Feshbach-Schur RG for the Anderson Model

Similar documents
Newton s Method and Localization

Physics 202 Laboratory 5. Linear Algebra 1. Laboratory 5. Physics 202 Laboratory

Clusters and Percolation

ANDERSON BERNOULLI MODELS

Non Adiabatic Transitions in a Simple Born Oppenheimer Scattering System

Introduction to Spectral Theory

Course Description for Real Analysis, Math 156

3 Symmetry Protected Topological Phase

Quantum Mechanics Solutions

Review problems for MA 54, Fall 2004.

Quasi-1d Frustrated Antiferromagnets. Leon Balents, UCSB Masanori Kohno, NIMS, Tsukuba Oleg Starykh, U. Utah

Spectral Processing. Misha Kazhdan

Invertibility of random matrices

Decouplings and applications

Quantum Mechanics Solutions. λ i λ j v j v j v i v i.

Lecture 10. Central potential

A classification of gapped Hamiltonians in d = 1

Physics 221A Fall 2017 Notes 27 The Variational Method

Anderson Localization on the Sierpinski Gasket

Section 9 Variational Method. Page 492

1 Mathematical preliminaries

Renormalization Group: non perturbative aspects and applications in statistical and solid state physics.

DRIFT OF SPECTRALLY STABLE SHIFTED STATES ON STAR GRAPHS

Szegö Limit Theorems With Varying Coefficients. Optimal trace ideal properties of the restriction operator and applications

Delocalization for Schrödinger operators with random Dirac masses

On Many-Body Localization for Quantum Spin Chains

PHY 407 QUANTUM MECHANICS Fall 05 Problem set 1 Due Sep

Brief review of Quantum Mechanics (QM)

Vector spaces. DS-GA 1013 / MATH-GA 2824 Optimization-based Data Analysis.

Advanced Computation for Complex Materials

Efficient time evolution of one-dimensional quantum systems

Gaussian Fields and Percolation

Electrons in a periodic potential

MP463 QUANTUM MECHANICS

The University of Texas at Austin Department of Electrical and Computer Engineering. EE381V: Large Scale Learning Spring 2013.

CHAPTER 6 Quantum Mechanics II

Page 404. Lecture 22: Simple Harmonic Oscillator: Energy Basis Date Given: 2008/11/19 Date Revised: 2008/11/19

SPECTRAL PROPERTIES OF THE LAPLACIAN ON BOUNDED DOMAINS

Topics in Harmonic Analysis Lecture 1: The Fourier transform

Opinions on quantum mechanics. CHAPTER 6 Quantum Mechanics II. 6.1: The Schrödinger Wave Equation. Normalization and Probability

Diffusion of wave packets in a Markov random potential

A Minimal Uncertainty Product for One Dimensional Semiclassical Wave Packets

Eigenvalue statistics and lattice points

2. As we shall see, we choose to write in terms of σ x because ( X ) 2 = σ 2 x.

Invariant measures and the soliton resolution conjecture

Quasi-1d Antiferromagnets

Gabor Frames for Quasicrystals II: Gap Labeling, Morita Equivale

Lecture notes on topological insulators

Physics 342 Lecture 17. Midterm I Recap. Lecture 17. Physics 342 Quantum Mechanics I

MAGNETIC BLOCH FUNCTIONS AND VECTOR BUNDLES. TYPICAL DISPERSION LAWS AND THEIR QUANTUM NUMBERS

THE IMAGINARY CUBIC PERTURBATION: A NUMERICAL AND ANALYTIC STUDY JEAN ZINN-JUSTIN

Physics 137A Quantum Mechanics Fall 2012 Midterm II - Solutions

1 Math 241A-B Homework Problem List for F2015 and W2016

Effective Resistance and Schur Complements

Kosterlitz-Thouless Transition

MATH 829: Introduction to Data Mining and Analysis Clustering II

arxiv: v1 [hep-ph] 5 Sep 2017

Spectral decimation & its applications to spectral analysis on infinite fractal lattices

arxiv: v1 [physics.comp-ph] 28 Jan 2008

Physics 505 Homework No. 1 Solutions S1-1

Molecular propagation through crossings and avoided crossings of electron energy levels

