Existence and rigidity of the vectorial Peierls-Nabarro model for dislocations in high dimensions
Abstract.
We focus on the existence and rigidity problems of the vectorial Peierls-Nabarro (PN) model for dislocations. Under the assumption that the misfit potential on the slip plane only depends on the shear displacement along the Burgers vector, a reduced non-local scalar Ginzburg-Landau equation with an anisotropic positive (if Poisson ratio belongs to ) singular kernel is derived on the slip plane. We first prove that minimizers of the PN energy for this reduced scalar problem exist. Starting from regularity, we prove that these minimizers are smooth 1D profiles only depending on the shear direction, monotonically and uniformly converge to two stable states at far fields in the direction of the Burgers vector. Then a De Giorgi-type conjecture of single-variable symmetry for both minimizers and layer solutions is established. As a direct corollary, minimizers and layer solutions are unique up to translations. The proof of this De Giorgi-type conjecture relies on a delicate spectral analysis which is especially powerful for nonlocal pseudo-differential operators with strong maximal principle. All these results hold in any dimension since we work on the domain periodic in the transverse directions of the slip plane. The physical interpretation of this rigidity result is that the equilibrium dislocation on the slip plane only admits shear displacements and is a strictly monotonic 1D profile provided exclusive dependence of the misfit potential on the shear displacement.
Key words and phrases:
fractional Laplacian, De Giorgi conjecture, stable entire solution, anisotropic nonlocal operator, spectral analysis, energy rearrangement, Peierls-Nabarro model, plastic deformation2010 Mathematics Subject Classification:
35A02, 35Q74, 35S15, 35J501. Introduction and main results
In materials science, the Peierls-Nabarro (PN) model with Poisson ratio plays a fundamental role in describing dislocations or line defects in materials [6, 27]. Understanding this model provides insights on designing new materials with robust performance [24, 21, 8, 16]. However, the existence and rigidity problem regarding the vector-field PN model has not been explored.
The PN model is a nonlinear model that studies the core structure of the dislocation by incorporating the atomistic effect in the dislocation core into the continuum elastic model. In the PN model in three dimensions, two half-spaces separated by the slip plane of a dislocation are assumed to be linear elastic continua. Here the slip plane is assumed to be a fixed plane , where the horizontal displacement discontinuity (known as disregistry) happens. Without loss of generality, we assume that the Burgers vector is where . The magnitude of the Burgers vector represents the typical length to observe a heavily distorted region in the dislocation core. Hence it is natural to rescale all the quantities including spatial variable , the displacement vector and with respect to the magnitude of the Burgers vector. After rescaling, we regard all these quantities (with same notations) as dimensionless quantities and .
In this paper, the shear direction is referred to as the direction of the Burgers vector, i.e. the direction; the vertical direction of the slip plane is referred to as the direction and the transverse direction in the slip plane is referred to as the direction.
The PN model is a minimization problem for the total energy which is given by
(1.1) |
Here is the displacement vector. (1.1) incorporates not only the elastic energy in the bulk but also the atomistic effect in the dislocation core. The elastic energy in the two half-spaces is defined as
(1.2) |
where . Here and are the strain tensor and the stress tensor respectively, defined as
(1.3) |
Here is the Poisson ratio and is the shear modulus.
On the slip plane, we denote the upper limit and lower limit of the displacement as
(1.4) |
Moreover, we assume that are subject to the following boundary conditions at the slip plane:
(1.5) |
We call (1.5) the symmetric assumption. Characterizing the nonlinear atomistic interactions, the misfit energy is defined as the integral of the misfit potential on the slip plane:
(1.6) |
The last equality is due to the symmetric assumption (1.5). Notice, is already dimensionless quantity so is well-defined. For brevity, we will omit factor 2 in (1.6) before and which makes no difference in the conclusions.
In this paper, to characterize the key property imposed by the Burgers vector, i.e., the direction of the dislocation and existence of two stable states, we assume that depends only on the shear displacement in the Burgers direction, i.e.,
(1.7) |
where the misfit potential is a double-well type potential, i.e. is a function satisfying
(1.8) |
We remark that this assumption on the misfit potential also includes some other typical periodic potentials which satisfy and represent the periodic lattice structure of crystalline materials; see in an explicit example (1.16).
Because the magnitude of the rescaled Burgers vector is order , for convenience, we take as bi-states at far fields, i.e.,
(1.9) |
which equivalent to the magnitude of the dislocation is assumed to be .
In this bi-states case (1.9), the total energy in (1.1) in the whole space is always infinite. Therefore, we consider the global minimizer in the following perturbed sense. However we remark that for a dislocation loop, i.e., a disregistry with compact support instead of the bi-states far field condition, energy in (1.1) is finite.
Definition 1.
The problem of existence and rigidity for the PN model interests us the most:
- (i)
-
(ii)
Do minimizers in (i) and layer solutions (see Definition 3) have 1D symmetry on the slip plane, i.e. are only depending on the shear direction, but independent with the transverse direction?
The answers to these two questions are both positive. To provide explicit and complete answers to these two questions, we consider the resulting Euler-Lagrange equation satisfied by the minimizer, which is a Lamé system with nonlinear boundary conditions on the slip plane (see (1.13)). Because we assume (1.7), i.e., the misfit potential depends only on the shear displacement , this Euler-Lagrange equation is reduced to a nonlocal semi-linear scalar equation on the slip plane with an elliptic pseudo-differential operator of order (see (1.15)). In particular, when , the pseudo-differential operator can be described in the singular kernel formulation; see Assumptions (A)-(D).
After these simplifications and reformulation, we only need to focus on the existence and rigidity of this reduced scalar nonlocal equation (see (1.23)). This equation is the Euler-Lagrange equation of a reduced energy function on the slip plane (see (1.37)). We will first prove that minimizers of energy functional (see (1.37)) in set (1.35) exist by constructing a minimizing sequence in which each function is an perturbation of a given 1D profile; see Theorem 1. Although starting from this weak regularity, we finally prove that these minimizers are smooth 1D profiles that monotonically and uniformly converge to stable states of the misfit functional in the shear direction, i.e., they converge to as .
After proving Theorem 1, we also establish a rigidity result of De Giorgi-type conjecture on 1D symmetry for all minimizers in set (1.35), and more generally for all layer solutions (see Definition 3). As a corollary, the uniqueness of these minimizers, as well as layer solutions, is also demonstrated; see Theorem 2 and Theorem 3. The existence and rigidity results are also stated for the original vectorial PN model (1.13) in Theorem 4.
Our results on both existence and rigidity hold in any dimension due to the periodic assumption: we are interested in solutions that are periodic in transverse directions. This dimension-independent rigidity is also observed in other equations if the domain is armed with periodicity [22].
In terms of materials science, our results provide a compatible physical interpretation. For Poisson ratio , if the misfit potential depends only on the shear displacement, then the equilibrium dislocation profile only admits shear displacements on the slip plane. Furthermore, this uniquely (up to translations) determined shear displacement is a strictly monotonic 1D profile connecting two stable states. In view of this rigidity result, the vectorial PN model (1.13) in three dimensions is reduced to a two-dimensional problem which was thoroughly investigated in our previous work [19].
In the remaining parts of the introduction, we will introduce the vectorial PN model and its reduced scalar equation (see (1.15)) in Section 1.1. From the reduced scalar equation, in Section 1.3, we introduce the nonlocal high-dimensional equation (see (1.23)) which contains the PN model as a special case. Finally, in this general context, we will present our main results and strategies in Section 1.4 to provide a rigorous and complete answer to the main questions (i) and (ii).
