On the localization regime of certain random operators within Hartree-Fock theory
Abstract
Localization results for a class of random Schrödinger operators within the Hartree-Fock approximation are proved in two regimes: large disorder and weak disorder/extreme energies. A large disorder threshold analogous to the threshold obtained in [J. Schenker, Lett. Math. Phys, Vol 105, 1 (2015)] is provided. We also show certain stability results for this large disorder threshold by giving examples of distributions for which converges to , or to a number arbitrarily close to it, as the interaction strength tends to zero.
I Introduction
In recent decades there has been intense activity regarding mathematical aspects of disordered systems. In the Anderson model in dimension two or higher, there is an extensive literature regarding localization in the regimes of large disorder or at spectral edges. In this context, proofs either follow the strategy of the multiscale analysis, see Bourgain-Kenig ; Carm-Klein-Mart ; Ding-Smart ; Fr-M-S-S85 ; Fr-Spenc ; Germ-Hislop-Klein ; GKBootstrap ; Kir-Stol-Stolz ; vonD-K and also the surveys Kirschsurv ; Klein-surv , or the method of fractional moments, dating back to A-Molc ; Aiz-weakdis and further developed in both discrete and continuous settings A-S-F-H ; Aiz-Elg-N-S-S and also in the context of non-monotone potentials Elg-Taut-Ves ; E-S-S , see also the survey Stolz-surv and the monograph A-W-B . Localization in the context of weak disorder and existence of the so-called Lisfshitz tails were also extensively studied, see Aiz-weakdis ; Elgart-LT3d ; RojasM-Geb1 ; RojasM-Geb2 ; Klopp-Lif ; Klopp-Nak ; Wang-univ and references therein. For results on complete localization in one dimension using large-deviation techniques we refer to Jit-Z ; Bucaj1dloc .
In the past years, there has been a number of developments in the context of many-body disordered systems such as systems with a finite number of particles A-W-Mult ; Chul-Suh ; Chu-Suh-ind ; the quantum AR-N-S-S ; H-S-Stolz ; Klein-Perez and E-K22 ; E-K-S-2 ; E-K-S-1 spin chains; systems of hardcore particles Beaud-W ; harmonic oscillators in the presence of disorder N-S-S-harmonic ; particle-oscillator interactions S-M-Holst . Unlike in the single-particle Anderson-type models, where the notions of localization aimed at are usually spectral or dynamical localization, the challenges in the context of true many-body quantum systems start at defining the correct objects and notions of localization for each model.
One alternative to explore interactive quantum systems while remaining closer to the single-particle Schrödinger operator setting is to approximate the true many-body Hamiltonian by an effective one, as in the case of mean field theories and the Hartree/Hartree-Fock approximations which are widely studied beyond the setting of disordered systems B-Lieb-S ; Bene-Porta-Schlein ; Canc-Lab-Lew ; CHENN2022109702 ; Hainzl-Lew-Spa ; Lah-1 ; Lieb-Simon .
In the disordered setting, Anderson localization in the Hartree-Fock approximation was first studied in Duc . There, through the multiscale analysis technique, spectral localization was obtained in the presence of a spectral gap at both large disorder and at spectral edges. Recently in M-S localization properties of the disordered Hubbard model at positive temperature within the Hartree-Fock approximation have been established via the Aizenman-Molchanov fractional moment technique. There, exponential dynamical localization ( in fact, decay of eigenfunction correlators) is shown to hold at large disorder in dimension and at any disorder in dimension provided the interaction strength is sufficiently small. No assumption on the existence of a spectral gap is made but, in contrast, the interactions are modelled at positive temperature. The present manuscript is devoted to localization properties of random operators in the form
(I.1) |
where are independent, identically distributed random variables and is a multiplication operator implicitly defined by
(I.2) |
Here will be assumed to decay sufficiently fast ( see 1-7 for the precise assumptions) with respect to a metric , , and is an analytic function on a strip which is bounded. It is worth noting that the above setting allows for the decay of to be of polynomial type. The above model is somewhat analogous (in the Hartree-Fock setting) to models in the single-particle setting with fast decaying potentials which still exhibit monotonicity properties (for instance, the ones studied in Kir-Stol-Stolz ). In the particular case where is the Fermi-Dirac function at temperature and a chemical potential and ( with the Kronecker delta) (I.2) simplifies to operators already studied in M-S . There for a fixed , dynamical localization is shown in any dimension provided and for certain constants and which depend on and but a more concrete estimate for was not pursued there. In this note, we generalized the large disorder result of M-S to the operator (I.2), obtain a novel result of localization at weak disorder/extreme energies and, moreover, study the question of stability of the large disorder threshold under ‘weak’ interactions, inspired by the analysis of Schenkl . In particular, it is proven here that there is a large disorder threshold such that the operators given by (I.2) exhibit dynamical localization provided as long as is sufficiently small. Moreover, we show that as where is the solution of the transcendental equation
(I.3) |
with the connectivity constant of . For the uniform distribution in , in which case , this value of was obtained for the Anderson model in Schenkl and coincides with Anderson’s original prediction in Anderson . To the best of our knowledge, in arbitrary dimension in (I.3) is the best rigorous large disorder threshold proved with current methods. It is worth noting that letting formally in (I.2) we obtain the Anderson model .
