Quantum ergodicity on graphs

TL;DR

This paper studies how eigenfunctions distribute evenly on large quantum graphs at high energies, providing new estimates on deviations from uniformity and conditions for asymptotic equidistribution.

Contribution

It introduces a novel field-theoretic approach using supersymmetric sigma-models to estimate eigenfunction distribution deviations on large quantum graphs.

Findings

Provides a refined rate of convergence for equidistribution.

Establishes criteria for asymptotic equidistribution in large graphs.

Numerical tests confirm theoretical predictions in specific examples.

Abstract

We investigate the equidistribution of the eigenfunctions on quantum graphs in the high-energy limit. Our main result is an estimate of the deviations from equidistribution for large well-connected graphs. We use an exact field-theoretic expression in terms of a variant of the supersymmetric nonlinear sigma-model. Our estimate is based on a saddle-point analysis of this expression and leads to a criterion for when equidistribution emerges asymptotically in the limit of large graphs. Our theory predicts a rate of convergence that is a significant refinement of previous estimates, long-assumed to be valid for quantum chaotic systems, agreeing with them in some situations but not all. We discuss specific examples for which the theory is tested numerically.