Localization for gapped Dirac Hamiltionians with random perturbations: Application to graphene antidot lattices
Jean-Marie Barbaroux, Horia D. Cornean, Sylvain Zalczer

TL;DR
This paper investigates how random impurities affect the electronic properties of graphene antidot lattices modeled by Dirac Hamiltonians, demonstrating localization phenomena at band edges due to disorder.
Contribution
It establishes band edge localization for Dirac Hamiltonians with random perturbations in graphene-like systems, extending understanding of disorder effects in such materials.
Findings
Proves existence of dense pure point spectrum near band edges
Shows eigenfunctions decay exponentially, indicating localization
Demonstrates dynamical localization in the perturbed system
Abstract
In this paper we study random perturbations of first order elliptic operators with periodic potentials. We are mostly interested in Hamiltonians modeling graphene antidot lattices with impurities. The unperturbed operator is the sum of a Dirac-like operator plus a periodic matrix valued potential , and is assumed to have an open gap. The random potential is of Anderson-type with independent, identically distributed coupling constants and moving centers, with absolutely continuous probability distributions. We prove band edge localization, namely that there exists an interval of energies in the unperturbed gap where the almost sure spectrum of the family is dense pure point, with exponentially decaying eigenfunctions, that give rise to dynamical localization.
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Taxonomy
TopicsSpectral Theory in Mathematical Physics · Quantum chaos and dynamical systems · Quasicrystal Structures and Properties
Localization for gapped Dirac hamiltonians with random perturbations: application to Graphene Antidot Lattices
J.-M. Barbaroux
Aix Marseille Univ, Université de Toulon, CNRS, CPT, Marseille, France
,
H.D. Cornean
Department of Mathematical Sciences, Aalborg University
Fredrik Bajers Vej 7G, 9220 Aalborg Ø, Denmark
and
S. Zalczer
Aix Marseille Univ, Université de Toulon, CNRS, CPT, Marseille, France
Abstract.
In this paper we study random perturbations of first order elliptic operators with periodic potentials. We are mostly interested in Hamiltonians modeling graphene antidot lattices with impurities. The unperturbed operator is the sum of a Dirac-like operator plus a potential , and is assumed to have an open gap. The random potential is of Anderson-type with independent, identically distributed coupling constants and moving centers, with absolutely continuous probability distributions. We prove band edge localization, namely that there exists an interval of energies in the unperturbed gap where the almost sure spectrum of the family is dense pure point, with exponentially decaying eigenfunctions, that give rise to dynamical localization.
Key words and phrases:
Dirac operators, random potentials, localization
2010 Mathematics Subject Classification:
Primary 81Q10; Secondary 46N50, 34L15, 47A10
Contents
- 1 Introduction
- 2 Setting and main results
- 3 One method to localize them all: Germinet and Klein’s bootstrap multiscale analysis
- 4 Application to our setting
- A Spectrum location
- B Combes-Thomas estimates
1. Introduction
The main goal of this paper is to derive spectral and dynamical localization properties near band edges for first order elliptic and periodic operators densely defined in , perturbed by random potentials. The main application we have in mind is related to graphene antidot lattices. Graphene is a two-dimensional material made of carbon atoms arranged in a honeycomb structure [7]. Charge carriers close to the Fermi energy behave like massless Dirac fermions, making pristine graphene a semimetal. One needs to produce an energy gap in order to turn graphene into a semiconductor.
Several gapped models have been proposed in the physics literature (see [10] and references therein). One such setting consists of a graphene sheet with periodic nanoscale perforations, a so-called graphene antidot lattice (GAL). Here the quantum dynamics is given by a two dimensional Dirac operator with a periodic mass term. Under certain conditions, a spectral gap appears near the zero energy (see [6] and [12] for theoretical works and [3] for a mathematical study).
The next step is to perturb the gapped Hamiltonian by an Anderson type potential for modeling sample impurities. There are two types of properties of such Hamiltonians we are interested in (see Definition 3.1 for details):
- •
Spectral localization: Dense pure point spectrum near the Fermi level with exponentially decaying associated eigenfunctions.
- •
Dynamical localization: Uniform boundedness in time of moments of positive orders of states which are spectrally supported in the dense point spectrum.
Starting from the seminal contributions by Anderson [1] and the rigorous spectral analysis initiated by Pastur [20, 15], a significant number of papers on Anderson-like Hamiltonians have been published in the mathematical literature.
Most of the existing mathematical results regarding these properties are derived for the case were the kinetic energy is described by discrete or continuous Laplace operators. The case where the kinetic energy is given by Dirac or Maxwell operators has been the subject of studies only recently.