1.1. The vectorial Peierls-Nabarro model and its reduced scalar equation
Denote the unit torus as . Instead of minimizing the total energy (1.1) on , we consider the model on . Correspondingly, the slip plane is replaced by which is defined as
(1.12) |
A standard calculation of the first variation of the total energy (1.1) derives the following Euler–Lagrange equation satisfied by minimizers of (1.1) in the sense of Definition 1. The proof of this lemma can be found in Appendix B or our previous work [19].
Lemma 1.1.
Remark 1.
We can view (1.13), especially the second and the fourth equations as an incorporation of the linear response theory. Moreover, they are coupled equations of and . Notice that taking trace in (1.3), on . (i) Regard the elastic bulks as an environment and the slip plane as an open system. (ii) Given a Dirichlet disregistry boundary condition , by solving in the environment, one can obtain the trace on . (iii) We call this operator the Dirichlet to Neumann map; also known as a nonlocal linear response operator. As a consequence, this enables us to consider a nonlocal semi-linear elliptic system on ; see Section 2 on the kernel representation of this Dirichlet to Neumann map.
For the special case in (1.7), where only depends on the shear displacement , we can simplify and decouple the system (1.13) into two independent equations and finally drive a reduced scalar equation of , i.e. (1.15). In details, one can employ the Dirichlet to Neumann map and the elastic extension introduced in [19] to reduce the problem from onto , i.e., to equations of on the split plane . Second, if further employing (1.7), one can derive a linear representation formula between and on the Fourier side, i.e.,
(1.14) |
Here are the Fourier transform of with frequency vector . Substituting (1.14) into system (1.13), an independent equation of is derived, which contains a pseudo-differential operator defined on :
(1.15) |
The derivation of (1.15) is standard and can be found in Section 2. Therefore, as long as we can solve the non-local semi-linear equation of , i.e. the first equation in (1.15), we can also find by (1.14), and then derive the solution of the original system (1.13). For brevity, we will omit the superscript ’’ in the following sections. We call (1.15) the reduced scalar equation.
To solve (1.15), a meaningful observation is that we can write down an explicit solution to it for certain double-well potential ’s. Highly compatible with dislocations in Halite, the cosine potential in the PN model implements an explicit solution [6, 17] to (1.15) and (1.14):
(1.16) |
In particular, in (1.16) is a layer solution (see Definition 3) since it is strictly monotonic in direction and satisfies assumption (1.9). In fact, (1.16) is a good candidate for minimizers of total energy (1.1) in the sense of Definition 1. We will prove that this solution is the unique minimizer up to translations which concludes the question on existence and rigidity. We remark here that this is just a concrete example of our general result: for general double-well type potentials, we prove that minimizers of the total energy (see (1.37)) in function set (1.35) exist and they are layer solutions (see Definition 3). Moreover, they are unique up to translations.
1.2. Unsolved problems on the vectorial PN model
The existence and rigidity of the vectorial PN model are important in understanding dislocations. Previous literature on the vectorial PN model mainly focused on numerical simulations [40, 42, 28, 36] and physical experiments [42, 39], while only few rigorous mathematical results [19] were derived. In this section, we aim at mathematically formulating those important but unsolved problems into a framework and embedding our result into this macroscopic framework.
Consider the Euler-Lagrange equation of the vectorial model. We first observed that the second and fourth equations of (1.13) can be rewritten as
(1.17) |
where is a pseudo-differential operator with Fourier symbol . Equation (1.17) is a nonlocal reduced elliptic equations on slip plane , which is an open system. Meanwhile, the misfit potential here may depend on both and : . As far as we know, neither existence nor rigidity of (1.17) was studied by previous literatures.
In fact, if the misfit potential is carefully selected [42, 28, 36, 6], solutions of (1.17) determine the underlying structure of dislocations in crystals such as Cu () and Al (), no matter straight ones or curved ones. Considering symmetry of the crystal lattice, authors of [40] adopted a truncated Fourier expansion for the generalized stacking fault energy (see eq.(14) in [40]) as the misfit energy , with different coefficients for Cu and Al.
Numerical simulations in [40] indicated that straight edge dislocations in both Cu (figure 4 in [40]) and Al (figure 5 in [40]) possess the following structure: the displacement in the shear direction (i.e. ) is a layer solution (see Definition 2) and the displacement in the transverse direction (i.e. ) is a solitary wave. As claimed by authors in [40], this numerical result agrees with data from experiments on real materials [39].
To understand this consistency between the numerical result and the experimental data, we consider (1.17) where the Poisson ratio , which is exactly the case for cork. This special case is less obscure since equations for and are decoupled now. Furthermore, we assume that the misfit potential consists of two parts which depend merely on and respectively:
(1.18) |
Suppose that is a double-well potential (see (1.8)) and is the nonlinear potential in the Benjamin-Ono equation [7], i.e.
(1.19) |
If is a minimizer of (1.1) with boundary conditions
(1.20) |
then separately, and satisfy
(1.21) |
For , because is a double-well potential, [9] proved that (1.21) admits layer solutions (unique up to translations) in the sense of Definition 2. For , (1.21) is the traveling wave form of the Benjamin-Ono equation which admits
(1.22) |
as a solitary solution [7]. These solutions also satisfy the boundary condition (1.20). These special solutions partially explain the structure of minimizers observed in [40, 39], i.e., it is a layer solution in the shear direction while it is a solitary wave in the transverse direction.
As far as we know, a complete answer on the rigidity of minimizers is still unknown even for the case . More explicitly, does the De Giorgi conjecture hold in this case? Does (1.17) (or (1.21)) admit any other solution? Existing evidence indicates negative results. If is replaced by in (1.21) and we take , the author of [11] proved that there exist solutions being a soliton in the direction while being periodic (but non-constant) in the direction. Thus, the one-dimensional symmetry (or the De Giorgi conjecture) fails in this case. This evidence strongly indicates the existence of high-dimensional solutions of in (1.21). High dimensionality physically indicates the existence of curved dislocations but the construction of a counterexample for the De Giorgi conjecture in the nonlocal case is still open.
For general cases where the Poisson ratio is non-zero, neither existence nor rigidity result is proved to our best knowledge. In particular, no matter has a one-dimensional profile or not, no conclusion can be drawn on the rigidity of .
Another question regarding the De Giorgi conjecture is also of great interest: for what misfit potential , there exist one-dimensional solutions for (1.17)? For what misfit potential , the De Giorgi conjecture holds, i.e. all solutions of (1.17) are one dimensional? No previous study has ever considered these problems as far as we know.
In summary, the rigidity and existence of the vectorial PN model is an important problem that is central to studies of dislocations, both straight and curved dislocations. Our contribution to this macroscopic framework is that, under the assumption , i.e. only depends on , a complete answer to existence and rigidity is justified even for high dimensions. See the following sections in the introduction.
1.3. The nonlocal scalar equation in high dimensions
We remind our audience here that we will focus on the case where only depends on and is a double-well type potential (see (1.8)) in the following sections.
We extend the discussion to any dimension and clarify the set up. Denote , consider the high-dimensional reduced scalar equation in :
(1.23) |
The potential function is a double-well potential that satisfies (1.8). The linear operator is a convolution-type singular integral operator [38] which is defined as
(1.24) |
whose convolution kernel can be written as
(1.25) |
where .
We impose several assumptions on the operator and its kernel . To clarify these assumptions, we first introduce the Fourier transform on and the Sobolev spaces .