Global theory of one-frequency Schrödinger operators

04. Five Principles of Quantum Mechanics

4 ORTHOGONALITY ORTHOGONALITY OF THE FOUR SUBSPACES 4.1

Physics 221A Fall 1996 Notes 16 Bloch s Theorem and Band Structure in One Dimension

Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015

8.334: Statistical Mechanics II Spring 2014 Test 2 Review Problems

R. Lachieze-Rey Recent Berry-Esseen bounds obtained with Stein s method andgeorgia PoincareTech. inequalities, 1 / with 29 G.

Concentration inequalities for linear cocycles and their applications to problems in dynamics and mathematical physics *

Spinons and triplons in spatially anisotropic triangular antiferromagnet

Quantum wires, orthogonal polynomials and Diophantine approximation

General Exam Part II, Fall 1998 Quantum Mechanics Solutions

8.1 Concentration inequality for Gaussian random matrix (cont d)

Statistical Interpretation

Degenerate Perturbation Theory. 1 General framework and strategy

Hamiltonian approach to Yang- Mills Theories in 2+1 Dimensions: Glueball and Meson Mass Spectra

Heat kernels of some Schrödinger operators

Recall : Eigenvalues and Eigenvectors

Oberwolfach workshop on Combinatorics and Probability

The Particle in a Box

arxiv: v5 [math.na] 16 Nov 2017

Lecture 7: Positive Semidefinite Matrices

CONTINUITY WITH RESPECT TO DISORDER OF THE INTEGRATED DENSITY OF STATES

Scaling analysis of snapshot spectra in the world-line quantum Monte Carlo for the transverse-field Ising chain

(f(x) P 3 (x)) dx. (a) The Lagrange formula for the error is given by

Fractal Weyl Laws and Wave Decay for General Trapping

The Kadison-Singer Conjecture

Hamiltonian approach to Yang- Mills Theories in 2+1 Dimensions: Glueball and Meson Mass Spectra

Physics 127b: Statistical Mechanics. Renormalization Group: 1d Ising Model. Perturbation expansion

Jeffrey Schenker and Rajinder Mavi

GRAPH QUANTUM MECHANICS

4. Supplementary Notes on Time and Space Evolution of a Neutrino Beam

Physics 115C Homework 2

H ψ = E ψ. Introduction to Exact Diagonalization. Andreas Läuchli, New states of quantum matter MPI für Physik komplexer Systeme - Dresden

Lectures on Quantum Gases. Chapter 5. Feshbach resonances. Jook Walraven. Van der Waals Zeeman Institute University of Amsterdam

The 1+1-dimensional Ising model

Problem 1: A 3-D Spherical Well(10 Points)

SVD, Power method, and Planted Graph problems (+ eigenvalues of random matrices)

Quasi-Diffusion in a SUSY Hyperbolic Sigma Model

Contribution from: Springer Verlag Berlin Heidelberg 2005 ISBN

Transcription:

Feshbach-Schur RG for the Anderson Model John Z. Imbrie University of Virginia Isaac Newton Institute October 26, 2018

Overview Consider the localization problem for the Anderson model of a quantum particle moving in a random potential. We develop a renormalization-group framework based on a sequence of Feshbach-Schur maps. Each map produces an effective Hamiltonian on a lower-dimensional space by localizing modes in space and in energy. Randomness in ever-larger neighborhoods produces nontrivial eigenvalue movement and separates eigenvalues, making the next step of the RG possible. We discuss a particularly challenging case where the disorder has a discrete distribution. Reference: arxiv:1705:01916

