On the distribution of the largest real eigenvalue for the real ginibre ensemble

Citation
Poplavskyi, Mihail et al., On the distribution of the largest real eigenvalue for the real ginibre ensemble, Annals of applied probability , 27(3), 2017, pp. 1395-1413
ISSN journal
10505164
Volume
27
Issue
3
Year of publication
2017
Pages
1395 - 1413
Database
ACNP
SICI code
Abstract
Let $\sqrt{\mathrm{N}}+{\mathrm{\lambda }}_{\mathrm{max}}$ be the largest real eigenvalue of a random N . N matrix with independent N(0, 1) entries (the "real Ginibre matrix"). We study the large deviations behaviour of the limiting N . . distribution .[.max < t] of the shifted maximal real eigenvalue .max. In particular, we prove that the right tail of this distribution is Gaussian: for t > 0, $\mathrm{\mathbb{P}}[{\mathrm{\lambda }}_{\mathrm{max}}<\mathrm{t}]=1-\frac{1}{4}\mathrm{e}\mathrm{r}\mathrm{f}\mathrm{c}\left(\mathrm{t}\right)+\mathrm{O}\left({\mathrm{e}}^{-2{\mathrm{t}}^{2}}\right)$. This is a rigorous confirmation of the corresponding result of [Phys. Rev. Lett. 99 (2007) 050603]. We also prove that the left tail is exponential, with correct asymptotics up to O(1): for t < 0, $\mathrm{\mathbb{P}}[{\mathrm{\lambda }}_{\mathrm{max}}<\mathrm{t}]={\mathrm{e}}^{\frac{1}{2\sqrt{2\mathrm{\pi }}}\mathrm{\zeta }\left(\frac{3}{2}\right)\mathrm{t}+\mathrm{O}\left(1\right)}$, where . is the Riemann zeta-function. Our results have implications for interacting particle systems. The edge scaling limit of the law of real eigenvalues for the real Ginibre ensemble is a rescaling of a fixed time distribution of annihilating Brownian motions (ABMs) with the step initial condition; see [Garrod, Poplavskyi, Tribe and Zaboronski (2015)]. Therefore, the tail behaviour of the distribution of ${\mathrm{X}}_{\mathrm{s}}^{(\mathrm{max})}$.the position of the rightmost annihilating particle at fixed time s > 0.can be read off from the corresponding answers for .max using ${\mathrm{X}}_{\mathrm{s}}^{(\mathrm{max})}\stackrel{\mathrm{D}}{=}\sqrt{4\mathrm{s}}{\mathrm{\lambda }}_{\mathrm{max}}$.