Denote . The Fourier transform on is understood as a composition in two directions: the Fourier transform on in the direction and the Fourier series expansion on in the direction. Denote where and , then the Fourier transform of , denoted as , is defined as
Thus the Fourier transform on maps functions defined on into functions defined on . For any , we define Sobolev spaces in the classical way on the Fourier side:
(1.26) |
are Hilbert spaces with inner product
(1.27) |
Denote the norm induced by this inner product as . We also define the homogeneous norm as
(1.28) |
Now we are ready to impose assumptions of in (1.24) and introduce several important properties of it. We assume that:
-
(A)
(symbol of order 1) The Fourier symbol of is positive with same order as , i.e. for any , there exist positive constants and such that
(1.29) -
(B)
(positivity and continuity) is positive and continuous on .
-
(C)
(homogeneity) For any and ,
(1.30) -
(D)
(symmetry) For any , .
The assumptions we impose on and its kernel include two important cases. First, in dimension , the non-local operator in equation (1.15) derived from the PN model is included if the Poisson ratio . In this case, the operator has Fourier symbol (see (1.15)) which is of the same order as , so Assumption (A) is satisfied. Moreover, the authors of [14] proved that satisfies assumption (B), (C) and (D) if and only if . So equation (1.15) is included in this context if . Second, in arbitrary dimensions, if we take , then defined on is also included. In this case, the Fourier symbol is exactly and according to [26], there exists a constant such that
(1.31) |
So all assumptions are satisfied.
We remark here that we adopt two different but equivalent definitions for : one is as a Fourier multiplier and the other is as a singular convolution. The result that these two definitions for fractional Laplacian are equivalent is thoroughly investigated in [26]. For equation (1.15), the equivalence of these two definitions is also well-studied in [14]. So in later sections, we will switch between these two definitions for the sake of convenience.
1.4. Main results and strategies
Before presenting the main results, we introduce the fractional Allen-Cahn equation [5]:
(1.32) |
Here the double-well type potential satisfying (1.8) is exactly the misfit potential in the PN model. Taking in (1.15), we see that (1.32) is a special case of (1.23) and (1.15). (1.32) has already been thoroughly investigated in the literatures [9, 32, 37, 34, 35, 15]. In particular, the well-posedness result of (1.32) is completely developed. A long standing conjecture named after De Giorgi [12, 21] (which originally discussed the local case, i.e., one replaces by in (1.32), but then generalized to the non-local case (1.32)) is proved for dimension . The De Giorgi conjecture claims that any layer solution (see below) to (1.32) is a simple 1D profile for dimensions . In the classical Allen-Cahn equation, this conjecture is optimal in the sense that a counterexample in dimension is constructed [13]. The layer solution in the De Giorgi conjecture is defined as:
Definition 2.
is a layer solution to equation (1.32) if
(1.33) |
The layer solution is also of main interest in the PN model since it models a dislocation profile that monotonically converges to two stable states at far field in the shear direction.
Now we are ready to articulate our existence and rigidity result on the PN model and (1.23). Although the PN model and (1.23) share the common double-well nonlinearity and non-localness with the fractional Landau-Ginzburg equation (see (1.32)), the main difference between our setting and previous work on (1.32) is that we work on a partially periodic domain and Hilbert spaces while previous work focused on the whole domain and Banach spaces . This discrepancy in the setting urges us to develop more appropriate methods while referring to some valuable techniques introduced in previous work.
For the existence problem, although we know that (1.16) is a solution to (1.15) and (1.14), we are still not aware of whether a minimizer of the total energy (1.1) in function set (1.35) exists. In [9], authors worked on Hölder spaces and derived some Schauder’s estimates of the weak solution to (1.32). Based on these estimates, they proved the existence of the classical solutions to (1.32) for by considering the harmonic extension of (1.32) on the upper half-plane. In [32], the authors adopted the direct method in calculus of variations minimizing the total energy on a subset of , i.e.
(1.34) |
They proved the existence and uniqueness of the minimizer in one dimension and the existence result is generalized to any dimension .
For the high-dimensional equation (1.23), we will follow the idea of [32] by using the direct method in the calculus of variations to prove that the minimizer of a functional exists. However, instead of requiring the far field assumption (1.9), we only consider perturbation of a given 1D profile who satisfies (1.9):
(1.35) |
Here is a smooth 1D profile, i.e. for any , satisfying
(1.36) |
We will abuse the notation to represent the profile defined on either or . We remark here that the weak regularity does not ensure any far field limit behavior in any dimension, even in dimension .
The functional that we aim to minimize is the perturbed version of the total energy (1.1):
(1.37) | ||||
Here is the double-well type potential considered in (1.23) that satisfies (1.8).
Starting from functions only with regularity and even not necessarily satisfying the far field limit condition, we construct a minimizer with regularity (in fact smooth) that also satisfies the desired rigidity result that we aim to prove: it is a layer solution with 1D symmetry.
Theorem 1.
(Existence of the minimizer) Suppose that is a double-well type potential satisfying condition (1.8). Consider set defined in (1.35) and energy functional defined in (1.37). Then:
- (i)
-
(ii)
(regularity) in satisfies . In particular, solves equation (1.23) in sense and satisfies the far end limit condition uniformly in :
-
(iii)
(monotonicity) in satisfies for any , i.e. is strictly increasing in direction.
-
(iv)
(symmetry) in satisfies for any , i.e. is a 1D profile.
The critical technique in the proof is the energy decreasing rearrangement method in [32]. This method relies on the rearrangement inequality (see Lemma 3.1) whose proof is quite elementary. However, driven by this basic inequality, the energy decreasing method is powerful in proving monotonicity and 1D symmetry. We will introduce this method in Section 3.1.
For the rigidity problem, it worth mentioning the De Giorgi conjecture on the fractional Ginzburg-Landau equation (1.32). It claims that at least for , layer solutions to (1.32) are in fact just 1D profiles. Here a layer solution is defined in Definition 3. This conjecture was proved for dimension in [9] and finally completely proved by Savin in his series of work [34, 35, 32]. We also mention the asymptotic analysis for the sharp interface limit of the fractional diffusion-reaction equation with isotropic/anisotropic nonlocal kernel of order in [4, 20, 23, 30] .
The common approach to prove the De Giorgi conjecture is to develop a Liouville-type theorem and then apply the theorem on ratios of partial derivatives in different directions . Then one can conclude that there exist constants such that
So in fact only depends on variable and hence is a 1D profile. For (1.23), we can prove the following theorem which is true for any dimension , not only for dimension :
Theorem 2.
(De Giorgi Conjecture) For any dimension , suppose that satisfies and is a layer solution (defined in Definition 3) to equation (1.23), i.e.
Here is a double-well type potential satisfies (1.8) and is defined in (1.24) satisfying Assumptions (A)-(D). Then only depends on variable, i.e. there exists such that .
We emphasize here that the main reason of Theorem 2 being true in any dimension instead of only dimensions less than eight is that we fully employed the compactness of the torus . The compactness ensures convergence of a sequence which is a key step in our proof (see the proof of Theorem 2). As we explained in Section 1.2, without periodicity, the De Giorgi conjecture may fail in the classical case [11]. Therefore, domain is critical to our result which is also physically meaningful since it incorporates the periodicity in materials.
Instead of using Liouville type theorems, we prove Theorem 2 by analyzing the spectrum of a linear operator. This method sufficiently respects the maximal property of operator (see Lemma 2.1) which is realized by the positivity assumption (Assumption (B)). Utilized in our previous work [18], this spectral analysis method is straightforward and appropriate in our setting since the working spaces are selected as Hilbert spaces instead of Banach spaces in [9]. Under this setting, we can use the perturbation theory of self-adjoint operators on Hilbert spaces [25].