We now comment on other technical merits of the present work, for further technical aspects we refer to section II.1 below. Our first observation is that even for the non-interacting Anderson model , the fractional moment method requires the random variables to have a density which is “sufficiently regular". Thus, it is to be expected that a direct application of this technique to interacting models, which is the approach adopted here and also in M-S , will require further regularity of . The previous paper M-S covers a large class of probability distributions with by making use of the symmetry and decay properties of the Fermi-Dirac function when in order to obtain certain improved Combes-Thomas bounds. Such bounds reflect decay of the effective potential at a given site when the local potential is changed at a site . However, such bounds appear not to be available in the generality studied here. In fact, they seem not to be available even when one restricts (I.2) to the case of nearest neighbor lattice fermions, i.e., when if and only if where and thus with indicating that and are nearest neighbors on . The key observation surrounding the present paper is that there is a trade off between the regularity/decay properties of on the real line, the decay properties of the interaction kernel and the density . Namely, by reducing the class of probability distributions covered by our main result, we are able to include interactions of a much longer range, including the case where only decays in an algebraic fashion and where is bounded of a strip but does not necessarily decay as . In conclusion, even though the methods employed here to obtain the a-priori bound on fractional moments of the Green’s function follow the general scheme of M-S , in order to prove our stability result, we need to keep an explicit dependence on all parameters involved and now have the inclusion the decay rate of as well. Once an a-priori bound on fractional moments of the Green’s function is obtained, we follow the approach of Schenker in Schenkl in order to get the best large disorder threshold which seem to be available with current methods which turns out to converge to when .
This paper is dedicated to Abel Klein in occasion of his 78th birthday. Klein’s contributions to the field go well beyond the aforementioned works and can hardly be overstated. Certain aspects of the present work were also inspired by Klein’s efforts. For instance, the idea of studying distributions near a suitable chosen density (for which explicit calculations are available) used below in assumption 6 is analogous to Acosta-Klein , where analyticity of the density of states on a strip is shown for distributions sufficiently close to the Cauchy distribution. Moreover, throughout the note, Combes-Thomas type bounds for kernels of analytic functions of are used extensively. In GK-CT such bounds are obtained in great generality which provides hope for future extensions of the results below.
II Model, Statement of the main results and proof strategies
This note concerns random operators of the form
(II.1) |
acting on as follows:
-
1.
for each , i.e. is the adjacency operator of .
-
2.
for each where are independent, identically distributed random variables with a bounded density .
-
3.
The effective potential is a multiplication operator implicitly defined by
(II.2) We impose the following conditions on and .
-
4.
There exists such that is an analytic function on the strip
and bounded on its closure . Moreover, we assume that .
-
5.
The values are real numbers for all and
(II.3) for constants and and some metric for which there exists such that
(II.4) -
6.
We also assume that and that for some and
(II.5) and
(II.6)
Remark 1
Assumptions 1-6 suffice for the first result of this note, namely, localization at large disorder given by Theorem 1 below, and also for the stability bounds on the large disorder threshold of Corolary 2. It is worth observing that assumption 6 holds, for instance, for the Cauchy distribution and also for the (negative) exponential distribution.
For the results of localization at weak disorder/extreme energies we will make the following additional requirement.
-
7.
We further assume that for some where
(II.7) for some .
Remark 2
Intuitively speaking, assumption 7 means that is near the (negative and two sided) exponential distribution with density and . With the help of the mean value theorem and Young’s inequality, one may check that this assumption applies to densities of the form with , , and sufficiently small depending on and .