A step towards Dirac operators has been done in the case where the kinetic energy is given by a Laplacian on , and the random potential is matrix valued (see [4] and references therein). In [22, 23] the authors considered discretized versions of Dirac operators on (), with a simple mass potential, and a random potential given by a matrix valued diagonal operator, and proved spectral and dynamical localization near band edges.
A precise analysis of the conditions leading to localization enables us to provide a result not only for 2-dimensional continuous Dirac operators, but also for a larger class of first order elliptic operators. This includes the operators describing “classical waves” as defined by Klein and Koines [18].
In our paper we are mainly interested in the case in which a spectral gap is created near the Fermi level by a deterministic multiplicative potential, which afterwards is perturbed by a random one.
Our main results on spectral and dynamical localization are stated in Theorem 2.10 and Theorem 2.11. The proofs of these results exploit the developments of the theory of multi-scale analysis for continuous operators as given by [8, 13, 14, 9].
2. Setting and main results
We start with a few definitions.
Definition 2.1**.**
Let be a family of Hermitian matrices where . We consider the following first-order linear operator with constant coefficients:
[TABLE]
densely defined in . It is elliptic if there exists such that for all and we have
[TABLE]
If , the maps
[TABLE]
are well defined and due to (2.2) there exists a constant such that
[TABLE]
where for some norm on .
A direct consequence is that is self-adjoint on the Sobolev space .
Definition 2.2**.**
We say that an operator on is a coefficient positive operator if it is a bounded invertible operator given by the multiplication by an Hermitian matrix-valued measurable function such that there exist two positive constants such that:
[TABLE]
where is the identity matrix.
We consider operators of the type
[TABLE]
where is a first-order elliptic operator with constant coefficients like in (2.1), and is a coefficient positive operator as in (2.4). The function , where is the space of Hermitian matrices, is supposed to be -periodic. We denote
[TABLE]
Such operators appear in connection with wave propagation and are sometimes called classical wave operators (cf. [19, 18]). We warn the reader that this name has nothing to do with the Möller wave operators of quantum scattering theory. The potential is -periodic and belongs to .
With the above definitions and assumptions the operator is self-adjoint on .
Assumption 1** (gap assumption).**
The spectrum of contains a finite open gap, which will be denoted .
Example 2.3**.**
The simplest examples are the free Dirac operators with mass in dimension two and three, respectively given by
[TABLE]
[TABLE]
and
[TABLE]
[TABLE]
Both operators are such that (cf. [26]), where for self-adjoint, is its resolvent set.
Example 2.4**.**
A family of operators which is physically relevant in connection to graphene antidot lattices, as introduced e.g. in [21] and rigorously studied in [3], is the following:
[TABLE]
where is the two-dimensional massless Dirac operator, , , and is a bounded function with support in a compact subset of .
If it has been proved in [3, Theorem 1.1] the existence of a spectral gap near zero for this operator, namely that there exist constants and such that for every and satisfying we have
[TABLE]
Example 2.5**.**
In [11] it has been shown that certain operators of the type as in (2.5), modeling Maxwell operators with periodic dielectric constants, can also have open gaps.
For operators fulfilling Assumption 1, we want to study the effect of random perturbations on the spectral gap .
The random matrix-valued perturbation describing local defects is defined by
[TABLE]
for some , and satisfying Assumption 2 below. The total Hamiltonian is thus
[TABLE]
Assumption 2**.**
(i) The real-valued random variables are independent and identically distributed. Their common distribution is absolutely continuous with respect to Lebesgue measure, with a density such that . We assume that for some finite non-negative and .
(ii) The variables are independent and identically distributed, and they are also independent from the ’s. They take values in with , where is the ball in with radius and centered at the origin.
(iii) The single-site matrix potential is compactly supported with . In addition, is assumed to be continuous almost everywhere, with , where is the space of non-negative Hermitian matrices.
(iv) The density decays sufficiently rapidly near and , i.e.
[TABLE]
[TABLE]
for some .
Remark 2.6**.**
Here are a few comments:
(i) We take as probability space equipped with the product probability measure.
(ii) The periodicity of and , and hypotheses (i) and (ii) imply that the family has a deterministic spectrum in the sense that there exists with probability 1 such that (cf. for example [9, Theorem 4.3, p20]).
(iii) A standard result about trace estimates [25, Theorem 4.1] states that
[TABLE]
with
[TABLE]
where denotes the trace ideal and the associated norm.