Specifically speaking, suppose that is a given solution to (1.23) that satisfies conditions in Theorem 2. Differentiating on both sides of equation (1.23), we see that and are solutions to the following non-local linear elliptic equation of on which is given by:
Equivalently, and are eigenfunctions of eigenvalue 0 for the linear operator linearized along profile :
(1.38) |
Therefore, as long as we can prove that 0 is a simple eigenvalue of , i.e. the eigenspace of 0 is only 1 dimension, then we prove that and are linearly dependent, which indicates 1D symmetry. This is the main idea and approach we will utilize to prove Theorem 2.
As a direct corollary of Theorem 2, we can prove that both layer solutions and minimizers of on are unique up to translations. Define and as
(1.39) | ||||
i.e. is the set of layer solutions to (1.23) with regularity and is the set of minimizers of on set . Then we can prove the following theorem:
Theorem 3.
Theorem 3 provides a compatible physical interpretation of the PN model in three dimensions (with periodicity in the transverse direction): if we assume exclusive dependence of the misfit potential on the shear displacement, then the equilibrium dislocation on the slip plane only admits shear displacements. Furthermore, this uniquely (up to translations) determined shear displacement is a strictly monotonic 1D profile connecting two stable states. This reduces the vectorial PN model to the two-dimensional PN model which was investigated in our previous work [19]. In summary, we have the following theorem:
Theorem 4.
Suppose that is a double-well type potential satisfying (1.8). Consider the functional energy in (1.1) integrating on , i.e.
(1.42) |
Here is the displacement vector, and are the strain tensor and the stress tensor respectively given by (1.3) and is the slip plane defined in (1.12). Assume . Suppose that is a global minimizer of as in Definition 1, then:
-
(i)
(regularity) The displacement vector is smooth in .
-
(ii)
(rigidity) The displacement in transverse direction is 0, i.e. in ; is the unique (up to translation in direction) 1D profile independent with variable, strictly monotonic in direction satisfying
(1.43) -
(iii)
(Fourier representation) and only depend on and in . On the Fourier side, and can be uniquely represented by :
(1.44) (1.45) -
(iv)
(Dirichlet to Neumann map) On , the stress tensor can be expressed as
(1.46) (1.47) -
(v)
The stress tensor is divergence free, i.e.
(1.48) This also holds point-wisely in .
These four theorems (Theorem 1, 2, 3 and 4) are the main results for this work which completely close the problem of existence and rigidity in a general setting including the original PN model with Poisson ratio . Following this logic, we will first conduct a preliminary analysis in Section 2 to assist readers to bridge some gaps in understanding the derivation of (1.23) and be aware of some important properties of the linear operator . Then we prove Theorem 1 in Section 3 and Theorem 2, 3 and 4 in Section 4. Finally, the spectral analysis of operator is established in Section 5 which proves that 0 is simple and the principle eigenvalue of . For facts in functional analysis and details in the spectral analysis, readers may refer to Appendix A; for proofs of some lemmas in the proof of the theorems, readers may refer to Appendix B.
2. Preliminary analysis
In this section, we will first provide some details of the derivation of the reduced scalar equation (1.15), then discuss three important properties that will be used in the proof of the three theorems.
2.1. Derivation of the reduced scalar equation
Denote the Fourier transform of as where is the frequency vector. Given that satisfies equation (1.13), one can rewrite on as a linear transform of on the Fourier side:
(2.1) |
Details of this derivation can be found in Appendix [14].
From equation (2.1), the Euler-Lagrangian equation (1.13) can be rewritten as an equation of on , i.e.
(2.2) |
Here is the nonlocal differential operator with Fourier symbol .
A further simplification can be realized on equation (2.2) due to independence of with , i.e. . This independence reduces equation (2.2) into an equation of . On the Fourier side, the second component in (2.2) indicates that we can represent by , i.e.
(2.3) |
Substituting this equality to the first component in (2.1) yields
Now denote the linear operator with Fourier symbol . Then the first component of equation is in fact an equation of , i.e. equation (1.15):
(2.4) |
This equation is the reduced scalar equation.
2.2. Properties of
Assumption (A) ensures that is a self-adjoint operator defined on and maps to (see Lemma A.2). By assumption (B) and (C), one can easily conclude that kernel satisfies that for any ,
(2.5) |
Here and are positive constants. Indeed, for any non-zero , we have
and has a positive lower bound and a positive upper bound on the compact set . So (2.5) holds.
Furthermore, we will prove three important properties of the linear operator which play critical roles in the proof of Theorem 1, 2 and 3.
First, positivity of ensures that if attains global maximum at point , then . We call it the maximal principle of operator :
Lemma 2.1.
(Maximal principle) Suppose that attains global maximum at and global minimum at on . Then
The equality holds if and only if is constant.
Proof.
By positivity of , we know that
Thus the inequality holds and the equality holds if and only if is constant. ∎
We emphasize that this property of operator plays an important role in the proof of the De Giorgi conjecture (see Section 4.2).
Second, homogeneity of ensures that if , i.e. is a simple 1D profile independent with variable , then there exists constant such that .
Lemma 2.2.
Suppose that satisfies . Then there exists a constant such that
Proof.
Consider which is defined as
Then for any , a change of variable implies that
So is the kernel of half Laplacian for one dimension. Therefore by Fubini’s theorem, if , we have
By (1.25), we have
Substituting this back to the formula of , we have
So for any that is 1D profile, acting on is just acting on up to a constant. ∎
Lemma 2.3.
There exist positive constants such that
(2.6) |
3. Existence of minimizers
In this section, we will prove Theorem 1. Recall the energy functional defined in (1.37), i.e.
We first rewrite this energy functional. In fact, by Lemma 2.2, if we denote , then we can rewrite as
(3.1) |
Here is the constant in Lemma 2.2. From (3) we see that subtraction of in the definition (1.37) ensures that is finite if is bounded and satisfies . For the sake of convenience, we will switch between (1.37) and (3) when using functional .
The main idea in the proof of Theorem 1 is to first slightly modify the minimizing problem on a subset of denoted as . is defined as
(3.2) |
Here where and are real numbers. By definition of minimizers, a minimizer solves the following Dirichlet problem in weak sense:
(3.3) |
For a minimizer , result similar to Theorem 1 can be proved, which is summarized in the following proposition:
Proposition 1.
Suppose that is a double-well type potential satisfying condition (1.8). Define function set as in (1.35) and energy functional as in (1.37). Then:
-
(i)
(existence) There exists such that . In particular, is a weak solution to (3.3).
-
(ii)
(monotonicity) in satisfies that for any , holds for a.e. , i.e. is increasing in direction.
-
(iii)
(symmetry) in satisfies that for any , holds for a.e. , i.e. is a 1D profile.
To prove monotonicity and symmetry, one needs to utilize a critical technique: the energy decreasing rearrangement method in [32] which is based on the rearrangement inequality. After constructing in Proposition 1, a minimizer of on will be constructed using these minimizers on finite intervals and Theorem 1 is ready to be proved.
Following this logic, we will first carefully introduce the energy decreasing rearrangement method utilized in [32] in Section 3.1. This tool is prepared for the proof of Proposition 1 in Section 3.3 which ensures existence of the minimizer on . Then in Section 3.4, we will introduce several technical lemmas before proving Theorem 1 in Section 3.5.
3.1. Energy decreasing rearrangement
We denote and , i.e., and represent the positive part and the negative part of respectively. In this section, we will introduce the energy decreasing rearrangement method that is used in [32]. In fact, this method relies on the following elementary equality:
Lemma 3.1.
(rearrangement) Suppose that are four real numbers. Denote and . Then the following inequality holds:
(3.4) |
In particular, if and only if .
Readers may refer to Appendix B for proof of this inequality. Now we are ready to introduce the energy decreasing rearrangement method.
Lemma 3.2.
