Simple Eigenvalues and Non-vanishing Eigenvectors of the Anderson Model

Abstract

We consider the Anderson model on the finite grid G = Z/L1 Z×·s× Z/Ld Z, defined by the random Hamiltonian Ht=+tV, where is the discrete Laplacian and V=diag(\ωx\x∈ G) is a random onsite potential with ωxμ i.i.d. We ask the natural question of when Ht has simple eigenvalues and non-vanishing eigenvectors. We prove that, when μ is a continuous probability distribution, Ht has this property for all but finitely many t values with probability 1. However, when μ is a Bernoulli distribution, the conditions fail with positive probability, for which we give a lower bound. We also calculate the exact probability of these conditions being met in the Bernoulli case when d = 1 and L = L1 is prime.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…