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We propose a definition for a Tau function and a spinor kernel (closely related to Baker-Akhiezer functions), where times parametrize slow (of order 1/N) deformations of an algebraic plane curve. This definition consists of a formal…

Mathematical Physics · Physics 2015-03-19 Gaëtan Borot , Bertrand Eynard

We consider the probability distributions of the subsystem (staggered) magnetization in ordered and disordered models of quantum magnets in D dimensions. We focus on Heisenberg antiferromagnets and long-range transverse-field Ising models…

Statistical Mechanics · Physics 2024-11-20 Riccardo Senese , Jacob H. Robertson , Fabian H. L. Essler

We review some occurrences of Painlev\'e II transcendents in the study of two-dimensional Yang-Mills theory, fluctuation formulas for growth models, and as distribution functions within random matrix theory. We first discuss settings in…

Mathematical Physics · Physics 2015-06-16 Peter J. Forrester , Nicholas S. Witte

We propose a generalization of pseudospin and spin symmetries, the SU(2) symmetries of Dirac equation with scalar and vector mean-field potentials originally found independently in the 70's by Smith and Tassie, and Bell and Ruegg. As…

Quantum Physics · Physics 2017-07-14 P. Alberto , M. Malheiro , T. Frederico , A. de Castro

We consider the probability to find a string of $x$ adjacent parallel spins in the antiferromagnetic ground state of the model (in a magnetic field). We derive a system of integro-difference equations which define this probability. This…

Condensed Matter · Physics 2009-10-22 Holger Frahm , Alexander R. Its , Vladimir E. Korepin

It has recently been emphasized that all known exact evaluations of gap probabilities for classical unitary matrix ensembles are in fact $\tau$-functions for certain Painlev\'e systems. We show that all exact evaluations of gap…

Mathematical Physics · Physics 2009-11-07 P. J. Forrester , N. S. Witte

We propose a scalable inference algorithm for Bayes posteriors defined on a reproducing kernel Hilbert space (RKHS). Given a likelihood function and a Gaussian random element representing the prior, the corresponding Bayes posterior measure…

Machine Learning · Statistics 2025-02-26 Veit Wild , James Wu , Dino Sejdinovic , Jeremias Knoblauch

We show that the Riemannian Gaussian distributions on symmetric spaces, introduced in recent years, are of standard random matrix type. We exploit this to compute analytically marginals of the probability density functions. This can be done…

Mathematical Physics · Physics 2021-10-29 Leonardo Santilli , Miguel Tierz

In this paper we study the extension of Painlev\'e/gauge theory correspondence to circular quivers by focusing on the special case of $SU(2)$ $\mathcal{N}=2^*$ theory. We show that the Nekrasov-Okounkov partition function of this gauge…

High Energy Physics - Theory · Physics 2020-04-22 Giulio Bonelli , Fabrizio Del Monte , Pavlo Gavrylenko , Alessandro Tanzini

The time-integrated current of the TASEP has non-Gaussian fluctuations of order $t^{1/3}$. The recently discovered connection to random matrices and the Painlev\'e II Riemann-Hilbert problem provides a technique through which we obtain the…

Statistical Mechanics · Physics 2007-05-23 M. Praehofer , H. Spohn

We theoretically study quantum spin transport in a one-dimensional folded XXZ model with an alternating domain-wall initial state via the Bethe ansatz technique, exactly demonstrating that a probability distribution of finding a left-most…

Statistical Mechanics · Physics 2024-12-31 Kazuya Fujimoto , Tomohiro Sasamoto

Equivalence is established between a special class of Painleve VI equations parametrized by a conformal dimension $\mu$, time dependent Euler top equations, isomonodromic deformations and three-dimensional Frobenius manifolds. The…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Henrik Aratyn , Johan van de Leur

With a graph $G=(V,E)$ we associate a collection of non-negative real weights $\cup_{v\in V}{\lambda_{i,v}:1\leq i \leq m} \cup \cup_{uv \in E} {\lambda_{ij,uv}:1\leq i \leq j \leq m}$. We consider the probability distribution on…

Combinatorics · Mathematics 2012-06-15 David Galvin

In the Bayes paradigm and for a given loss function, we propose the construction of a new type of posterior distributions, that extends the classical Bayes one, for estimating the law of an $n$-sample. The loss functions we have in mind are…

Statistics Theory · Mathematics 2024-01-05 Yannick Baraud

We consider the circular unitary ensemble with a Fisher-Hartwig singularity of both jump type and root type at $z=1$. A rescaling of the ensemble at the Fisher-Hartwig singularity leads to the confluent hypergeometric kernel. By studying…

Mathematical Physics · Physics 2020-06-09 Shuai-Xia Xu , Yu-Qiu Zhao

We discuss a relativistic diffusion in the proper time in an approach of Schay and Dudley. We derive (Langevin) stochastic differential equations in various coordinates.We show that in some coordinates the stochastic differential equations…

High Energy Physics - Theory · Physics 2009-11-13 Z. Haba

Generic c=1 four-point conformal blocks on the Riemann sphere can be seen as the coefficients of Fourier expansion of the tau function of Painlev\'e VI equation with respect to one of its integration constants. Based on this relation, we…

High Energy Physics - Theory · Physics 2013-12-19 N. Iorgov , O. Lisovyy , Yu. Tykhyy

The gap probability generating function has as its coefficients the probability of an interval containing exactly $k$ eigenvalues. For scaled random matrices with orthogonal symmetry, and the interval at the hard or soft spectrum edge, the…

Mathematical Physics · Physics 2007-08-14 Peter J. Forrester

Tracy and Widom have evaluated the cumulative distribution of the largest eigenvalue for the finite and scaled infinite GUE in terms of a PIV and PII transcendent respectively. We generalise these results to the evaluation of…

Mathematical Physics · Physics 2009-11-07 P. J. Forrester , N. S. Witte

We present a novel kernel over the space of probability measures based on the dual formulation of optimal regularized transport. We propose an Hilbertian embedding of the space of probabilities using their Sinkhorn potentials, which are…

Machine Learning · Statistics 2022-10-14 François Bachoc , Louis Béthune , Alberto Gonzalez-Sanz , Jean-Michel Loubes