If , each . Thus if we obtain that and there exists a constant such that for all and one has
[TABLE]
In order to simplify notation we will sometimes forget about the matrix structure of the various objects and simply write for example instead of taking the maximum over all its components.
Denote for simplicity . We have
[TABLE]
and
[TABLE]
A consequence of (2.4) is that the entries of and those of are globally bounded. Hence, for any bounded interval , there exists a finite constant such that for any and we have:
[TABLE]
If we have that exists as a bounded operator. Then by using both the first resolvent identity to change with and the second resolvent identity to produce a to the left, we find if and that for any compact subinterval of there exists a finite constant such that for any and we have:
[TABLE]
(iv) Hypotheses (i)-(iii) imply that , where is a finite constant depending only on , , and .
(v) As a consequence, the operator is self-adjoint on for any .
(vi) Another useful result is the following. Given a Schwartz function , since , the commutator is bounded. Indeed, we have:
[TABLE]
We denote:
[TABLE]
where means the supremum on of the operator norm associated with the standard Euclidian norm on . Remember that has compact support thus only a finite numbers of terms are different from zero in the above series.
Next, we need an assumption on the almost sure spectrum. In Proposition 2.8 we will give sufficient conditions which make sure that it holds.
Assumption 3**.**
Let be the almost sure spectrum of . Then there exist two constants satisfying such that
[TABLE]
i.e. some new almost sure spectrum appears in the old gap, while a smaller gap still exists.
Due to [17, Theorem 1, §6, p304] we have information on the spectrum not only for almost every but for all .
Definition 2.7**.**
We say that an ergodic family of operators is Kirsch-standard if:
- (1)
is a Polish space and the -algebra contains the Borel sets on . 2. (2)
There is a set with probability one such that is self-adjoint for any and the mapping restricted to is continuous in the sense that if then in the sense of strong resolvent convergence.
Let us briefly show that in our case we deal with a Kirsch-standard ergodic family of operators with . First, is a Polish space as a countable product of Polish spaces when it is equipped with the classical distance on a product of metric spaces. Second, it suffices to show that for any we have when (cf. [24, Theorem VIII.25]).
If , then for all and . Then (assuming for simplicity ):
[TABLE]
As is continuous almost everywhere, the difference in the integral tends almost everywhere to 0 and the integrand is bounded by which is integrable. Using the dominated convergence theorem, we find the desired result.
Note that if takes only discrete values (including the case where it is constant), we do not need the continuity of .
The fact that is a standard ergodic family of operators has the important consequence that (see [17, Theorem 1, §6, p304])
[TABLE]
Hence only depends on the support of the probability distributions. Also, is characterized by the following two propositions which state that under Assumptions 1 and 2 one can tune the parameters in such a way that Assumption 3 holds and some “new” almost sure spectrum appears in the old gap, without closing it though. Moreover, the almost sure spectrum has exactly one (smaller) gap in the given gap of the unperturbed operator. Proofs will be given in Appendix A.
Proposition 2.8**.**
There exist , , and as in Assumption 2 such that satisfies Assumption 3.
Proposition 2.9** (Location of the spectrum in the gap of ).**
Assume the existence of and of Assumption 3. Denote
[TABLE]
Then and .
Our main results on localization are the following.
Theorem 2.10** (Spectral localization).**
Under Assumptions 1, 2 and 3, there exist two constants satisfying and such that is non-empty, dense pure point, with exponentially decaying eigenfunctions.
Theorem 2.11** (Dynamical localization).**
Suppose Assumptions 1, 2 and 3 hold, and denote the two energies of Theorem 2.10. If and has compact support, then for any compact interval ,
[TABLE]
where denotes the spectral projector on the interval for and is the expectation associated to .
Throughout this article, we shall use the sup norm in
[TABLE]
Remark 2.12**.**
Some stronger dynamical localization results will be described in the next section, see in particular the estimate (3.1) which will be proved in Theorem 4.1. In particular, Theorem 2.11 is a straightforward consequence of Theorem 4.1.
3. One method to localize them all: Germinet and Klein’s bootstrap multiscale analysis
Here we briefly explain how Germinet and Klein’s multiscale analysis has to be applied in our setting. More details can be found in [14] and [9].
In this section, denotes an ergodic random self-adjoint operator on .
3.1. Spectral and dynamical localization
Given a set , we denote its characteristic function. For , we denote the characteristic function of the cube of side-length centered at . We recall that . The projection-valued spectral measure of will be denoted by . The Hilbert-Schmidt norm of an operator is denoted by .
