Monotonicity of the logarithmic energy for random matrices

TL;DR

This paper investigates a monotonicity property of the logarithmic energy of spectral distributions in certain random matrix ensembles, revealing a potentially universal phenomenon with explicit formulas for key models.

Contribution

It introduces and verifies a monotonicity property of the logarithmic energy in spectral distributions, supported by explicit formulas and numerical evidence for various ensembles.

Findings

Monotonicity holds for GUE, Ginibre, and Laguerre ensembles.

Explicit formulas for logarithmic energy are derived.

Numerical simulations suggest universality of the phenomenon.

Abstract

It is well-known that the semi-circle law, which is the limiting distribution in the Wigner theorem, is the minimizer of the logarithmic energy penalized by the second moment. A very similar fact holds for the Girko and Marchenko--Pastur theorems. In this work, we shed the light on an intriguing phenomenon suggesting that this functional is monotonic along the mean empirical spectral distribution in terms of the matrix dimension. This is reminiscent of the monotonicity of the Boltzmann entropy along the Boltzmann equation, the monotonicity of the free energy along ergodic Markov processes, and the Shannon monotonicity of entropy or free entropy along the classical or free central limit theorem. While we only verify this monotonicity phenomenon for the Gaussian unitary ensemble, the complex Ginibre ensemble, and the square Laguerre unitary ensemble, numerical simulations suggest that it is actually more universal. We obtain along the way explicit formulas of the logarithmic energy of the mentioned models which can be of independent interest.