,k with ℓk.
Let hk∈(0,k) be such that Ln(Q1ν,k∖Q1ν,hk)→0 as k→∞, necessarily hk→∞.
Then, by Fubini’s Theorem there exists λρ,jk∈(k−hk,k) such that
[TABLE]
where (wjρ,k)− is the inner trace of wjρ,k on ∂∥Q1ν,λρ,jk. Furthermore, since wjρ,k=uk=ℓk
on ∂⊥Q1ν,k, using Poincarè inequality on the one-dimensional restrictions of wjρ,k in the ν direction, we obtain that
We now argue as in Proposition 5.4 (cf. (5.37), (5.38)), and for every ρ and j fixed we use Lemma 5.5 to infer the existence of wjρ,k∈W1,1(Q1ν,k,RN) such that
wjρ,k=ℓk on ∂Q1ν,k and
[TABLE]
Therefore, by (5.79), (5.84), (5.3)
we conclude from the last inequality above that
[TABLE]
Set rρ,j:=εjρ and w~jρ,k(x):=rρ,jwjρ,k(rρ,jx−ρx0),
we have that w~jρ,k∈W1,1(Qrρ,jν,k(ρrρ,jx0),RN) with w~jρ,k=ℓk−εjx0 on ∂Qrρ,j(ρrρ,jx0) and, thanks to the 1-homogeneity of f∞ (cf. item (i) in
Lemma 5.5), we infer that
[TABLE]
In particular, since kn−1w~jρ,k=ℓa⊗ν−εjkn−1x0 on ∂Qrρ,jν,k(ρrρ,jx0), thanks to (5.3) we obtain
[TABLE]
where the last-but-one equality follows from Lemma 5.5 (vi), and
the last equality follows from Proposition 4.3.
Then, taking k→∞ and M→∞ in this order, we infer that
Theorem 5.2 implies that from any strictly positive infinitesimal sequence we can extract a subsequence (εj) such that
[TABLE]
with F:Lloc1(Rn,RN+1)×A⟶[0,+∞]. Moreover,
F(u,1,⋅) is the restriction to open sets of a finite Radon measure on A and F(u,1,A)≤C(∣Du∣(A)+Ln(A))
for every A∈A and every u∈Lloc1(Rn,RN) such that u∈BV(A,RN).
Therefore, F(u,1,⋅) is absolutely continuous respect to the measure Ln\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptA+∣Dcu∣\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptA+Hn−1\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptJu∩A.
Since Ln\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptA,∣Dcu∣\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptA,Hn−1\vruleheight=7.0pt,width=0.5pt,depth=0.0pt\vruleheight=0.5pt,width=6.0pt,depth=0.0ptJu∩A are mutually singular,
by the properties of Radon-Nikodym derivatives, for every B∈A(A) we have that
[TABLE]
In particular, if A∈A and u∈Lloc1(Rn,RN) with u∈BV(A,RN)∩L∞(A,RN),
Propositions 5.4, 5.7 and 5.9 give that
[TABLE]
where Fhom is as in (5.4).
From (f2), for every A∈A and every (u,v)∈Lloc1(Rn,RN+1) with (u,v)∈W1,1(A,RN)×W1,2(A,[0,1]) we have that
[TABLE]
hence, by [7, Theorem 4.1] and [8, Remark 3.5],
for every (u,v)∈Lloc1(Rn,RN+1) such that u∈GBV(A,RN) or v=1 on A we get
[TABLE]
Eventually, arguing exactly as in [8, Section 6] we obtain
[TABLE]
for every A∈A and every u∈Lloc1(Rn,RN) such that u∈GBV(A,RN).
Indeed, the lower bound inequality for general GBV maps follows easily from Lemma 5.3 and
the result in the BV∩L∞-setting. Instead, the upper bound inequality is a consequence of the latter together
with both the Lloc1(Rn,RN+1) lower semicontinuity of Γ-limsupj→∞Fεj(⋅,1,A)
and the continuity of Fhom along sequences of maps obtained via the smooth truncations (Tk)k∈N,
namely Fhom(Tk(u),1,A)→Fhom(u,1,A) as k→∞ for every u∈GBV(A,RN) (cf. [8, Lemma 6.1]).
Since the Γ-limit does not depend on the extracted subsequence Urysohn’s property of Γ-convergence yields the claim.