Definition 3.1**.**
Let be an ergodic random operator defined on a probability space and an open interval. The different localization properties are the following:
- (1)
The family of operators exhibits exponential localization (EL) in if it has only pure point spectrum in and for - almost every the eigenfunctions of with eigenvalue in decay exponentially in the sense, i.e. for - almost every , for any eigenvalue in and any associated eigenfunction , there exist constants and such that for all , . 2. (2)
exhibits strong dynamical localization (SDL) in if and for each compact interval and with compact support, we have
[TABLE] 3. (3)
exhibits strong sub-exponential Hilbert-Schmidt-kernel decay (SSEHSKD) in if and for each compact interval and there is a finite constant such that
[TABLE]
for all , , the supremum being taken over all Borel functions of a real variable, with , and is the Hilbert-Schmidt norm.
Other types of localization are presented in [9] but they are all implied by (SSEHSKD). Note that (SDL) is also implied by (SSEHSKD).
As in [9], we define (resp. ) as the set of for which there exists an open interval such that exhibits exponential localization (resp. strong sub-exponential Hilbert-Schmidt kernel decay) in .
3.2. Generalized eigenfunction expansion
Let . Given , we define the weighted spaces as
[TABLE]
The sesquilinear form
[TABLE]
where and is the duality map.
We set to be the self-adjoint operator on given by multiplication by the function ; note that is bounded.
Property 3.2** (SGEE).**
We say that an ergodic random operator satisfies the strong property of generalized eigenfunction expansion (SGEE) in some open interval if, for some ,
- (1)
The set
[TABLE]
is dense in and is an operator core for with probability one. 2. (2)
There exists a bounded, continuous function on , strictly positive on the spectrum of such that
[TABLE]
Definition 3.3**.**
A measurable function is said to be a generalized eigenfunction of with generalized eigenvalue if and
[TABLE]
As explained in [9], when (SGEE) holds, a generalized eigenfunction which is in is a bona fide eigenfunction. Moreover, if is the spectral measure for the restriction of to the Hilbert space , then -almost every is a generalized eigenvalue of .
3.3. Finite volume operators and their properties
We remind the reader that throughout this article we use the sup norm in : . By we denote the open box of side centered at :
[TABLE]
and by the closed box. We define the boundary belt as
[TABLE]
We will write when a smaller box is completely surrounded by the belt of a bigger box . More precisely, this means that if and we have .
Given a box , we define the localized operator
[TABLE]
where we denote . This operator is a self-adjoint unbounded operator on .
We can then define the resolvent of and its spectral projection.
Definition 3.4**.**
We say that an ergodic random family of operators is Klein-standard [9] if for each , there is a measurable map from to self-adjoint operators on such that
[TABLE]
where and define the ergodicity:
[TABLE]
It is easy to see that the family (3.2) of localized operators makes a Klein standard operator.
We now enumerate the properties which are needed for multiscale analysis to be performed, yielding thus various localization properties.
Definition 3.5**.**
An event is said to be based in a box if it is determined by conditions on the finite volume operators .
Property 3.6** (IAD).**
Events based in disjoint boxes are independent.
The following properties are to hold in a fixed open interval .
Property 3.7** (SLI).**
Denote by the characteristic function of and . We also denote the characteristic function of . Then for any compact interval there exists a finite constant such that, given , , , , , with , then for -almost every , if with we have
[TABLE]
Property 3.8** (EDI).**
For any compact interval there exists a finite constant such that for -almost every , given a generalized eigenfunction of with generalized eigenvalue , we have, for any and with , that
[TABLE]
Property 3.9** (NE).**
For any compact interval there exists a finite constant such that, for all and ,
[TABLE]
Property 3.10** (W).**
For some , there exists for each compact subinterval of a constant such that
[TABLE]
for any , , and .
Property 3.11** (H1(, , )).**
[TABLE]
3.4. Multiscale analysis and localization
In this paragraph, we recall two very powerful results of Germinet and Klein which give us localization properties.
Definition 3.12**.**
Given , and with , we say that the box is -regular for a given if
[TABLE]
In the following, we denote
[TABLE]
Definition 3.13**.**
For , , , and an interval, we denote.
[TABLE]
The multiscale analysis region for is the set of for which there exists some open interval such that, given any , and , , there is a length scale and a mass so if we set , , we have
[TABLE]
for all , , with .
Theorem 3.14** (Multiscale analysis - Theorem 5.4 p136 of [9]).**
Let be a Klein-standard ergodic random operator with (IAD) and properties (SLI), (NE) and (W) fulfilled in an open interval . For being the almost sure spectrum of and for as in (3.4), given , for each there exists a finite scale bounded on compact subintervals of such that, if for a given we have (H1)(, , ) at some scale with , then .
