On the Open Question of The Tracy-Widom Distribution of \beta-Ensemble With \beta=6
Yuqi Li

TL;DR
This paper completely determines the Tracy-Widom distribution for the eta-ensemble with eta=6 by analyzing a specific nonlinear ODE and solving an open problem about the existence of global smooth solutions, confirming the distribution's properties.
Contribution
The authors solve the open question of the existence of a global smooth solution to a key ODE for eta=6, establishing the Tracy-Widom distribution in this case.
Findings
Confirmed the existence of a unique global smooth solution with specific boundary conditions.
Parameterization of solutions by (c_1, c_2) and identification of the unique solution corresponding to (0,0).
Proved the solution is bounded and satisfies the boundary conditions of the Bloemendal-Virág equation.
Abstract
We determine completely the Tracy-Widom distribution for Dyson's \beta-ensemble with \beta=6. The problem of the Tracy-Widom distribution of \beta-ensemble for general \beta>0 has been reduced to find out a bounded solution of the Bloemendal-Vir\'ag equation with a specified boundary. Rumanov proposed a Lax pair approach to solve the Bloemendal-Vir\'ag equation for even integer \beta. He also specially studied the \beta=6 case with his approach and found a second order nonlinear ordinary differential equation (ODE) for the logarithmic derivative of the Tracy-Widom distribution for \bea=6. Grava et al. continued to study \beta=6 and found Rumanov's Lax pair is gauge equivalent to that of Painlev\'e II in this case. They started with Rumanov's basic idea and came down to two auxiliary functions {\alpha}(t) and q_2(t), which satisfy a coupled first-order ODE. The open question by Grava et…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRandom Matrices and Applications · Bayesian Methods and Mixture Models · Statistical Distribution Estimation and Applications