Proof.
Recall energy functional defined in (1.37), i.e.
since is a local term, we have
So we only need to compare the convolution term. A straightforward calculation implies that
By the definition of and , we know that
holds for every , thus
Let , then in terms of Lemma 3.1 we know that
By Lemma 3.1, we have
Thus (3.5) holds. So in terms of integrating , holds if and only if holds a.e. in . This concludes the proof. ∎
Lemma 3.2 ensures that if we are given two functions defined on , we can construct a pair such that they have a total energy less than . Here comes the name of this tool: the energy decreasing property of this construction is realized by the precedent rearrangement (Lemma 3.1), so we name it as energy decreasing rearrangement method. Now we are ready to prove Proposition 1 using Lemma 3.2.
3.2. Relationship with the increasing rearrangement
Clarification on this rearrangement technique is necessary to help readers distinguish it from other similar tools. Another rearrangement skill broadly utilized in the calculus of variations is the increasing rearrangement, which was first introduced in [33]. Given satisfying , the increasing rearrangement of , denoted as , is an increasing function with sublevel sets which are of same volume as those of , i.e.,
(3.7) |
Here the rearrangement of a Borel set , i.e. , is defined as
(3.8) |
The machinery of the increasing rearrangement is exactly the same as that of the cumulative density function (CDF) matching approach. The measure-preserving property maintains local functional energies (e.g., the double-well potential), while the monotonicity reduces the convolution-type non-local functional energy (e.g., the reduction of the elastic energy on the slip plane).
Due to this energy reduction property, the increasing rearrangement is also employed to minimize functional energies that share common structures with in (1.37) [3]. Although results derived in [3] are similar to ours, the context of [3] is much different in the sense that the convolution kernel satisfies
(3.9) |
while in the current context we have
(3.10) |
Therefore, the availability of the increasing rearrangement in our setting is indirect. Application of the increasing rearrangement was also considered in [32] in which the authors commented that it worked for instead of the critical case which is exactly in the PN model.
In contrast, originated in [32], Lemma 3.2 is powerful in this critical case (also other non-critical cases as discussed in [32]) with a much simpler and elementary proof compared to the increasing rearrangement [2]. The main difference between Lemma 3.2 and the increasing rearrangement is that the former rearranges a pair of profiles and while the latter merely works on a single candidate . Therefore, the hidden mechanisms of these two methods are totally different and readers should be aware of this discrepancy.
3.3. Minimizers on finite intervals
Before proving Proposition 1, we introduce the translation-invariant property of the energy functional which is applied in the proof.
Lemma 3.3.
(translation invariant) Consider in (1.37). Then for any , we have
i.e. is invariant under any translation.
The proof of this lemma only relies on some elementary computations of integrals using Lemma 2.2. Readers can refer to Appendix B for detail. We will again use this invariant property later to prove the lower boundedness of on .
Now we are ready to prove Proposition 1 which addresses the minimizer of on the set defined in (3.2):
We aim to prove that there exists a minimizer of on set .
Proof of Proposition 1.
First we prove statement (i). Notice that for any , is uniformly bounded from below by a constant that depends on , i.e.
The last equality is by Lemma 2.2. is the constant in Lemma 2.2. Therefore, there exists a minimizing sequence such that
(3.11) |
For any , consider
i.e. is the cut-off of from below by and from above by 1. Then and satisfies
by definition of . So we can assume without loss of generality.
Denote . Then is supported on since . This indicates that , i.e. is uniformly bounded in . Moreover, is also uniformly bounded in since by Lemma 2.3,
Meanwhile, using the definition of in (3) and the Cauchy-Schwartz inequality, we have
Here is the constant in Lemma 2.2 and is the constant in Lemma 2.3. is a constant that only depends on and but independent with any certain minimizing sequence. Therefore, is uniformly bounded in .
Now we are ready to prove that is indeed a minimizer. Uniform boundedness of in implies that there exists supported on such that in . Hence and up to a subsequence,
Therefore, by Fatou’s lemma, the strong convergence and the definition of in (3), we know that
Thus is indeed a minimizer of on set . In particular, it is a weak solution to (3.3) by a simple calculation of the first variation of the energy functional . This proves (i).
We will use the energy decreasing rearrangement method (Lemma 3.2) to prove (ii) and (iii). First we prove (ii). For any given , consider . Denote and . Then by Lemma 3.2, we know that
This inequality is in fact an equality. Notice that if and if , so . By the translation invariant property (Lemma 3.3), we know that is in fact a minimizer of on Thus
Note that if and if , so . Then by minimality of we know that
Therefore, we have
Thus
By Lemma 3.2, this equality holds if and only if either or holds almost surely in . By the boundary condition and that , we know that the former is true, i.e.
This inequality holds for a.e. for arbitrary . This proves (ii).
Eventually, we prove (iii). Again we will adopt Lemma 3.2, i.e. the energy decreasing rearrangement method. Unlike the case in the proof of (ii) where we only consider translation in direction, we consider translation in both and direction, but with direction still positive. For any given such that , consider . As in the proof of (ii), by considering the minimum and maximum of and , we conclude that
(3.12) |
holds for almost every .
Now let . For any , denote the square with length centered at . Then for any (not almost every but every) and , by inequality (3.12), we have
Then let and by Lebesgue’s differential theorem, we have
holds for a.e. . This holds for arbitrary without specific assignment of sign of each component. Then taking both and in the translation concludes that
holds for a.e. . This closes the whole proof of Proposition 1. ∎
3.4. Technical lemmas
Before proving the existence theorem, i.e. Theorem 1, we will first provide several technical lemmas whose proofs are attached in Appendix B. These lemmas finally lead to the fact that is lower bounded on . This enables the application of the direct method in calculus of variations in the proof of Theorem 1.
Lemma 3.4 addresses an approximation property:
Lemma 3.4.
For any such that , there exist a sequence and positive constants such that
and
Proof.
Given such that , because , so standard density argument (see [1, 38]) claims that there exists and such that , on and as . Therefore,
Denote , . Then by (3), we have
(3.13) | ||||
here is the constant in Lemma 2.2. Then by Lemma 2.3 and convergence in and , we have
as .
For the non-linear potential term in (3.13), the mean value theorem ensures that there exist and such that
Because , we can assume without loss of generality. Thus
is uniformly bounded in . Also notice that for , then by the Cauchy-Schwartz inequality, there exists that only depends on such that
Here is a constant that only depends on and . This closes the proof. ∎
The following lemma claims that we can use the nonlinear potential to control norm of .
Lemma 3.5.
Suppose that is a non-decreasing function on such that is non-decreasing, for all and . satisfies (1.8). Then there exist constants and such that
Here and only depend on and are independent with .
Proof.
According to (1.8), and attains strict minimum at and , so there exists such that
Remember that is non-decreasing, and , so
Therefore, we have
∎
Using these technical lemmas, we are ready to prove Theorem 1.
3.5. Proof of Theorem 1: existence of the minimizers
As stated in previous sections, we will use the calculus of variations to prove Theorem 1 by minimizing on set . Proved in Proposition 1, a key property of the minimizers is that for and ,
(3.14) | ||||
To prove lower boundedness of with the help of (3.14), we consider the following subset of which is much finer than :
(3.15) |
This definition is inspired by Proposition 1 and preceding technical lemmas: according to Proposition 1, we know that if . Here is the minimizer of on which is constructed in Proposition 1. Through the bridge of set , we will prove that:
Lemma 3.6.
Proof.
We first prove (i). Because , so we have . Hence we only need to prove that .
Consider , i.e. the cut-off of by 1 from above and by from below. Then is also in and satisfies that . So we only need to consider those such that .