∎
6. Stochastic homogenisation
This section is devoted to the proof of the stochastic homogenisation result stated in Theorem 3.4. The proof will be achieved by showing that if f is a stationary random integrand in the sense of Definition 2.7, then the assumptions of Theorem 5.1 are satisfied for P-a.e. ω∈Ω. Here a pivotal role is played by the Subadditive Ergodic Theorem, Theorem 2.3.
The following proposition establishes the existence and spatial homogeneity of fhom. The proof can be found in [24, Proposition 9.1] and in [42, Lemma 4.1].
Proposition 6.1** (Homogenized random volume integrand).**
Let f be a stationary random integrand. Then there exist Ω′∈T, with P(Ω′)=1 and a T⊗BN×n-measurable function fhom:Ω×RN×n→[0,+∞) such that for every ω∈Ω′, x∈Rn, ξ∈RN×n, ν∈Sn−1 and k∈N
[TABLE]
If in addition f is ergodic, then fhom is independent of ω and
[TABLE]
Propositions 4.3 and 6.1 readily imply the following result.
Proposition 6.2** (Homogenized random Cantor integrand).**
Let f be a stationary random integrand. Then there exist Ω′∈T, with P(Ω′)=1 and a T⊗BN×n-measurable function fhom∞:Ω×RN×n→[0,+∞) such that for every ω∈Ω′, every ξ∈RN×n every k∈N, every x∈Rn and every ν∈Sn−1
[TABLE]
and
[TABLE]
If in addition f is ergodic, then fhom∞ is independent of ω and
[TABLE]
The analogous result for the surface integrand is more involved and requires a new proof.
Proposition 6.3** (Homogenized random surface integrand).**
Let f be a stationary random integrand. Then there exist Ω′∈T, with P(Ω′)=1 and a T⊗BN⊗BSn-measurable function ghom:Ω×RN×Sn−1→[0,+∞) such that for every ω∈Ω′, x∈Rn, ζ∈RN and ν∈Sn−1
[TABLE]
If in addition f is ergodic, then ghom is independent of ω and
[TABLE]
Proof.
We divide the proof into a number of steps.
Step 1: Let uζ,ν be as in (l) of the notation list. In this step we prove that for every ζ∈QN and ν∈Sn−1∩Qn and for P-a.e. ω∈Ω there exists the limit
[TABLE]
and defines an x-independent random variable.
To prove the claim let ν∈Sn−1∩Qn and ζ∈QN be fixed, Rν∈O(n)∩Qn×n be the orthogonal matrix as in (e) of the notation list, and Mν be a positive integer such that MνRν∈Zn×n, so that MνRν(z′,0)∈Π0ν∩Zn. Given A′=[a1,b1)×⋯×[an−1,bn−1)∈In−1 we define the n-dimensional interval Tν(A′) as
[TABLE]
For every ω∈Ω and every A′∈In−1 we set
[TABLE]
We now show that μζ,ν:Ω×In−1→[0,+∞) defines an (n−1)-dimensional subadditive process on (Ω,T,P). The separability and completeness of W1,1(A,RN)×W1,2(A,[0,1]) for every A∈A combined with [41, Lemma C.2] and (f2) in Definition 2.4 give the T-measurability of the map ω↦msfω∞(uζ,ν,Tν(A′)) for every A′∈In−1.
Next, we prove that μζ,ν is stationary with respect to an (n−1)-dimensional group of P-preserving transformations (τz′ν)z′∈Zn−1.
To this end, fix z′∈Zn−1 and A′∈In−1. By (6.3) we have that
[TABLE]
where zν′:=MνRν(z′,0)∈Πν∩Zn. Thus by (6.4) we get
[TABLE]
Now let u,v be test functions in the definition of msfω∞(uζ,ν,Tν(A′)+zν′) and for x∈Tν(A′) set
[TABLE]
Then, a change of variables together with the stationarity of f yield
[TABLE]
Set (τz′ν)z′∈Zn−1:=(τzν′)z′∈Zn−1; we notice that
(τz′ν)z′∈Zn−1 is well defined since zν′∈Zn and it defines a group of P-preserving transformations on (Ω,P,T). Then, the equality above can be rewritten as
[TABLE]
Moreover, since zν′∈Πν∩Zn we also have that u~=uˉζ,ν on ∂Tν(A′). Thus gathering (6.5) and (6.6), by the arbitrariness of u~,v~ we infer
[TABLE]
and hence the stationarity of μζ,ν with respect to (τz′ν)z′∈Zn−1.