Working with finite volume restrictions of both and also will turn out convenient thus we let and
(II.8) |
where and is the projection onto . We will often write
(II.9) |
to denote the “full potential" at site . It will be shown below in Lemma 8 that under assumptions 1-6 the conditional distribution of at specified values of has a density which is bounded with an upper bound independent of the parameters and . This upper bound is denoted herein by and the conditional density by . We also recall the definition of the eigenfunction correlators for an operator :
(II.10) |
where the supremum is taken over Borel measurable functions bounded by one and supported on the interval . In case we simply write . In what follows we denote by the eigenfunction correlators of for and by the expected value of with respect to the probability space in question.
Our first result is the following.
Theorem 1
Under assumptions 1-6 there exist and such that for all and we have that
(II.11) |
for some and independent of and . Moreover, satisfies
(II.12) |
where is the conective constant of and is given by
(II.13) |
Remark 3
Theorem 1 above extends to the present context a result of Schenker Schenkl , who obtained the large disorder threshold which solves
(II.14) |
for the Anderson model with a uniformly distributed potential on .
We also show that is close to in a quantified fashion.
Before stating our second theorem we let, for each
(II.15) |
(II.16) |
and
(II.17) |
As we shall see below, under assumptions 1-7 the measure is -moment regular in the sense of (A-W-B, , Definition 8.5) meaning that for all . We also define the Green’s function of at by
(II.18) |
and let, for , and be the Green’s function of and , respectively:
(II.19) |
We emphasize that the effective potential is for both of the above operators. Finally, we denote by the Green’s function of the “free” operator , namely
(II.20) |
We are now ready to state our second Theorem which yields localization at weak disorder/extreme energies provided the interaction strength is not too large relative to the remaining parameters.
Theorem 3
Given there exist and such that whenever and we have that
(II.21) |
for some and independent of and . Moreover, we have that
(II.22) |
where
(II.23) |
Remark 4
By the Combes-Thomas bound (A-W-B, , Theorem 10.5), Theorem 3 is applicable when . In particular, since it was assumed that , this yields a non-trivial result for all . We choose the above formulation for general for future reference, as in more general settings localization at weak disorder may be established away from the spectrum of the deterministic part of , see (A-W-B, , Theorem 10.4) and comments therein.
II.1 Proof strategy: discrete subharmonicty bounds
The proofs of Theorems 1 and 3 follow the general scheme of the Aizenman-Molchanov fractional moment method A-Molc ; Aiz-weakdis and further refinements of their technique, in particular the one in Schenkl , combined with tools from M-S (and a few technical improvements on it). Their approach requires the random potential to be sufficiently regular (even though it allows for certain singularities) which is the case in the Anderson model given by assumptions 1 and 2. The first difficulty in the present work is that the full random potential is of the form thus and are correlated for all values of and and, a-priori, their regularity is unknown. While correlations are not necessarily a problem for the fractional moment technique, as it is well-known and already stated in the Aizenman-Molchanov original work A-Molc , in order to prove localization one needs at least some regularity on the conditional distributions of , for each , when the remaining variables are specified. Moreover, the involved bounds should be uniform in . At an intuitive level, such requirement on the conditional distributions amounts to the variables and being less and less correlated as so that some of the regularity of is persists in the conditional distribution of . The technical implementation of the above reasoning essentially consists of two main parts, each of them having of a few steps. The first part is completely deterministic and aims at showing that, in terms of the metric in which , the effective potential is a quasilocal function of the random variables . The second part involves applying the fractional moment method in the spirit of Schenkl once the regularity of the is determined.
Before stating the main steps of the proof, let us remark that for simplicity we do not always mention finite-volume restrictions in this sketch. Nonetheless, their introduction is technically important for the arguments, as it will be clear later in the note. Moreover, each point of the outline below is carried out in the appropriate smallness regime (cf. Theorems 1 and 3).
-
(i)
Step 1: Show that
holds for every , with , independent of and . This will allow us to make the change of variables and guarantee that the map is a diffeomorphism in for each finite set .
-
(ii)
Step 2: Fix and . Let be a rank-one perturbation of at and define to be such that for all . Then for some and we have that
(II.24) This step, along with assumption 6 will allow us to control fluctuations of the density which naturally appear when computing the conditional density
-
(iii)
Step 3: Prove that
(II.25) This step will help us control fluctuations in the Jacobian of the above change of variables which also appear in the expression for .
