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It is shown that the correlation functions of the random variables $\det(\lambda - X)$, in which $X$ is a real symmetric $ N\times N$ random matrix, exhibit universal local statistics in the large $N$ limit. The derivation relies on an…

Mathematical Physics · Physics 2009-11-07 E. Brezin , S. Hikami

The Kontsevich-Penner model, an Airy matrix model with a logarithmic potential, may be derived from a simple Gaussian two-matrix model through a duality. In this dual version the Fourier transforms of the n-point correlation functions can…

Mathematical Physics · Physics 2015-05-30 E. Brezin , S. Hikami

The paper addresses the calculation of correlation functions of permanental polynomials of matrices with random entries. By exploiting a convenient contour integral representation of the matrix permanent some explicit results are provided…

Mathematical Physics · Physics 2007-05-23 Yan V Fyodorov

The resolution of many large-scale inverse problems using MCMC methods requires a step of drawing samples from a high dimensional Gaussian distribution. While direct Gaussian sampling techniques, such as those based on Cholesky…

Methodology · Statistics 2015-06-22 Clément Gilavert , Saïd Moussaoui , Jérôme Idier

We study the probability for a random line to intersect a given plane curve, defined over a finite field, in a given number of points defined over the same field. In particular, we focus on the limits of these probabilities under successive…

Combinatorics · Mathematics 2021-04-30 Mehdi Makhul , Josef Schicho , Matteo Gallet

We investigate the properties of a class of piecewise-fractional maps arising from the introduction of an invariance under rescaling into convex quadratic maps. The subsequent maps are quasiconvex, and pseudoconvex on specific convex cones;…

Optimization and Control · Mathematics 2025-04-25 Alexandra Zverovich , Matthew Hutchings , Bertrand Gauthier

The generating series of the intersection numbers of the stable cohomology classes on moduli spaces of curves satisfies the string equation and a KdV hierarchy. Kontsevich's original proof of this result uses a matrix model and the matrix…

Algebraic Geometry · Mathematics 2012-09-25 Domenico Fiorenza

The present work provides an original framework for random matrix analysis based on revisiting the concentration of measure theory from a probabilistic point of view. By providing various notions of vector concentration ($q$-exponential,…

Probability · Mathematics 2021-01-19 Cosme Louart , Romain Couillet

The $\tau$-function theory of Painlev\'e systems is used to derive recurrences in the rank $n$ of certain random matrix averages over U(n). These recurrences involve auxilary quantities which satisfy discrete Painlev\'e equations. The…

Mathematical Physics · Physics 2009-11-10 P. J. Forrester , N. S. Witte

We address the six vertex model on a random lattice, which in combinatorial terms corresponds to the enumeration of weighted 4-valent planar maps equipped with an Eulerian orientation. This problem was exactly, albeit non-rigorously solved…

Combinatorics · Mathematics 2020-07-17 Andrew Elvey Price , Paul Zinn-Justin

A random intersection graph is constructed by assigning independently to each vertex a subset of a given set and drawing an edge between two vertices if and only if their respective subsets intersect. In this paper a model is developed in…

Probability · Mathematics 2015-09-24 Maria Deijfen , Willemien Kets

We obtain in closed form averages of polynomials, taken over hermitian matrices with the Gaussian measure involved in the Kontsevich integral, and prove a conjecture of Witten enabling one to express analogous averages with the full (cubic…

High Energy Physics - Theory · Physics 2015-06-26 P. Di Francesco , C. Itzykson , J. -B. Zuber

We study pathwise invariances of centred random fields that can be controlled through the covariance. A result involving composition operators is obtained in second-order settings, and we show that various path properties including…

Statistics Theory · Mathematics 2013-08-07 David Ginsbourger , Olivier Roustant , Nicolas Durrande

The inverse of a large matrix can often be accurately approximated by a polynomial of degree significantly lower than the order of the matrix. The iteration polynomial generated by a run of the GMRES algorithm is a good candidate, and its…

Numerical Analysis · Mathematics 2025-02-26 Mark Embree , Joel A. Henningsen , Jordan Jackson , Ronald B. Morgan

We provide strong evidence for the conjecture that the analogue of Kontsevich's matrix Airy function, with the cubic potential $\mathrm{Tr}(\Phi^3)$ replaced by a quartic term $\mathrm{Tr}(\Phi^4)$, obeys the blobbed topological recursion…

Mathematical Physics · Physics 2023-04-24 Johannes Branahl , Alexander Hock , Raimar Wulkenhaar

We investigate the characteristic polynomials of the Gaussian $\beta$-ensemble for general $\beta>0$ through its transfer matrix recurrence. We show that the rescaled characteristic polynomial converges to a random entire function in a…

Probability · Mathematics 2021-08-03 Gaultier Lambert , Elliot Paquette

This paper establishes a comparison theorem for the maximum eigenvalue of a sum of independent random symmetric matrices. The theorem states that the maximum eigenvalue of the matrix sum is dominated by the maximum eigenvalue of a Gaussian…

Probability · Mathematics 2026-03-17 Joel A. Tropp

We investigate the problem of recovering a partially observed high-rank matrix whose columns obey a nonlinear structure such as a union of subspaces, an algebraic variety or grouped in clusters. The recovery problem is formulated as the…

Machine Learning · Statistics 2022-12-12 Florentin Goyens , Coralia Cartis , Armin Eftekhari

In this paper, for solving inconsistent matrix equations we propose a dual-space residual-based randomized extended Kaczmarz method and its version with Nesterov momentum. Without the full column rank assumptions on coefficient matrices, we…

Numerical Analysis · Mathematics 2026-04-08 Wendi Bao , Jing Li , Lili Xing , Weiguo Li , Jichao Wang

Consider a sample of a centered random vector with unit covariance matrix. We show that under certain regularity assumptions, and up to a natural scaling, the smallest and the largest eigenvalues of the empirical covariance matrix converge,…

Probability · Mathematics 2018-03-16 Djalil Chafaï , Konstantin Tikhomirov
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