Theorem 3.15** (Localization - Theorem 6.1 p139 of [9]).**
Let be a Klein-standard ergodic operator with (IAD) and properties (SGEE) and (EDI) in an open interval . Then,
[TABLE]
4. Application to our setting
We will now show that all the conditions listed in the previous Section hold true in our setting.
Theorem 4.1**.**
Let be the operator defined by (2.6) obeying Assumptions 1-3. Then, we have (IAD) and there exist two constants satisfying and such that (SLI), (EDI), (NE), (W), (SGEE) and (H1(, ,)) for and large enough are satisfied on . Therefore, we have the localization properties (EL) and (SSEHSKD) on the interval .
Proof.
(IAD) is a direct consequence of the independence of random variables stated in Assumption 2 (i) and (ii).
To show (SLI), let , , , , and be as in Property 3.7 and consider, for and a function which has value 1 on and 0 outside of and whose gradient has norm smaller than 3. Pick such that .
Using Assumption 2(iii) on the support of leads us to the identity and then we get:
[TABLE]
where
[TABLE]
is bounded according to Remark 2.6 (vi).
With similar support arguments, we have and together with the identity (4.1) we get the geometric resolvent equation:
[TABLE]
Multiplying (4.2) from the left by , from the right by , writing , , and taking the norm of the adjoints, yields the estimate (3.3).
For (EDI), we have, for a generalized eigenfunction of with associated generalized eigenvalue :
[TABLE]
But, denoting , we have,
[TABLE]
Then,
[TABLE]
Using the facts that and , we get
[TABLE]
which, through operations similar to the ones of the proof of (SLI), will give the desired result.
(NE) and (W) will be proved in Paragraph 4.1. (H1()) for good values of the parameters will be proved in Paragraph 4.2.
Let us now give the proof of (SGEE). For the first part, we see that which is dense in and a core for for any .
For the second part we pick as in Section 3.2, being defined by the multiplication with where . Then we will show that for some :
[TABLE]
with almost surely independent of , which will imply (SGEE) for any interval , with .
To this purpose, it suffices to show that is Hilbert-Schmidt with a Hilbert-Schmidt norm almost surely independent of .
For some , let defined on . By using the fact that the multiplication by commutes with potentials, we find that for any
[TABLE]
for some bounded operator independent of . We can then extend on .
Then, for ,
[TABLE]
where . As is bounded independently of and , we see that for large enough so is invertible. Moreover,
[TABLE]
By a standard argument one can prove that the following identity holds:
[TABLE]
which together with (4.3) implies that:
[TABLE]
The idea is to write the operator as a product of factors, each of them belonging to . In order to simplify notation, let us denote by and with . Then we get by induction:
[TABLE]
For each , we can put and by (4.4) we get:
[TABLE]
where is a bounded operator with a norm independent of . The function belongs to when . Thus reasoning as in Remark 2.6(iii) we have that is Hilbert-Schmidt with a norm which is independent of . This proves and thus concludes the proof of Theorem 4.1. ∎
4.1. Proof of (W) and (NE)
Let . We denote . In order to alleviate notations, we denote , and the spectral projector. We prove in this paragraph properties (W) and (NE) for the operator , namely we establish the following theorem.
Theorem 4.2** (Wegner estimate).**
Suppose Assumptions 1 and 2(i)-(iii) hold true, and, for and , we denote . For any compact subinterval of , there exists a constant such that for all
[TABLE]
Remark 4.3**.**
This estimate trivially implies (NE). By Chebishev’s inequality, it also leads to (W) with .
The resolvent of in will be denoted . Let us fix some and denote . The following proposition holds true:
Proposition 4.4**.**
Assume that belongs to a compact in the gap. Let us denote
[TABLE]
given a -tuple for being an even integer larger than . Under Assumptions 1 and 2 (iii) on , there exists a constant such that for all we have
[TABLE]
For the proof of this Proposition we need the following two Combes-Thomas like lemmas which are proved in Appendix B.
Lemma 4.5**.**
Fix a compact interval . There exist two constants and such that, for all and any pair of bounded functions and with for and compactly supported, such that the distance between their supports is , we have:
[TABLE]
The second lemma is a similar estimate with trace norm:
Lemma 4.6**.**
Let . With the same notation as in Lemma 4.5, assume that . Then the operator is trace class and furthermore, there exist two constants and such that for all and all , satisfying the hypotheses in Lemma 4.5 we have
[TABLE]
The proof of these two lemmas are given in Appendix B.