To show that μζ,ν is subadditive in In−1, fix ω∈Ω
and A′∈In−1 and let (Ai′)1≤i≤M⊂In−1 be a finite family of pairwise disjoint sets such that A′=∪i=1MAi′.
For every η>0 and i∈{1,…,M}, let (ui,vi)∈W1,1(Tν(Ai′),RN)×W1,2(Tν(Ai′),[0,1]) with (ui,vi)=(uζ,ν,1) on ∂Tν(Ai′) such that
[TABLE]
Note that by construction we always have ∪i=1MTν(Ai′)⊆Tν(A′), thus we define
[TABLE]
In particular, (u,v)∈W1,1(Tν(A′),RN)×W1,2(Tν(A′),[0,1]) with (u,v)=(uζ,ν,1) on ∂Tν(A′).
Hence, we get
[TABLE]
and the subadditivity follows by the arbitrariness of η>0.
Finally, we show that μζ,ν is bounded. To this end we observe that for every A′∈In−1 and every ω∈Ω we have
[TABLE]
where we used Tν(A′)∩Πν=MνRν(A′×{0}) and {∣∇(uζ,ν(y)∣>0}⊆{∣y⋅ν∣≤1/2}. Therefore, for every ζ∈QN and ν∈Sn−1∩Qn, μζ,ν defines a subadditive process.
Then, we can apply Theorem 2.3 to deduce the existence of a T-measurable function ψν,ζ:Ω→[0,+∞), and a set Ωζ,ν∈T with P(Ωζ,ν)=1, such that
for every ω∈Ωζ,ν
[TABLE]
where Qr′:=Qr∩{xn=0}, with r>0, is a (n−1)-regular family of sets (cf. Definition 2.2).
Step 2: In this step we prove the existence of Ω~∈T with P(Ω~)=1 such that for every ω∈Ω~ and for every ζ∈RN and ν∈Sn−1 the following limit exists
[TABLE]
and defines an x-independent T⊗BN⊗BSn-measurable function.
To prove the claim let Ω~ denote the intersection of the sets Ωζ,ν, as in Step 1, for ζ∈QN and ν∈Sn−1∩Qn.
Clearly, Ω~∈T and P(Ω~)=1. Let g,g:Ω~×RN×Sn−1→[0,+∞] be the functions given by
[TABLE]
By Step 1, for every ω∈Ω~, every ζ∈QN and every ν∈Sn−1∩Qn we have that
[TABLE]
Furthermore, fixed ω∈Ω~ and ν∈Sn−1, arguing as in Proposition 4.7 (i) we have
[TABLE]
for every ζ1,ζ2∈RN.
From (6.7) and (6.8) we deduce that for every ω∈Ω~, every ζ∈RN and every ν∈Sn−1∩Qn
[TABLE]
and that g(⋅,ζ,ν):Ω~→[0,+∞) is T-measurable for every ζ∈RN and every ν∈Sn−1∩Qn.
We now claim that for every ω∈Ω~ and every ζ∈RN, the restrictions of the functions ν↦g(ω,ζ,ν) and ν↦g(ω,ζ,ν) to the sets S^±n−1 are continuous. We show only the continuity of g on S^+n−1, the proof for g is analogous. To this end, let ω∈Ω~, ζ∈RN, ν∈S^+n−1, then by density
let (νj)j∈N⊂S^+n−1∩Qn be such that νj→ν as j→+∞. By the continuity of ν↦Rν on S^+n−1, for every δ∈(0,1/2) there exists a jδ∈N such that
[TABLE]
for every j≥jδ and every r>0.
Setting κj:=max{∣Rνj(ei)⋅ν∣:i=1,…,n−1} we have that κj→0 as j→+∞, thanks to the continuity of ν↦Rν on S^±n−1. We observe that for every y∈Qr(1+δ)ν, we have y=y′+(y⋅νj)νj where
[TABLE]
and in particular, if in addition ∣y⋅ν∣≤21, for j large enough depending only on δ, we get
[TABLE]
where K(δ):=2(1−δ)(n−1)(1+δ). Then, by applying Lemma 4.6, with R=K(δ)rκj+1, we obtain
[TABLE]
Therefore, dividing by rn−1, passing to the liminf as r→+∞, and to the limsup as j→+∞, and finally
letting η,δ→0 we obtain
[TABLE]
An analogous argument using the cubes Q(1−δ)rνj shows that
[TABLE]
implying the claim.