Schur complement (or Feshbach map) Let H be a symmetric matrix in block form, H = ( A B C D ), with C = B T. Assume that (D E) 1 ε 1, B γ, C γ. The Schur complement at energy λ is: F λ A B(D λ) 1 C. Let ε and γ/ε be small, and λ E ε/2. Then ( ) ϕ (i) If (F λ λ)ϕ = 0, then (H λ) (D λ) 1 Cϕ = 0, and all eigenvectors of H with eigenvalue λ are of this form. (ii) ( γ ) 2 λ F λ F E 2 E. ε (iii) The spectrum of H in [E ε/2, E + ε/2] is in close agreement with that of F E in the following sense. If λ 1 λ 2... λ m are the eigenvalues of H in [E ε/2, E + ε/2], then there are corresponding eigenvalues λ 1 λ 2... λ m of F E, and λ i λ i 2(γ/ε) 2 λ i E.

Utility of the Schur complement With the Schur complement, we are able to reduce the eigenvalue problem for a large matrix into an equivalent (and hopefully more tractable ) one for a smaller matrix. If one focuses on a window of energies in some neighborhood of E, the submatrix D is gapped, in the sense that (D λ) 1 2/ε for λ E ε/2. The degrees of freedom associated with D are eliminated, and one can work with a renormalized operator F λ for λ near E. The fact that F λ depends on λ means that we cannot find all of the eigenvalues in the interval by looking at one matrix. However, (ii) guarantees that the λ-dependence is mild, and then the closeness of the spectra of H and that of F E is guaranteed by (iii). In particular, if one finds a gap in the spectrum of F λ in the interval, then a similar gap occurs for H. This is a way to demonstrate non-degeneracy in the spectrum.

Iterated Schur complement: a natural for the renormalization group For example, let H =. Then invertibility is an issue near E = 0. Low-momentum modes lead to long-range correlations. One can try to handle the problem by introducing block-spin RG. Kinematics of block spin transformations a simple example: Consider models like φ 4 on the lattice, S(φ) = φ, Hφ + V (φ). One could project onto energies 2 k, say, in step k of the RG. But locality would not be preserved, because of the plane wave eigenvectors. Instead, introduce block fields, ψ x = average of φ on block B(x) centered at x. Change basis: φ y = ψ x 1 B(x) (y) + χ y, for y B(x). = constant + fluctuation dim 1 dim L d 1 (choose basis) H = ( ) ( A B C D using the basis ψχ ) block averages fluctuations

Kinematics of block spin transformations, cont. S(φ) = φ, Hφ + V (φ) H = ( A B C D ) using the basis ( ψχ ) block averages fluctuations D = fluctuation covariance, D 1 1 ε Terms B, C couple φ and χ, so one needs to shift the fluctuation field χ to obtain a centered Gaussian integral: χ χ D 1 Cψ (minimizer of quadratic φ, Hφ, given ψ) ( ψ χ ) ( A B C D ) ( ψχ ) = ψ, Aψ + χ, Dχ + 2 χ, Cψ ψ, Aψ + χ, Dχ 2 χ, Cψ + 2 χ, Cψ + ψ, BD 1 Cψ = ψ, F 0 ψ + χ, Dχ, with F 0 = A BD 1 C. We see that the Schur complement F 0 becomes the effective Laplacian for the block spins. The translation D 1 Cψ now appears in V. One is ready to integrate out the fluctuation χ to obtain the new effective action.

Application of iterated Schur complements to random Schrödinger Consider the Anderson model in Z d : The potentials {v x } x Z d H = γ + v with γ 1. are iid random variables. We are particularly interested in the case of a discrete distribution; specifically we may give each v x a uniform distribution 1 on {0, N 1, 2 N 1,..., 1}, with N 1. For N = 2, this is the Anderson-Bernoulli model, the Ising model of random Schrödinger operators. We are interested in showing exponential decay of eigenfunctions (localization). We would also like to control the probability of degeneracies or near-degeneracies in the spectrum of H. Related work: Bourgain, Kenig, Invent. Math. 2005: Localization for the continuum version of Anderson-Bernoulli (N = 2, Z d R d ) for energies near the bottom of the spectrum, E = 0.