Once the above steps are completed, the second part of the proof makes use of probabilistic techniques.
- (iv)
-
(v)
Step 5: Complete the proof using the fractional moment technique.
While the overall strategy outlined above is similar to the one in M-S there are some key technical differences. Firstly, by obtaining the cancellation directly on (iii) we are able to avoid having to bound the second derivatives which shortens the proof quite a bit, especially for the model studied here where may be non-local. Secondly, in Step 4 the observation that further regularity of can be obtained under assumption 7, which ultimately yields the localization at weak disorder/extreme energies result, is also new. A third difference is present in Step 5. Namely, while localization at large disorder was obtained in (M-S, , Theorem 2), in the case where , the explicit dependence of the large disorder threshold on the remaining parameters is not given (although it can certainly be inferred from the proof). Here we provide a self-consistent equation for the large disorder threshold in (II.12). Moreover we show that under assumption 7 this threshold is somewhat sharp from the point of view of what is currently known for the Anderson model from Schenkl . Indeed, within the class of exponential distributions, we show that the difference between the large disorder threshold of the non-interactive setting ( cf. (II.14)) and given by (II.12) can be made arbitrarily small when the interaction strength tends to zero.
Turning to the question of how to show the quasilocality bounds in Steps (i)-(iii), the following Lemma will be useful since and, by extension, its partial derivatives are only implicitly defined and hence the desired control of them can only be achieved via inequalities of self-consistent nature.
Lemma 4
(A-W-B, , Theorem 9.2) Let be a countable set and be given by with and
(II.26) |
Let and be positive functions such that
(II.27) |
Then, any which satisfies
also obeys the bound
(II.28) |
The first instance where Lemma 4 is applied is in Step 1 with the choice
(II.29) |
where is given below in (III.11) and is as in 5. To accomplish Step 2, Lemma 4 is applied to
(II.30) |
with as above. In Step 3, Lemma 4 is applied to
(II.31) |
Finally, in Step 5 Lemma 4 is applied to different functions depending on whether we wish to show decay of the Green’s function in the large disorder or in the weak disorder/extreme energies regime. In the large disorder regime of Theorem 1, thanks to an a-priori bound which follows from Lemma 8 below, Lemma 4 is applied to a fixed letting
(II.32) |
for a suitable and choosing
(II.33) |
In the regime of weak disorder/extreme energies of Theorem 11, Lemma 4 can be applied to
(II.34) |
thanks to Lemma 9 below which implies a decoupling estimate for the Green’s function fractional moments cf. (A-W-B, , Theorems 8.7 and 10.4)
The remainder of this note is organized as follows: in Section III we show the quasilocality bounds of Steps 1 and 2 above, in Section IV we show the cancellation bound of Step 3, in Section V we state and prove the technical Lemmas on the conditional densities .The proofs of Theorems 1 and 3 as well as Corollary 2 are given in Sections VI and VII. In the Appendix we provide some basic facts about existence of the effective potential and norm resolvent convergence of finite volume restrictions to the infinite volume operator.
III First order decay bounds on the effective potential
Let us collect some basic facts which will be repeatedly used in this note. Firstly, if is as above we can write for , where and the Poisson kernel, see (A-G, , Appendix D). In particular, the inequality holds. The formula
(III.1) |
with
(III.2) |
readily follows and is a useful representation for the effective potential. It is shown below that it yields, for each , self-consistent equations for the derivatives which in turn imply the desired exponential decay in Step 1 of the proof strategies given earlier. We introduce such that
(III.3) |
The decay rate in the Lemma below will be dictated by and .
Lemma 5
Proof.
Denote by the projection onto . Using difference quotients, it is immediate to check that
(III.7) |
Taking matrix elements we obtain from (III.2) that
(III.8) |
with
(III.9) |
The above derivatives of the kernel are shown to decay exponentially in as follows. We first rewrite as
(III.10) | ||||
For the operators studied here the Combes-Thomas bound (A-W-B, , Theorem 10.5) yields
(III.11) |
for all satisfying (III.3). Moreover, by (A-G, , Appendix D, Lemma 3) we have the following inequality:
(III.12) |
We remark that the above result, as the usual Combes-Thomas bound, may also be applied to the metric instead of the usual metric of . One then obtains
(III.13) |
By the spectral measure representation and the Cauchy-Schwarz inequality, the right-hand side of (III.13) can be controlled via
(III.14) |
Therefore,
(III.15) |
Keeping in mind assumption 5 and combining (III.1), (III.8) and (III.15) we reach the inequality
(III.16) | ||||
We now apply Lemma 4 with fixed and the choices ,
(III.17) |
(III.18) |
in the regime where , i.e. when
(III.19) |
In this context, introducing the weight function with we reach
(III.20) |
and
(III.21) |
In particular, under the more restrictive assumption
(III.22) |
we find that and thus , finishing the proof.