Proof of Proposition 4.4.
The inequality (4.6) is also proved in [2, Proposition 7.2] for Schrödinger operators under the assumptions that (4.7) and (4.8) hold true, although the authors do not consider moving centers .
We omit here details of the proof since it is a straightforward adaptation of the proof of [2, Proposition 7.2] once Lemma 4.5 and Lemma 4.6 are given.
The main ingredient behind the proof is that has compact support, thus keeping one index fixed, say , the operator is trace class and is bounded by a numerical constant, uniformly on compacts in the gap. Note that if any two consecutive and have overlapping supports then we use that , otherwise we use (4.8) and control the series through the exponential localization. In the end we use that the number of terms is proportional with the Lebesgue measure of . ∎
For the proof of Theorem 4.2, we will use the following spectral averaging result proven in [8, Corollary 4.2].
Proposition 4.7**.**
Let a family of self-adjoint operators on a Hilbert space where is bounded and satisfies
[TABLE]
for some and some bounded, self-adjoint operator . Let be the spectral family for . Then, for any borelian and any function compactly supported, ,
[TABLE]
Proof of Theorem 4.2.
The proof is very similar to the one in [2] though it requires few technical changes. For the sake of completeness, we give it here.
Let be a compact subinterval of . We recall that if , , we have
[TABLE]
where . When there is no ambiguity, we will drop the dependence in in the notations. Henceforth,
[TABLE]
Thus, noting that is a positive trace class operator,
[TABLE]
and since , we get
[TABLE]
A first consequence of (4.10) is, by the Hölder inequality with as in Proposition 4.4 and ,
[TABLE]
where denotes the norm in the Schatten class .
Since , according to (2.7) we obtain that there exists a constant such that for all we have
[TABLE]
where is defined by (2.8).
From this inequality, the fact that (a consequence of the fact that the non-zero eigenvalues of the spectral projector are equal to one) and (4.11), we obtain:
[TABLE]
for all which in particular ends the proof of Property (NE).
Now, we use the adjoint of formula (4.9) to derive
[TABLE]
which implies
[TABLE]
Hence, by (4.10) and , this yields
[TABLE]
If , one continues this procedure and writes:
[TABLE]
One has by Hölder’s inequality,
[TABLE]
Taking the expectation and again using Hölder’s inequality, inequality (4.12) and (4.13), one can bound the expectation of the left hand side of (4.16) by , where is a constant independent of , and . Consequently, the latter equations (4.14)-(4.16) imply
[TABLE]
If , one repeats this procedure again. Finally, one obtains
[TABLE]
where is independent of , and .
To estimate the first term on the right hand side of (4.17), we expand the potential . In the rest of this proof, by abuse of notation, we shall denote by . Moreover, we fix the values of all ’s, and expectation will be taken only with respect to the ’s. For each -tuple of indices , we define:
[TABLE]
By using Hölder’s inequality for trace ideals [25, Theorem 2.8],
. In terms of this operator, using cyclicity of trace, the first term on the right side of (4.17) becomes
[TABLE]
Since is compact, we write it in terms of its singular value decomposition. For each multi-index , there exists a pair of orthonormal bases, and , and non-negative numbers , all independent of , such that
[TABLE]
Inserting the representation (4.19) into (4.18) and expanding the trace in , we obtain
[TABLE]
where . Recalling that , we bound the -sum in (4.20) by
[TABLE]
From the independence of the ’s, the spectral averaging result (Proposition 4.7) applied to each term in (4.21) gives for the first term:
[TABLE]
where is finite, independent of , and independent of according to Assumption 2(i). From inequalities (4.18), (4.21) and (4.22), we obtain as upper bound for the first term on the right hand side of (4.17):
[TABLE]
Applying Proposition 4.4 we can bound the above series by a constant times the Lebesgue measure of , and this ends the proof of the Wegner estimate and of the theorem. ∎
Remark 4.8**.**
In order to apply Theorem 3.14 ([9, Theorem 5.4, p136]) for proving Theorems 2.10, 2.11 and 4.1, it would be enough to have a Wegner-like estimate with raised to some high power. Thus we could have shown directly using (2.7) and Hölders’s inequality for trace ideals that
[TABLE]
In this way we would have avoided the use of Proposition 4.4.
4.2. Proof of (H1(,,))
In this subsection, we want to prove
[TABLE]
for close enough to band edges , some and large enough. As in [2], we first prove that, for small, with good probability. We can then apply Lemma B.1 to get exponential decay of the resolvent at energies . We finally verify for any , and for some depending only on , , , , , and .