Large N result Let I δ (E) denote the interval [E δ, E + δ], and let N (I ) denote the number of eigenvalues of H in I. Theorem. Choose a sufficiently large p. Then for N sufficiently large (depending on p) and γ sufficiently small (depending on N), E N (I δ (E)) Λ (log γ δ) p, and ( ) P min E α E β < δ Λ 2 (log γ δ) p. α β for any rectangle Λ and any δ [γ diam(λ)/2, 1]. Also, α ψ α(x)ψ α (y) decays exponentially, and its disorder average is bounded by C x y p.

Resonant set and block decomposition of H Given an energy E, we expect eigenfunctions whose eigenvalues are close to E will be localized near sites where v x E is small. Eigenfunctions should decay rapidly away from such sites. Resonant Set: Let ε = 1/N and γ ε 20. The resonant step for the first step is R (1) = {i Λ : v i E ε}. The nonresonant set is R (1)c = Λ \ R (1). Block decomposition: H = ( ) A B C D where A, D are H restricted to R (1), R (1)c, respectively, and B, C contain the nearest-neighbor terms from the Laplacian that connect the two regions. As D operates on the subspace associated with nonresonant sites, where v i E ε, one has that (D λ) 1 3/ε for λ E ε/2. Consequence: If ψ is an eigenvector of H with eigenvalue λ I ε/2 (E) then ( ) ψ = with ϕ an eigenvector of F λ = A B(D λ) 1 C. ϕ (D λ) 1 ϕ Also, (D λ) 1 decays exponentially, so ψ(x) decays rapidly with dist(x, R (1) ).

Iteration preliminaries Connected components of the resonant set 1. Decompose the resonant set R (1) into connected blocks or supersites B using proximity conditions.

Iteration preliminaries Accurate diagonalization as in quasidegenerate perturbation theory 2. Obtain a very accurate approximation to the energy levels associated with each block B. We need to do much better than the values of v i for i B because in the next step, the energy window will be shrunk considerably. To do this, let B be a neighborhood of B of width L 1. Here we introduce a sequence of length scales L k = L 0 2 k with L 0 a moderately large number. Then replace: F λ F (1) λ = A B(D λ) 1 C where the matrix D is now restricted to B \ B, instead of Λ \ B. In terms of a random-walk expansion for (D λ) 1 (x, y), take only walks that remain inside B. Then we have that F λ = α F (B α ) + O(γ 2L 1 ). This is analogous to the statement H = diag(v 1,..., v Λ ) + O(γ). Weyl s inequality: spectrum moves no more than the norm of the perturbation.

Iterated Schur Complement Recall the length scales L k = L 0 2 k. Energy window width in step k: ε k = γ L k. Resonant set R (k) consists of blocks still resonant to E within ε k. New proximity conditions: k th -step blocks separated by a distance L 3/2 k. k th -step block B k has a neighborhood B k of width L k (to approximate its spectrum and determine if it remains resonant). Block decomposition of the (k 1) st Schur complement leads to the k th Schur complement: ( F (k 1) A (k) B λ = (k) ), C (k) D (k) F (k) λ = A (k) B (k) (D (k) λ) 1 C (k).

Estimates for the multi-scale percolation problem To obtain localization, we need to demonstrate that the resonant blocks (= percolation clusters) do not percolate. Connections between blocks are made at a distance L 3/2 k, but a compensating effect is the fact that blocks become less and less likely to remain resonant. Roughly speaking, the expected size of percolation clusters will stay bounded uniformly in k if the probability of a block remaining resonant is bounded by L p k with p > d. For a continuous distribution of potentials, the probability would go like ε k = γ L k, by the Wegner estimate. For a discrete distribution, narrowing the spectral window does not automatically lead to a reduction in probability. Therefore, we need to demonstrate eigenvalue movement and separation (degeneracy breaking) based on the effect of potentials in the annuli Bk \ B k 1.