By Lemma 3.4, for any , there exists and such that on and
Then according to the definition of in (3.2), we know that . By Proposition 1, we know that where is a minimizer of on satisfying that is a 1D profile and increasing in direction. Therefore
By the translation-invariant property (Lemma 3.3), we have
where is a translation of that crosses , i.e.
By definition, we know that . Thus for any and , there exists such that
Thus . By arbitrariness of , we have .
Now we prove (ii). By Lemma 3.5, for any , there exist and that only depend on such that
where . Therefore, using the expression of in (3), the Cauchy-Schwartz inequality, Lemma 2.3 and Lemma 2.2, we have
Here is the constant in Lemma 2.3, is the constant in Lemma 2.2, and
are constants that only depend on , and the operator . This concludes the proof. ∎
Lemma 3.6 in fact provides insightful corollaries: first, we have
Thus is lower bounded in . Moreover, according to (ii), functional can be used to bound norm of for any . In the proof of Theorem 1, this observation will be used to find an a.e. limit of the minimizing sequence which is proved to be a minimizer of on . Now we are ready to prove Theorem 1.
Proof of Theorem 1.
We will first prove (i). By Lemma 3.6, we know that
Denote . Then there exists such that as . Again by Lemma 3.6 (ii), we know that is uniformly bounded. Thus there exists such that up to a subsequence,
Denote and . Then a.e. in and in .
In fact, is a minimizer of on . By Fatou’s lemma, we know that
(3.16) |
Meanwhile, since weakly in , hence also converges weakly in , thus
(3.17) |
Substituting (3.5) and (3.17) into the following equality, we have
So is in fact a minimizer of on . In particular, it is a weak solution to (1.23). This proves (i).
Now we prove (ii). Because , so and they are all 1D functions and non-decreasing in direction, so the a.e. limit is also non-decreasing in direction and is a 1D profile satisfying . Thus (3.14) holds for almost every . To prove that , we first show that . This is true by the mean value theorem and (3.14):
(3.18) | ||||
So . Remember that , so by Lemma 2.3, we have
So . Moreover, by Lemma 2.2, so . In particular, solves equation (1.15) in sense. By (3.14), we know that is a 1D profile, so implies that holds uniformly in . So (ii) holds.
Finally, we prove (iii) and (iv). Boundedness of implies that . Thus and . Remember that is a 1D profile, so by embedding , we know that (3.14) implies that
holds for any . So (iv) is proved and (iii) is partially proved except the strict monotonicity.
To prove the strict monotonicity, suppose that for some , taking derivative on both sides of (1.23) yields
Thus at . However, since , we know that attains minimum at . Then by Lemma 2.1, we know that , i.e. is a constant. This contradicts with the far field limit of . So . This concludes the whole theorem. ∎
4. The De Giorgi Conjecture and uniqueness of solutions
In Theorem 1, we prove that there exists a minimizer of functional on set who satisfies that and for any , we have
In particular, we have . As Definition 2, we keep the same definition of layer solutions for (1.23).
Definition 3.
As far as we know, results parallel to the De Giorgi conjecture that address the vectorial case, i.e. system (1.13), and (1.23) are still wanting and lack of exploration. In this section, we will prove Theorem 2 which fills in this blank: all layer solutions to (1.13) or (1.23) with regularity are in fact 1D profiles if we further assume .
In [9] and related literatures on the De Giorgi conjecture, the standard approach to prove this type of symmetry result is to first derive some Schauder estimates for weak solutions and then using Liouville type theorems to prove 1D symmetry. For example, authors in [9] first derived regularity for layer solutions by careful application of theories on elliptic PDEs. Then they noticed the following lemma (see also Lemma 2.6 in [9]), a Liouville type lemma:
Lemma 4.1.
(a Liouville type theorem) Let be a positive function, not necessarily bounded on all of . Suppose that satisfies
in the weak sense. Assume that, for every , we have
for some constant independent of . Then is a constant.
Applying this lemma to function , where direction is the monotone direction for the layer solution , they proved the following lemma (see also Lemma 4.2 in [9]):
Lemma 4.2.
Suppose that is a double-well potential satisfying . Assume that and that is a bounded solution of
Then there exists a function with in and such that for every ,
for some constant .
As a straightforward corollary, the one-dimensional symmetry of solutions to is also established.
Instead of adopting any Liouville type theorem to prove Theorem 2, we will develop a new approach that is first utilized in our previous work [18] to prove 1D symmetry of layer solutions to (1.15). Although Liouville type theorem is not employed, we found that the insightful observation provided by Lemma 4.2 in [9] is significant: as long as one can prove that there exist constants such that
holds, then the profile is a 1D profile. Remember the discussion in Section 1, and are eigenfunctions of eigenvalue 0 for the linear operator
(4.2) |
Therefore, as long as we can prove that 0 is a simple eigenvalue of , i.e. the eigenspace of 0 is only 1 dimension, then we prove that and are in fact linearly dependent, which indicates 1D symmetry. This is the main idea and approach we will utilize to prove Theorem 2. Following this logic, we will first establish proper regularity results for layer solutions in Section 4.1 and then prove Theorem 2 in Section 4.2.
4.1. Regularity results
In this section, we will derive some regularity results for layer solutions to equation (1.23) and some properties of elements in the kernel of . Two main results will be derived in this section under assumption . First, any layer solution of equation (1.23) is in for any (see Lemma 4.3) and in particular, is smooth with bounded derivatives of any order. Second, eigenfunctions of with eigenvalue 0 are in for any and in particular, they decay to 0 uniformly in as (see Lemma 4.4).
As a reminder, we assume in this section. Even though this is stronger than assumption which is generally considered, this setting indeed covers many important cases. For instance, in the PN model and in the Allen-Cahn equation [5].
Now we begin to prove these two lemmas. All these lemmas only require that is bounded which is ensured by being a layer solution. Using the Gagliardo-Nirenberg interpolation inequality [31] and ideas in [29] (see Proposition 3.9), we will prove that:
Lemma 4.3.
Suppose that is a double-well potential satisfying (1.8) and is the linear operator defined in (1.24) satisfying assumption (A), (B), (C) and (D). For any dimension , if satisfying is a bounded solution to equation (1.23), i.e.
then for any . In particular, is in for any and smooth with bounded derivatives of any order.
Proof.
Taking derivative on both sides of the equation yields
Remember that is bounded, so is by continuity of . Thus which implies that . Thus by Lemma 2.3, . This also holds for . Thus and .
Now we prove by induction that for any positive integer . Suppose that , then by the Gagliardo-Nirenberg interpolation inequality, we know that for any , we have
Here and satisfy
Take , then we have and
Notice that if and , so , hence
Chain rule implies that for any multi-index that satisfies , we have
Here are constants depending on . Boundedness of and smoothness of ensure that is also bounded. Remember that , so we have for all . Thus by Hölder’s inequality, we have
where satisfies
Thus and . Thus for any multi-index that satisfies , so . Therefore,
Thus . Then by Lemma 2.3 and Assumption (A), we have and . Thus by induction, for any . In particular, this indicates that is smooth with bounded derivatives of any order. ∎
Remember that is smooth, so Lemma 4.3 also ensures that is smooth and bounded with bounded derivatives of any order. Recall that is a 0 eigenfunction of operator defined in (1.38), so by ellipticity of and regularity of , we can prove that , or more generally, any 0 eigenfunction of should attain regularity for any . As a direct corollary of Lemma 4.3, we have
Lemma 4.4.
Proof.
By Lemma 4.3, we know that is smooth with bounded derivatives of any order. Suppose that for some , then
Here is a constant that only depends on and . Thus , hence by Lemma 2.3 and Assumption (A), we know . So by induction, for any . In particular, is smooth and satisfies that holds uniformly in . ∎
Remark 2.