In particular, thanks to (6.9) we deduce that for every ω∈Ω~, ζ∈RN and ν∈Sn−1
[TABLE]
The T-measurability of g(⋅,ζ,ν):Ω~→[0,+∞) for every ζ∈RN and ν∈Sn−1
follows from the analogous property for ν∈Sn−1∩Qn. Furthermore, the map
g(ω,⋅,⋅):RN×S^±n−1→[0,+∞) is continuous for every ω∈Ω~ thanks to
(6.8).
Thus, defining ghom:Ω×RN×Sn−1→[0,+∞) by
[TABLE]
we have that ghom is T⊗BN⊗BSn-measurable and, thanks to Corollary 4.5,
[TABLE]
for every ω∈Ω~, every ζ∈RN and every ν∈Sn−1.
Step 3: In this step we show the existence of Ω′∈T with Ω′⊆Ω~ and P(Ω′)=1, such that for every ω∈Ω′,
z∈Zn, ζ∈QN, ν∈Sn−1∩Qn, and for every integer sequence (rk) with rk≥k for every k
[TABLE]
Let z∈Zn, ζ∈QN, ν∈Sn−1∩Qn, η>0 and δ∈(0,1/4). Arguing exactly as in [22, Theorem 6.1] we can prove the existence of a set Ωzζ,ν,η∈T, with Ωzζ,ν,η⊆Ω~, P(Ωzζ,ν,η)=1, and an integer m0=m0(ζ,ν,η,z,ω,δ)>δ1 satisfying the following property: for every ω∈Ωzζ,ν,η and for every integer m≥m0 there exists i=i(ζ,ν,η,z,ω,δ,m)∈{m+1,…,m+ℓ}, with ℓ:=⌊5mδ⌋, such that
[TABLE]
where j0=j0(ζ,ν,η,z,ω,δ), and ⌊s⌋ denotes the integer part of s∈R.
Define Ω′ as the intersection of the sets Ωzζ,ν,η for ζ∈QN, ν∈Sn−1∩Qn, η∈Q, with η>0 and z∈Zn. Thus Ω′⊆Ω~ and P(Ω′)=1. Let ω∈Ω′ and rk be as required, δ>0 with 20δ(∣z∣+1)<1 and η∈Q with η>0. For every k≥2m0(ζ,ν,η,z,ω,δ), let rk,rk∈N be defined as
[TABLE]
where
[TABLE]
therefore, by construction, we have that Qrkν(−ikz)⊂⊂Qrkν(−kz)⊂⊂Qrkν(−ikz).
Since 20δ(∣z∣+1)<1, k≤rk and ik−k≤5kδ by (6.15), for every y∈Qrkν(−ikz) such that ∣(y+ikz)⋅ν∣≤21, we obtain that
[TABLE]
and rk−rk=2(ik−k)⌊∣z∣+1⌋≤10kδ⌊∣z∣+1⌋≤10rkδ⌊∣z∣+1⌋<2rk. Applying Lemma 4.6, with R=5rkδ∣z∣+21, we obtain
[TABLE]
In particular, from the latter estimate, (6.14) and rk≤rk, for every k large enough such that rk≥j0(ζ,ν,η,z,ω,δ), we obtain
[TABLE]
and thus, taking the limsup for k→+∞ and letting η,δ→0, we get
[TABLE]
Arguing analogously with the external cubes Qrkν(−ikz) we get
[TABLE]
obtaining the claim.