Given an enumeration of the points in , it readily follows that within the smallness regime described in Lemma 5, the map given by
(III.23) |
is a diffeomorphism.
We are now ready to quantify the change in after resampling. Fix and define for . Then, is interpreted as the “full" potential in with value changed to at . Denote by the random variables for which . In this setting we have the quasilocality result below.
Lemma 6
Let be as in (III.5). Whenever and we have
(III.24) |
IV Second order decay bounds on the effective potential
This section is devoted to the cancellation bounds of Step 3 of the proof outline. From now on throughout the paper we denote by any positive number satisfying (III.3).
Lemma 7
Proof.
With these definitions, letting we reach
Note that by definition of we have that
(IV.4) |
for all . In particular
(IV.5) |
Indeed, (IV.5) follows from (IV.4) and a similar argument to the one in (III.14) with the help of the following Combes-Thomas type bound cf. (M-S, , Lemma 18)
(IV.6) |
applied separately to and .
V A pair of technical lemmas
Fix and . Recall that in (III.23) we have denoted for each with given by (II.8). We also write the above change of variables, i.e
(V.1) |
In the sequel we will abbreviate this by writing
The first result on uniform control of the conditional density of is given below.
Lemma 8
Proof. We note that in the above setting is given by
(V.3) |
Where
(V.4) |
and we recall that
Letting and one has that
(V.5) |
Indeed, (V.5) follows from the inequality (c.f (Simon-trace, , Lemma 3.3)), see (M-S, , Lemma 22). We remark that it suffices to control ratios of the above determinants instead of the ones in (V.4) since the later arise from the inverse change of variables .
We are now ready to estimate the right-hand side of (V.5). Using Lemma 5 we see that whenever we have that
(V.6) |
thus
(V.7) |
by the Combes-Thomas bound. Using Lemma 7 and the inequalities (V.5) and (V.7) we find that
(V.8) |
For each , writing , one concludes from assumption 6 that
(V.9) |
By Lemma 6 it then follows that for
(V.10) |
In particular, under assumptions 1-6 for each fixed we obtain for sufficiently small that if
(V.11) |
then
(V.12) |
finishing the proof of Lemma 8.
Now we shall see that under assumption 7 one may achieve a better control on the conditional densities.
Lemma 9
Proof. To reach the upper bound we follow most of the proof of Lemma 8, obtaining improvements at the very end with help of assumption 7. Observe that, with the choice , equations (V.3)-(V.8) imply the pointwise bound
(V.15) |
where we recall that is given in (III.5) and is independent of . The constant is given in (IV.2) and is proportional to when this number is sufficiently small. Note that by assumption 6 we have for any and :
(V.16) |
Hence from (V.15)
(V.17) |
with . Now we make use of assumption 7 to write with
(V.18) |
and observe that
(V.19) |
c.f. Theorem 3 in A-G and assumption 5. This yields, with ,
(V.20) |
Pick sufficiently small such that if then
(V.21) |
from which we readily obtain, for and
(V.22) |
The lower bound in (i) is analogous. One follows the above process using instead the upper bounds given in (V.8) and (V.10) along with assumptions 6, 7 and (V.3) to reach
(V.23) |
finishing the proof of (i). To prove (ii) we use (V.3) to write
(V.24) |
Where for . The bounds in (ii) then follow as above from (V.10) and (V.8), both applied to , along with assumption 6 and (V.19).
VI Self-avoiding walks and localization: Proof of Theorem 1
It is well known that the conclusion of Theorem 1 follows from the result below, see (A-S-F-H, , Appendix B).
Theorem 10
There exist and (independent of and ) such that whenever and we have that for each
(VI.1) |
for all and certain constants and independent of and . Moreover, solves (II.12).
Proof.