As in the previous section, we define for some . We denote , , .
Lemma 4.9**.**
Let for some . Then .
Proof.
It is (2.9). See also [2, Lemma 5.1] for an alternative proof that can easily be adapted for first order operators. ∎
Proposition 4.10**.**
Let and . Assume that
[TABLE]
Then we have
[TABLE]
and
[TABLE]
Proof.
We only prove the first inequality, the proof of the second one is similar.
Assume that the statement is false, i.e. there exist some and some values of the parameters and such that has an eigenvalue . If one of the coupling constants is negative, say , then let us consider the family
[TABLE]
We have that is a self-adjoint analytic family of type (A) (cf. [16, VII,§2]) and all its discrete eigenvalues in the interval can be followed real-analytically as functions of . Also, we may construct real analytic eigenvectors for each of them. The Feynman-Hellmann formula and Assumption 2(iii) give:
[TABLE]
which shows that will continue to have eigenvalues in up to . By induction, we may replace all the negative ’s with zero, not changing the fact that the new realisation of , this time with , still has at least one eigenvalue .
Now let us also assume that and consider the analytic family of type (A) , for in a small real neighbourhood of . Since has finite multiplicity, say , there are at most functions analytic in near such that . Let be a real analytic eigenfunction for , with for real and small. Applying the Feynman-Hellmann formula we find that for such that
[TABLE]
We now assume , and fix
[TABLE]
We see that by definition of the condition is satisfied on the interval
Upon integrating (4.24) over and using that we get:
[TABLE]
We have to bound the minimum of the distances. As we always have the following order
[TABLE]
there are only two cases:
- •
either the minimum is and then it is equal to .
- •
or the minimum is and then it is equal to . As , this distance is greater than . As , the distance is larger than . Using Lemma A.2 with and , we must have so the distance is larger than .
Thus the minimum is larger than . Then using the inequality with from (4.25) we have
[TABLE]
which leads to and thus to a contradiction. ∎
Corollary 4.11**.**
For , we have
[TABLE]
and
[TABLE]
with probability larger than
[TABLE]
Proof.
The probability that
[TABLE]
is given by
[TABLE]
The conclusion follows by using for and . ∎
We can now prove hypothesis .
Proposition 4.12**.**
Let , be two functions with and such that . Define . For as in Assumption 2 (iv), consider any such that . Then there exists such that for all and ,
[TABLE]
with probability larger than .
Proof.
Pick . For large enough we have , hence, using Assumption 2(iv), Corollary 4.11 and the fact that yields
[TABLE]
for large enough.
Now consider any realisation of which obeys and let . We now apply Lemma B.1 with , knowing that, for and as defined in Lemma B.1, we have . We get
[TABLE]
The result follows by taking large enough. ∎
Property comes directly from the previous proposition as and satisfy its hypotheses and when for some finite .
Appendix A Spectrum location
A.1. Proof of Proposition 2.8
Lemma A.1**.**
Let be a bounded, compactly supported, non-negative matrix valued multiplication potential which is not identically zero. Let be defined by (2.5) and define
[TABLE]
Then there exists some with such that has at least one discrete eigenvalue in .
Proof.
The perturbation given by is relatively compact to , hence due to the Birman-Schwinger principle we have that is a discrete eigenvalue of if is an eigenvalue of . The family of self-adjoint operators cannot be identically zero for because this would lead to
[TABLE]
hence and , contradiction. Now let be such that has a non-zero real eigenvalue . Then choosing we obtain that has a discrete eigenvalue at . ∎
A slightly more general version of the following lemma can be found in [16, V,Theorem 4.10]
The Hausdorff distance between two real subsets is defined as
[TABLE]
Lemma A.2**.**
Let and be two self-adjoint operators acting on the same Hilbert space and having the same domain, such that is bounded. Then
[TABLE]
Proof.
Let such that . Then the operator has norm less than and is invertible with a bounded inverse. Thus
[TABLE]
is also invertible with a bounded inverse, which shows that . In other words, no element of can be located at a distance larger than from , which implies:
[TABLE]
By interchanging with , the proof is over. ∎
Lemma A.3**.**
Using the notation and result of Lemma A.1, let and consider the operator as in (2.6). With the notation introduced in Assumption 2(i), let . Then there exists small enough such that Assumption 3 is satisfied if and are replaced respectively by and .
Proof.