Although we assume , for a given dimension , is sufficient to ensure that layer solutions and 0 eigenfunctions of operator are continuous and hold uniformly in . These are the properties we need to prove Theorem 2.
Finishing proving these two lemmas, we are ready to prove Theorem 2.
4.2. Proof of Theorem 2: the De Giorgi conjecture
As discussed in the beginning of this section, we will prove Theorem 2 by proving that the is only 1 dimension. Here is the operator defined in (1.38). Similar to the proof in [18], Lemma 2.1, i.e. the maximal property plays a critical role in concluding linear dependence of and any other function in the .
Proof of Theorem 2.
We will prove that if a non-trivial satisfies , then there exists a constant such that .
According to Lemma 4.3, for any , so is continuous. By definition of layer solution (see Definition 3), we know that .
This limit actually holds uniformly in by continuity of . To prove uniformness, by strict monotonicity of , for any and , there exists a unique such that . Therefore, for any , we consider function
We prove that is continuous. Given and sufficiently small, since , by strict monotonicity of w.r.t. , we know that
Then there exists such that
Here is the square centered at with width . Then by definition of and monotonicity of , we know that for any such that , we have . Thus is a continuous function for any . So by compactness of , there exist real numbers and such that
So by monotonicity, we know that for any ,
Thus limit holds uniformly in .
By Lemma 4.4, we know that
hold uniformly in . Consider and define set
(4.3) |
Because is non-trivial, we assume that for some without loss of generality. Then is non-empty because
Here we use the positivity of in the definition of layer solutions. Therefore,
is well-defined and satisfies .
We can also prove that for any , there exists such that attains a negative minimum. By construction of and Lemma 4.4, we know that
holds uniformly in . Meanwhile, attains a negative minimum. Therefore, there exists such that attains minimum at by continuity of and , which is ensured by Lemma 4.4 and Lemma 4.3.
Moreover, there exists that only depends on and such that for any . Notice that satisfies since both and are so, thus
holds by minimality of and Lemma 2.1. Because , so . However, since uniformly in and , so there exists a constant such that if , then . Because , so .
Therefore, we know that is a compact set in . So there exists a subsequence of in such that , i.e. the supremum of set , and
for some . Because , so
by passing the limit and continuity of and . However, by the definition of , we have for any otherwise should not be the supremum of . Thus .
This ensures . Because , so attains minimum at . However, since is also in the kernel of , we have
Then by Lemma 2.1 and minimality of , we have . Thus
i.e. and are linearly dependent. Thus the kernel of is only 1 dimension. Notice that every partial derivative of belongs to kernel of , so there exist constants such that
for any .
To close the proof, we prove that in fact . Otherwise, we assume without loss of generality. For any given , by periodicity and the far end limit assumption (1.9), we have
Here are positive integers and form the canonical orthogonal basis in with 1 only at the th component, and 0 for others. This yields contradiction. So , i.e. and is a 1D profile that only depends on . ∎
4.3. Proof of Theorem 3: uniqueness up to translations
To completely understand all layer solutions to (1.23) and minimizers of functional on set , we prove the following lemma:
Lemma 4.5.
Proof.
Let . First of all, is a weak solution to equation (1.23). Then as in the proof of Theorem 1, we know that it solves (1.23) sense, i.e. (see calculation (3.18)). Then by Lemma 2.3, we know that .
Because is a minimizer, so . Otherwise
(4.4) |
is also in and satisfies by definition of in (1.37). This contradicts with the minimality of . So is bounded. Then by Lemma 4.3, for any . Therefore, we have
(4.5) |
Now it is left to prove the strict monotonicity of . Again, this is realized by the energy decreasing rearrangement method (Lemma 3.2). For any , consider the translation of , i.e.
Define
Then by Lemma 3.2, we know that
By translation-invariance (Lemma 3.3), we know . Thus both and are minimizers. So by minimality of and , we have
Again, by Lemma 3.2, this equality holds if and only if either or . Then by the limit condition (4.5), we know . Thus is non-decreasing.
Finally, as in the proof of Theorem 1, the fact that is non-decreasing implies strict monotonicity. Suppose that for some , then taking derivative on both sides of (1.23) yields
Thus at . However, since , we know that attains minimum at . Then by Lemma 2.1, we know that , i.e. is a constant. This contradicts with the far field limit of . So holds for any . Thus is a layer solution. ∎
Therefore, all minimizers of on set are layer solutions. Recall that Theorem 2 claims that all layer solutions with regularity have one-dimensional symmetry if the double-well potential is smooth, so all these minimizers are also exactly 1D profiles.
Moreover, these 1D profiles are unique up to translations. According to [9], if is a double-well potential, then layer solutions to
(4.6) |
is unique up to translations (see Theorem 1.2 in [9]). Remember that Lemma 2.2 ensures that if is a 1D profile, therefore, both layer solutions and minimizers are unique up to translations.
Proof of Theorem 3.
By Theorem 2, we know that for any , u is a 1D profile to solution (1.23), i.e.
By Lemma 2.2, for any , we have
Thus viewed as a 1D profile , a layer solution satisfies
(4.7) |
Then by Theorem 1.2 in [9], we know
(4.8) |
Here is the unique solution to (1.41).
By Theorem 1 and Lemma 4.5, we know that is non-empty and . Moreover, by Lemma 3.3, i.e. the translation-invariant property, we know that if and only if . Notice that itself is also unique up to translations, so we have (1.40), i.e.
This concludes the uniqueness (up to translations) of layer solutions to equation (1.23) and minimizers of on set . ∎
4.4. Proof of Theorem 4: implication on the PN model
As a direct application of previous results on the existence and rigidity, now we can prove Theorem 4.
Proof of Theorem 4.
As a minimizer of in (1.42) in the perturbed sense, we know that is a weak solution to (1.13) by Lemma 1.1. A calculation (see [10]) involving the Dirichlet and Neumann map implies that if satisfies (1.13), the elastic energy in the bulk can be expressed by which is defined on the slip plane:
(4.9) |
Here is the linear operator defined in (1.15) and is the corresponding convolution kernel which satisfies Assumption (A)-(D). Therefore, is the minimizer of defined in (1.37). Then by Theorem 2 and Theorem 3, we know that statement (ii) hold. Therefore, only depend on and , satisfying the following reduced system of (1.13) in two dimensions:
(4.10) |
Here . Thus smoothness of implies that is smooth in , so (i) holds. Finally, by Lemma 2.3 in [19], we know that (iii), (iv) and (v) are true and hold point-wisely in by smoothness. ∎
5. Spectral analysis of
In Theorem 2, we prove that if is a layer solution to (1.23), then the operator in (1.38), i.e.
has one dimensional kernel which is exactly . In this section, we proceed to prove that is positively semi-definite and is an isolated point spectrum. Denote the spectrum, the point spectrum, the residual spectrum and the continuous spectrum of a linear operator as and respectively.
First of all, according to [41], since is self-adjoint (see Lemma A.2), we know . Meanwhile, since
holds uniformly in the direction and , we know that is lower bounded and can only be negative on a compact set in . Therefore, there exists a finite lower bound of the spectrum of , i.e.
Lemma 5.1.
. Here is a constant.
Employing the perturbation theory of self-adjoint operators [25], we can characterize the essential spectrum of by viewing as a self-adjoint perturbation of . Remember that the continuous spectrum is a subset of the essential spectrum, we have the following lemma:
Lemma 5.2.
. Here is a constant.