We closely follow the arguments of Schenkl but provide details for the sake of completeness since a few modifications are required to account for the Hartree-Fock setting. Let . We start from the depleted resolvent identity which is valid for :
(VI.2) |
Note that by Lemma 8 we have the local fractional moment bound
(VI.3) |
which is valid for any and , see (A-W-B, , Theorem 8.1). Iterating (VI.2) along a sequence of distinct points in and applying (VI.3) we find that after iterations
where we denote by the set of self-avoiding walks in of length starting at and ending at and by the set of all self-avoiding walks in of length starting at . Therefore, applying (VI.3) once more and denoting we have that
(VI.4) |
We now make use of some facts about self-avoiding walks, see Schenkl and references therein for a more detailed discussion. Recall that the self-avoiding walk correlation function is defined by
(VI.5) |
whenever . The self-avoiding walk susceptibility is defined by
(VI.6) |
where denotes the number of self-avoiding walks of length starting at . We also recall that the conective constant of is
(VI.7) |
In particular, is the radius of convergence of (VI.6). It is also well-known that . It is crucial for our argument that whenever the self-avoiding walk correlation function decays exponentially as . This follows from the inequality
(VI.8) |
valid for and some constant .
Therefore, whenever we have that . In particular, the remainder in (VI.4) satisfies
(VI.9) |
Thus, letting in (VI.4) we find
(VI.10) |
from which we conclude that
(VI.11) |
Finally, to end the proof we determine for which values of one has that . Observe that whenever the only critical point of is which yields
(VI.12) |
Thus if and only if
(VI.13) |
so the critical threshold is . For values of greater than we conclude that there exists for which
(VI.14) |
and . Applying Hölder’s inequality we conclude that (VI.1) holds for any and some and . This is immediate if and follows from (off-diagonal) a-priori bounds for the Green’s function if , see (A-S-F-H, , Lemma B2) and (A-W-B, , Theorem 8.3).
VII Proof of theorem 3 and Corollary 2
Theorem 11
In the setting of Lemma 9, for each the exists , , and (independent of and ) such that whenever and we have that
(VII.1) |
for some . Moreover, we have that
(VII.2) |
where
(VII.3) |
Theorem 11 in turn follows from Lemma 9 along with known results and thus we only provide an outline for how it is proven. Before doing so, we recall some notions of regularity for probability distributions, c.f. A-Molc ; A-W-B which will be relevant in the sequel.
Definition 12
-
(i)
A probability measure on the real line is -regular, with , if for some and
(VII.4) holds for all and .
-
(ii)
A joint probability measure of a collection of random variables is conditionally -regular if the conditional distributions of at specified values of satisfy (VII.4) with uniform values of the constants appearing there.
-
(iii)
If, additionally, for some the conditional expectations of are uniformly bounded:
(VII.5) then the joint probability measure is said to be conditionally -regular.
-
(iv)
has regular -decay for if
(VII.6)
Proof of Theorem 11: Lemma 9 (i) readily implies that has regular decay for all and that for all
i.e. is conditionally -regular for all . Moreover, by Lemma 9 (ii), we have that for any and
in particular we see that is (uniformly) -regular.
Appendix A Appendix
We now provide some results on existence and uniqueness of the effective potentials as well as their regularity with respect to the random variables. Since the statements are mostly immediate generalizations from the ones given in M-S we skip most proofs. We formulate the first of these results for but remark that its finite volume analogue holds similarly.
A.1 Contraction mapping arguments
Let be given by
(A.1) |
We wish to show that there is a unique solution to the equation . For that purpose, we introduce a technical Lemma which may be found in (M-S, , Proposition 12)
Lemma 13
Proposition 14
Whenever for some the map is a contraction. In particular, there is a unique such that . Moreover, the analogue effective potential in finite volume , , is a smooth function of .
We also note that if for each then for each .
A.2 Norm resolvent convergence
Finally, we briefly comment on the convergence of resolvents which allows to extend the results of Theorems 1 and 3 to infinite volume operators. It will be useful to introduce the augumented boundary
(A.4) |
with calculated in the metric of .
Lemma 15
- (a)
-
(b)
For any , with and as above
(A.6) In particular, for each fixed and we have that
(A.7)
Proof. Using (III.1) and the analogous representation for we find
where for
Observe that letting and , for any we have that
where we have used that c.f. Theorem 3 in A-G and assumption 5.
Acknowledgements
Dedicated to Abel Klein in ocasion of his 78th birthday. This work was partially supported by NSF DMS-2000345 and DMS-2052572. R. Matos is thankful to the anonymous reviewer for several remarks which greatly improved the exposition in this note.
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