Step 4: Let Ω′ be the set introduced in Step 3, then for every ω∈Ω′, x∈Rn, ζ∈QN
and ν∈Sn−1∩Qn there holds
[TABLE]
Fix ω,x,ζ,ν as required, η∈(0,21), q∈Qn with ∣x−q∣<η, and h∈Z such that z:=hq∈Zn. Consider a sequence of real numbers tk→+∞ as k→+∞ and let sk:=htk. Fixing an integer j>2∣z∣+1 and setting rk:=⌊tk+2ηtk⌋+j we have that
Qtkν(tkx)⊂⊂Qrkν(⌊sk⌋z). Since ∣(tkx−⌊sk⌋z)⋅ν∣≤∣tkx−tkq∣+∣skz−⌊sk⌋z∣≤tkη+∣z∣, for every y∈Qrkν(⌊sk⌋z) such that ∣(y−tkx)⋅ν∣≤21 we have that ∣(y−⌊sk⌋z)⋅ν∣≤tkη+∣z∣+21.
In particular, for k large enough depending only on z, we can apply Lemma 4.6, with R=tkη+∣z∣+21, to obtain
[TABLE]
where we used rk≥tk. From (6),
dividing by tkn−1 and recalling that rk≥tk≥sk≥⌊sk⌋, we obtain that
[TABLE]
Since ω∈Ω′ and rk≥⌊sk⌋, we can apply (6.13), taking the liminf as k→∞ and letting η→0 we obtain
[TABLE]
Arguing analogously we obtain
[TABLE]
deducing the claim, thanks to the generality of the sequence (tk)k∈N.
Step 5: Let Ω′ be the set introduced in Step 3, then for every ω∈Ω′, x∈Rn, ζ∈RN,
and ν∈Sn−1
[TABLE]
For ω,x,ζ,ν as above define
[TABLE]
Arguing exactly as in Proposition 4.7 (i) and in Step 2, we obtain from Step 4 that
[TABLE]
for every ω∈Ω′, x∈Rn, ζ∈RN, and ν∈Sn−1∩Qn.
Now let ω∈Ω′, x∈Rn, ζ∈RN and ν∈S^+n−1, by density there is (νj)j∈N in S^+n−1∩Qn
such that νj→ν as j→+∞. Thanks to the continuity on S^+n−1 of the map ν↦Rν, for every δ∈(0,21)
there exists jδ, such that
[TABLE]
for every j≥jδ and every r>0. Let us fix j≥jδ, r>0 and η>0. Setting cj:=max{∣Rνj(ei)⋅ν∣:i=1,…,n−1} we have that cj→0 as j→+∞, by continuity of ν↦Rν on S^±n−1, and recalling that Rν∈O(n) and Rνen=ν (cf. (e) of the notation list).
For every y∈Qr(1+δ)ν(rx) we have that y−rx=y′+((y−rx)⋅νj)νj where
[TABLE]
with, if j is large enough depending only on δ,
[TABLE]
where K(δ):=2(1−δ)(n−1)(1+δ), if in addition ∣(y−rx)⋅ν∣≤21.
Therefore, we can apply Lemma 4.6, with R=K(δ)rcj+1, and we get
[TABLE]
Dividing by rn−1 and letting r→+∞, we obtain
[TABLE]
Hence, we may use (6.18) as νj∈Sn−1∩Qn and deduce
by taking the superior limit as j→+∞ and letting η→0 in the latter estimate
[TABLE]
Therefore, by the continuity of ghom established in Step 2, letting δ→0 we obtain
[TABLE]
Arguing analogously we have g(ω,x,ζ,ν)≤ghom(ω,ζ,ν),
and recalling Corollary 4.5 we conclude.
Step 5: In this step we show that if f is ergodic then ghom is deterministic.
Set Ω^=⋂z∈Znτz(Ω~); we clearly have that Ω^∈T, Ω^⊆Ω~ and τz(Ω^)=Ω^ for every z∈Zn. Moreover, since τz is a P-preserving transformation and P(Ω~)=1, we have that P(Ω^)=1. We claim that
[TABLE]
for every ω∈Ω^, every ζ∈RN and every ν∈Sn−1. Fix z∈Zn, ω∈Ω^ and ν∈Sn−1. For every r>3∣z∣, let (ur,vr)∈W1,1(Qrν,RN)×W1,2(Qrν,[0,1]), with (ur,vr)=(uζ,ν,1) on ∂Qrν such that
[TABLE]
By the stationarity of f (and hence of f∞) we infer that
[TABLE]
Observe that Qrν⊂⊂Qr+3∣z∣ν(z) for every r>3∣z∣, and for every y∈Qr+3∣z∣ν(z) such that ∣y⋅ν∣≤21 we have that
[TABLE]
Then we can apply Lemma 4.6, with R=1, and for every η>0 we obtain
[TABLE]
Therefore, by definition of ghom, Ω^⊆Ω~, and (6.22) we obtain
[TABLE]
thus deducing the claim.