Eigenfunctions of γ + v cannot grow faster than exponentially on Z d Kagome lattice: Compactly supported e-fns Z d : normalized e-fn γ r somewhere on B r

This implies the existence of influential sites where an eigenfunction has a lower bound γ L k Use randomness at a single site in each annulus of radius L k : the most influential one. It splits an isolated eigenvalue into N values with spacing γ L k. The probability that the eigenvalue sits in an interval of size γ L k is N k = L p k, where p = log 2 N. This is summable decay for p > d, which means resonances don t percolate. If not isolated: the potential drives a rank 1 perturbation, which splits an n-fold (near) degeneracy to an (n 1)-fold degeneracy, with probability 1 1/N.

Result: Cantor-like splitting of eigenvalue distribution on a logarithmic length scale This leads to log-hölder continuity of the density of states: E N (I δ (E)) Λ (log γ δ) p. Large p, in particular p > d = separation of δ resonances by a distance L (log γ δ) p/d, so γ L δ. Thus the interaction strength is typically much smaller than δ, which implies localization.

Unique continuation in R d Usual unique continuation principle: If ψ(x) is a harmonic function that vanishes on an open set, then ψ(x) 0 everywhere. Quantitative unique continuation (Bourgain-Kenig 2005): If ψ(x) is an eigenfunction of + v then ψ(x) 2 dx exp( y 4/3 log y ). B 1 (y) The possibility of faster-than-exponential growth is realized for complex v examples (Meshkov 1992). Longstanding conjecture by Landis (from the 60 s) that this does not happen for real v.

Weak form of unique continuation in Z d for solutions to ( + v)ψ = 0 Although eigenfunctions cannot decay uniformly faster than exponentially on the lattice, they can vanish on large sets. Consider, for example, this solution to ( 4)ψ = 0: 1 0 0 0 0 0-1 0 0 0 0 0 1 0 0 0 0 0-1 0 0 0 0 0 1 In a box X, ψ X (x) exp( c z ) for at least one x X in a 45 light cone of R (where ψ is known to be nonzero).

Some recent results in dimension 2 Landis conjecture in dimension 2: Kenig, Sylvestre, Wang, Comm. PDE 2015. A form of unique continuation in Z 2 : Buhovsky, Logunov, Malinnikova, Sodin, arxiv:1712.07902. Localization near the edge for Anderson-Bernoulli in Z 2 : Ding, Smart, arxiv:1809.09041.

The Anderson-Bernoulli model (work in progress with Svitlana Mayboroda) H = + v with v {0, 1} on Z d. A plethora of degeneracies have the potential for spoiling localization. To combat the problem, take E > 0 small (Lifshitz tail regime). To get spectrum near E one needs a region of size l 0 E 1/2 with mostly 0 s. Large deviation arguments = probability exp( E d/2 ) = separation of resonant spots as in the large N case. 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 exp(e d/2 ) 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0

Issues with N = 2 1. Recall that in the large N case, we used the potential at one site per annulus (because of the Cantor condition: we need the upper bound for next-generation effects γ.85l k+1 = γ 1.7L k to fit inside the lower bound on the current effect γ L k.) We reach length scale L k after k eigenvalue splittings (using the potential at one site per annulus), and then each atom has probability N k = 2 kp = L p k, where p = log 2 N. To prevent percolation of resonances we need p > d. But L p k is no longer integrable when N = 2. So we need to find a way to use many sites per annulus. 2. Decay length is many lattice steps = it is difficult to pin down the location of a site where the eigenfunction is guaranteed to be big (the location should not depend on the randomness in the new annulus).

To be continued...