Therefore, the spectrum of that belongs to is a subset of with finite dimensional eigenspaces. Moreover, they are isolated points in . To finish the spectral analysis of , we finally prove the positive semi-definiteness of .
Lemma 5.3.
.
We will only prove Lemma 5.3 in this section and the proof of the fact that is self-adjoint, Lemma 5.1 and Lemma 5.2 is attached in Appendix A. Similar to the proof of Theorem 2, the proof of Lemma 5.3 adopts an argument of contradiction and relies on the maximal principle of in Lemma 2.1.
Proof of Lemma 5.3.
We will prove by contradiction. Suppose that there exist and non-zero s.t.
similar to the proof of Lemma 4.4, we can prove that for any and
holds uniformly in direction.
Consider . By Assumption B, i.e. positivity of kernel , and the fact that for any ,
we have
Thus satisfies
(5.1) |
Define for real number . Consider the following set of :
is nonempty because
for satisfying . Therefore
is a well-defined finite number that lies in .
Now for any , we will prove that there exists such that attains a negative minimum at . First of all, by the definition of , we know that is non-zero and attains a negative infimum. Remember that
holds uniformly in , so
holds uniformly in . Recall that attains a negative infimum, so continuity of implies that this infimum is indeed a minimum that is attained for some .
Moreover, is bounded in . Notice that by (5.1) and ,
Thus . By maximal principle (Lemma 2.1), we know that
since attains minimum at . Therefore, we have
Because by definition of , so . So there exists that only depends on and such that . Since is periodic in , we know that is bounded in .
Given the boundedness of sequence , we can now take a subsequence of (still denoted as ) such that , the supremum of , and as . As the supremum of , satisfies that . However, since , passing the limit in gives that
So , which means that attains minimum 0 at .
Acknowledgement
Jian-Guo Liu was supported in part by the National Science Foundation (NSF) under award DMS-1812573 and DMS-2106988.
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Appendix A Review of functional analysis
For the sake of completeness, we prove the fact that operator defined in (1.38) and in (1.24) are both self-adjoint in Lemma 5.1 and Lemma 5.2 which address the spectrum of . Let us recall that linear operator is given by
Here is a layer solution to equation (1.15). For theorems and definitions in functional analysis, one can refer to [41]. For perturbation theory of self-adjoint operators, one can refer to [25].
In fact, the fact that is self-adjoint is a corollary of Kato-Rellich’s theorem (see [25]). We still repeat the proof for readers’ convenience. The proof here needs an equivalent criterion for self-adjoint operators:
Lemma A.1.
Suppose that is a complex Hilbert space with inner product and is a symmetry operator on . Then is self-adjoint if and only if
(A.1) |
Proof.
: Suppose that is self-adjoint, we prove that . To prove this, notice that for any , we have
so by the closed image theorem, we know that is closed and . Also notice that
so are dense in by the Hahn-Banach theorem. Remember that they are also closed, so .
: Suppose that . We prove that is self-adjoint. Because is symmetry, so we only need to prove that since holds for any symmetry operator. Notice that
so . Remember that , so for any , there exists such that
So . Here we used that for , . Thus . So and . So is self-adjoint. ∎
Proof.
Then we prove that in (1.24) is self-adjoint. By Lemma A.1, we only need to prove that . We prove for only , the other side direction is just the same.
To prove this, we only need to prove that for any , there exists such that
One can rewrite this equality on the Fourier side as
Thus
(A.2) |
So we only need to prove that for any , in (A.2) is in . This is true by Assumption A which assumes that is real and with same order as :
Here is the constant in Assumption A. So by Lemma A.1, we know that is self-adjoint.
Finally, we prove that in (1.38) is self-adjoint. Denote and who is understood as a multiplier, then . First, because is self-adjoint, so by Lemma A.1, for any real number .
Moreover, there also exists such that . To prove this, notice that for any , we have
(A.3) |
Then take for any , we have
so and . Notice that for sufficiently large , we have since is a bounded linear operator and
So by choosing sufficiently large , we have . This gives that are invertible. Notice that
so since and is invertible. Then by Lemma A.1, is self-adjoint. ∎
Proof.
Notice that is self-adjoint, so . Because holds uniformly in and , so there exists such that holds by continuity of and . Now we prove that for any , has a bounded inverse. This directly shows .
First, is closed. Let . For any , if , we have
If but , we have
This is because
since and is positively semi-definite. Thus for any , there exists such that for any .
Therefore, by the closed image theorem, is closed and . So is injective. Moreover, we have
since also belongs to . So by the Hahn-Banach theorem, . Remember that is closed, so . Thus is a bijection. Because is self-adjoint, so is closed, so is . Thus by the closed graph theorem, is bounded. Therefore, is not in the spectrum of . ∎
Finally, we prove Lemma 5.2. To prove this lemma, we need to employ Weyl’s theorem on perturbation of self-adjoint operators.
Lemma A.3.
(Weyl’s theorem [25]) Suppose that is a Hilbert space, is a self-adjoint operator on and is a symmetric operator on . Then if is relatively compact with respect to , then .
See 5.2
Proof.
Define function as
Notice that and as holds uniformly in , so there exists such that and
holds uniformly in direction. Now we rewrite operator as
is understood as a multiplier. We will prove that is relatively compact with respect to . Suppose that is bounded. We only need to prove that is compact in .
Denote . We only need to prove that for any , there exists a subsequence of such that . First of all, because , thus by Lemma 2.2, we have
Here is a constant that only depends on . Then by the Cauchy-Schwartz inequality, we know that
Thus there exists such that , thus is bounded in . Moreover, for any sufficiently small, there exists such that
for . Therefore,
by selecting sufficiently small. Then by compact embedding of and boundedness of , we know that there exists a subsequent of (still denoted as ) such that . Then for this subsequence, we have
This proves that . However, since is uniformly bounded from below, so is positively definite and . Thus . Taking closes the proof. ∎
Appendix B Proof of lemmas
Proof of Lemma 1.1.
From Definition 1 of minimizers, we calculate the variation of energy in terms of a perturbation with compact support in an arbitrary ball which is centered at with radius . For any such that has compact support in and satisfies (1.11), we consider the perturbation where is a small real number. We denote , and , . Then we have that
(B.1) | ||||
where we used the property that and are locally integrable in when carrying out the integration by parts, and the outer normal vector of the boundary is (resp. the ) for the upper half-plane (resp. lower half-plane). Similarly, taking perturbation as and notice that that and , we have
(B.2) | ||||
Since , and . Hence due to the arbitrariness of , we conclude that the minimizer must satisfy
(B.3) | ||||
for any and has compact support in , which leads to the Euler–Lagrange equation (1.13). Here we have written the equation in as the first equation of (1.13) in terms of the displacement . ∎
Proof of Lemma 3.1.
If or holds, then the equality holds. So we will focus on cases where and . By enumeration of all possible orders, we have:
- (i)
- (ii)
- (iii)
- (iv)
Therefore, the inequality holds. The equality is attained if and only if or or the order is preserved, i.e. or . These conditions are equivalent to the following clear inequality: . This concludes the proof. ∎
Proof of Lemma 3.3.
In fact, by change of variables, we have
Thus by Lemma 2.2, we have
Here is the constant in Lemma 2.2. So we only need to prove that
for any . Without loss of generality, we assume that . Then for , we know that and for , we have . Denote , and we separate the integral into 3 different parts, i.e. integral on (denoted as ), (denoted as ) and (denoted as ). Since on , we know that
On , we have
Because if or , so integral vanishes on or . Thus
(B.4) |
On , we have
Notice that for and for , so we have
and
Then substituting these two formulas into , we have
(B.5) |
A careful comparison of equation (B) and (B) shows that . Thus
∎