By (6.20) and the properties of (τz)z∈Zn, we clearly infer that
[TABLE]
and hence, using the same argument as in [22, Corollary 6.3], if (τz)z∈Zn is ergodic we deduce that ghom does not depend on ω and thus is deterministic. To conclude, we just observe that the representation of ghom(ζ,ν) as in (6.2)
is a direct consequence of (6.12), and the Dominated Convergence theorem (cf. (4.16)).
∎
Finally, we are in aposition to prove the main result of this paper, Theorem 3.4.
The proof readily follwos by combining Theorem 5.1, Proposition 6.1, 6.2, and 6.3.
∎
Acknowledgements
F. Colasanto wishes to thank the excellence cluster “Mathematics Münster: Dynamics–Geometry–Structure” for the financial support, moreover he thanks the hospitality of the Institute for Applied Mathematics of the University of Münster where this work was initiated.
C. I. Zeppieri was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy EXC 2044 -390685587, Mathematics Münster: Dynamics–Geometry–Structure.
F. Colasanto and M. Focardi have been supported by the European Union - Next Generation EU, Mission 4 Component 1 CUP B53D2300930006, codice
2022J4FYNJ, PRIN2022 project “Variational methods for stationary and evolution problems with singularities and interfaces”.
F. Colasanto and M. Focardi are members of GNAMPA - INdAM.
The authors would like to thank the referee for a careful and thorough reading of the manuscript, as well as for their constructive comments and suggestions, which have helped to improve the presentation of the paper.
Bibliography49
The reference list from the paper itself. Each links out to its DOI / PubMed record.
1[1] Y. Abddaimi, G. Michaille, and C. Licht (1997) Stochastic homogenization for an integral functional of a quasiconvex function with linear growth . Asymptotic Analysis 15 ( 2 ), pp. 183–202 . Cited by: §1 .
2[2] M. Akcoglu and U. Krengel (1981) Ergodic theorems for superadditive processes . J. Reine Angew. Math. 323 , pp. 53–67 . External Links: ISSN 0075-4102,1435-5345 , Document , Link , Math Review (Yves Derriennic) Cited by: §1.2 , §2.2 . · doi ↗
3[3] G. Alberti (1993) Rank one property for derivatives of functions with bounded variation . Proc. Roy. Soc. Edinburgh Sect. A 123 ( 2 ), pp. 239–274 . External Links: ISSN 0308-2105,1473-7124 , Document , Link , Math Review (W. P. Ziemer) Cited by: §5.3 . · doi ↗
4[4] R. Alessi, F. Colasanto, and M. Focardi (2025) Phase-field modelling of cohesive fracture. Part I: Γ \Gamma -convergence results . preprint . Cited by: §1 , §1 .
5[5] R. Alessi, F. Colasanto, and M. Focardi (2025) Phase-field modelling of cohesive fracture. Part II: reconstruction of the cohesive law . preprint . Cited by: §1 .
6[6] R. Alessi, F. Colasanto, and M. Focardi (2025) Phase-field modelling of cohesive fracture. Part III: from mathematical results to engineering applications . preprint . Cited by: §1 .
7[7] R. Alicandro, A. Braides, and J. Shah (1999) Free-discontinuity problems via functionals involving the L 1 L^{1} -norm of the gradient and their approximations . Interfaces Free Bound. 1 ( 1 ), pp. 17–37 . External Links: ISSN 1463-9963 , Document , Link , Math Review (Gunther H. Peichl) Cited by: §1 , §1 , §1 , Remark 3.2 , §5.3 . · doi ↗
8[8] R. Alicandro and M. Focardi (2002) Variational approximation of free-discontinuity energies with linear growth . Commun. Contemp. Math. 4 ( 4 ), pp. 685–723 . External Links: ISSN 0219-1997 , Document , Link , Math Review (U. D’Ambrosio) Cited by: §1 , §1 , §1 , Remark 3.2 , Remark 3.2 , §4 , §4 , §5 , §5 , §5.2 , §5.3 , §5.3 , §5.3 , §5 . · doi ↗