Deviation probabilities and Sharp Berry-Esseen bound for rightmost eigenvalue of large non-Hermitian chiral random matrices
Yutao Ma, Xujia Meng
TL;DR
This work analyzes the rightmost eigenvalue of a large chiral non-Hermitian Dirac matrix in the maximally non-Hermitian regime ($τ=0$). By exploiting the determinantal point process structure of the eigenvalues and precise asymptotics of the correlation kernel, it establishes a sharp Berry–Esseen bound to the Gumbel law for a centered, scaled edge statistic $X_n$ defined via $s_n$ and $γ_n$, with an explicit rate $\frac{25 (\log\log s_n)^2}{16 e \log s_n}(1+o(1))$. In addition, the paper derives large- and moderate-deviation principles for the scaled rightmost eigenvalue, illuminating the rate at which the edge converges to $1$ across regimes where the parameter $v$ scales with $n$ (via $\alpha=\lim v/n$). The results advance quantitative understanding of edge statistics in structured non-Hermitian ensembles and complement the existing Ginibre-type quantitative benchmarks by providing exact rates and regime-dependent deviations.
Abstract
This paper provides a quantitative analysis of the rightmost eigenvalue for a chiral non-Hermitian random Dirac matrix in the maximally non-Hermitian regime ($τ=0$). Let $(σ_i)_{1\le i\le n}$ be the eigenvalues with positive real part. We define the normalization constants \[ s_n = \frac{4n(n+v)}{2n+v}, \qquad γ_n = \frac{1}{2}\log s_n - \frac{5}{4}\log(\log s_n) - \log\bigl(2^{1/4}π\bigr), \] and the centered and scaled variable \[ X_n = \sqrt{2s_n\log s_n}\,\bigl(\bigl(\tfrac{n}{n+v}\bigr)^{1/4}\,\max_{1\le i\le n}\Reσ_i \;-\; 1 \;-\; \frac{γ_n}{\sqrt{2s_n\log s_n}}\bigr). \] Our main result is the following sharp Berry--Esseen bound for the convergence of $X_n$ to the Gumbel distribution: \[ \sup_{x \in \mathbb{R}} \bigl|\mathbb{P}(X_n \le x) - e^{-e^{-x}}\bigr| = \frac{25 (\log\log s_n)^2}{16 e \,\log s_n}\,\bigl(1 + o(1)\bigr), \] which holds as $n \to \infty$ for an arbitrary parameter $v \ge 0$ (which may depend on $n$). As a byproduct of our analysis, we also obtain precise large- and moderate-deviation principles for the scaled rightmost eigenvalue $\bigl(\frac{n}{n+v}\bigr)^{1/4} \max_{1\le i\le n}\Reσ_i$, characterizing its rate of convergence to the value $1$.