For the sake of simplicity, let us assume . According to Lemma A.1, we know that some belongs to the spectrum of . Using (2.9), one can show that also belongs to the spectrum of for belonging to a set of measure one, hence belongs to the almost sure spectrum .
Now consider the family with . By multiplying the potential with we effectively reduce the support of to . Because is uniformly bounded for all , we know from Lemma A.2 that the spectrum varies Lipschitz continuously with , uniformly in .
We now want to prove that the almost sure spectrum is continuous in in the Hausdorff distance. Let and fix . There exists some such that . By the Weyl criterion, there exists of norm one such that
[TABLE]
Then there exists some large enough such that obeys
[TABLE]
This inequality implies by the same Weyl criterion that the operator must have at least one point of its spectrum such that . Now using Lemma A.2 we can find some such that for every obeying , the Hausdorff distance between the spectra of and is less than thus there must exist in such that . Finally, via Kirsch’s argument (2.9) one can prove that belongs to the almost sure spectrum of ; in other words,
[TABLE]
This implies in particular that the almost sure spectrum of must converge (as a set) to the spectrum of when tends to zero. Thus if is small enough, then at least one gap must appear in the almost sure spectrum of , which due to the same continuity, it must still have some non-empty component in the old gap . ∎
A.2. Proof of Proposition 2.9
Under the conditions of Lemma A.3 we know that there exists a gap in the almost sure spectrum of , and at the same time, either or is non-empty.
Now assume that is not empty. Let be the supremum of this set (note that since is closed and we must have ). If we consider the family and denote by its almost sure spectrum. As a set, varies continuously with in the Hausdorff distance as we saw in Lemma A.3. Denote by the supremum of . Because , and varies continuously with , we conclude that covers the interval . Finally, since , we conclude that , hence no other gaps can appear in this interval.
Appendix B Combes-Thomas estimates
This section is dedicated to Lemma 4.5 and Lemma 4.6. The proof of Lemma 4.5 follows closely the strategy [5, Proposition 5.2].
Lemma B.1**.**
Let be a symmetric and matrix-valued bounded potential, and let where is like in (2.5) and is a bounded coefficient operator as in (2.4). Assume that has a gap in its spectrum, containing [math]. Consider and two compactly supported functions such that . For define
[TABLE]
For let
[TABLE]
Then there exists a constant such that for all we have:
[TABLE]
Proof.
Let and define . For , we define on the (non self-adjoint) operator
[TABLE]
The operator is closed on the domain of . Let with norm . We denote and , where are the spectral projectors for , and we remind that .
We have
[TABLE]
We observe that the length of is bounded by a number independent of . Let where is independent of both and , and small enough so that:
[TABLE]
We then have
[TABLE]
Thus, is invertible for and
[TABLE]
uniformly in . Hence,
[TABLE]
The central factor is bounded by . By taking to zero, the first factor is bounded by and the third factor by . We have thus proved the lemma. ∎
Proof of Lemma 4.5.
Without loss of generality we may assume that the distance between the supports obeys . Let be a unit cube in . Let be the characteristic function of the cube , . We have
[TABLE]
The sum over only contains finitely many terms because is compactly supported. For any given such pair and we apply Lemma B.1 in which we choose . We observe that in this case and since we also have . Thus (B.1) leads to
[TABLE]
where and are constants depending on the interval . Then we can sum over for every fixed and we are done. ∎
We are ready to prove Lemma 4.6.
Proof of Lemma 4.6.
Using the same notation as in the proof of Lemma 4.5, the strategy is to show the existence of two positive constants and such that in the trace norm we have:
[TABLE]
Without loss of generality we may assume that and . Then the pairs and which give a non-zero contribution must obey .
We now consider smooth and compactly supported functions which obey the following conditions: , if , and the support of the ”largest” function is contained in the hypercube centered at with side-length . In particular, the support of and the support of the derivatives of are disjoint, and also .
Denote . We have and
[TABLE]
and repeating this for all we have:
[TABLE]
Each factor belongs to with a norm which is independent of and . Thus the product is trace class. Moreover, by applying Lemma B.1 to the pair and with we obtain and
[TABLE]
This proves (B.3). Since there is a finite number of ’s which give a non-zero contribution in (B.2), this number being proportional with the Lebesgue measure of the support of , the proof is over. ∎
Acknowledgment
J.-M.B. is grateful to P. Müller for sharing the reference [23] and for fruitful discussions. It is a pleasure to thank the REB program of CIRM for giving us the opportunity to start this research. H.C. acknowledges the support of the Simons-CRM Scholar-in-residence program during the preparation of this work.
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