The Instability of Painlev\'e Equations in Recovering Largest Eigenvalue Distributions of GUE, LUE, JUE and an Attempt of Solution to It
Haonan Gu

TL;DR
This paper investigates the numerical stability of recovering Painlevé equation solutions for largest eigenvalue distributions in classical random matrix ensembles, comparing them with Fredholm determinant methods.
Contribution
It demonstrates how to numerically recover Painlevé solutions from finite-$n$ data and assesses the stability and accuracy of this reconstruction process.
Findings
High-accuracy numerical verification of Painlevé and Fredholm determinant equivalence.
Finite-$n$ to scaling-limit transition illustrated with precision up to 10^{-5}.
Finite-$n$ Painlevé solutions can be accurately reconstructed from Fredholm data.
Abstract
The distribution of the largest eigenvalue for the three classical unitary ensembles -- GUE, LUE, and JUE -- admits two complementary exact descriptions: (i) as Fredholm determinants of their orthogonal polynomial correlation kernels and (ii) as isomonodromic -functions governed by Painlev\'e equations. For finite , the associated Jimbo-Miwa-Okamoto -forms are (GUE), (LUE), and (JUE); under soft- or hard-edge scalings these degenerate to or descriptions of the Tracy-Widom and hard-edge laws \cite{tracy1994level,forrester2003painleve,deift1999orthogonal}. It is well known among random matrix theorists (for example Folkmar Bornemann) that the Fredholm determinant is a more numerically stable and accurate way to compute the CDF of the largest eigenvalue for GUE, LUE, JUE than direct Painlev\'e integration. The aim of this paper…
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Taxonomy
TopicsMathematical functions and polynomials · Random Matrices and Applications · Advanced Chemical Physics Studies
