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In previous work, a description of the result of applying the Householder tridiagonalization algorithm to a G$\beta$E random matrix is provided by Edelman and Dumitriu. The resulting tridiagonal ensemble makes sense for all $\beta>0$, and…

Probability · Mathematics 2026-02-20 Alan Edelman , Sungwoo Jeong , Ron Nissim

We prove a Liouville-type theorem for semilinear parabolic systems of the form $${\partial_t u_i}-\Delta u_i =\sum_{j=1}^{m}\beta_{ij} u_i^ru_j^{r+1}, \quad i=1,2,...,m$$ in the whole space ${\mathbb R}^N\times {\mathbb R}$. Very recently,…

Analysis of PDEs · Mathematics 2015-07-28 Quoc Hung Phan , Philippe Souplet

We show that the limiting minimal eigenvalue distributions for a natural generalization of Gaussian sample-covariance structures (the "beta ensembles") are described by the spectrum of a random diffusion generator. By a Riccati…

Probability · Mathematics 2009-11-13 Jose A. Ramirez , Brian Rider

We study the rate of convergence for the largest eigenvalue distributions in the Gaussian unitary and orthogonal ensembles to their Tracy-Widom limits. We show that one can achieve an $O(N^{-2/3})$ rate with particular choices of the…

Probability · Mathematics 2015-03-19 Iain M. Johnstone , Zongming Ma

We establish the Gaussian Double-Bubble Conjecture: the least Gaussian-weighted perimeter way to decompose $\mathbb{R}^n$ into three cells of prescribed (positive) Gaussian measure is to use a tripod-cluster, whose interfaces consist of…

Functional Analysis · Mathematics 2021-10-11 Emanuel Milman , Joe Neeman

The wonderful formulas by I.Dumitriu and A.Edelman rewrite $\beta$-ensemble, with eigenvalue integrals containing Vandermonde factors in the power $2\beta$, through integrals over tridiagonal matrices, where $\beta$-dependent are the powers…

High Energy Physics - Theory · Physics 2022-04-20 A. Mironov , A. Morozov , A. Popolitov

Randomized quadratures for integrating functions in Sobolev spaces of order $\alpha \ge 1$, where the integrability condition is with respect to the Gaussian measure, are considered. In this function space, the optimal rate for the…

Numerical Analysis · Mathematics 2023-07-21 Takashi Goda , Yoshihito Kazashi , Yuya Suzuki

Many functions have approximately-known upper and/or lower bounds, potentially aiding the modeling of such functions. In this paper, we introduce Gaussian process models for functions where such bounds are (approximately) known. More…

Machine Learning · Computer Science 2022-10-20 Vu Nguyen , Marc Peter Deisenroth , Michael A. Osborne

We consider finite $\beta$-ensembles $\mathcal X_{n,\beta}^{\mathbb F}$ with $n$ points on $\mathbb F$, where $\mathbb F$ denotes either the real line or the complex plane. Let $U$ be a bounded subset of $ \mathbb F$ such that $\partial U$…

Probability · Mathematics 2026-05-19 Kartick Adhikari , Sitanath Majumder

In this paper, we derive new, nearly optimal bounds for the Gaussian approximation to scaled averages of $n$ independent high-dimensional centered random vectors $X_1,\dots,X_n$ over the class of rectangles in the case when the covariance…

Probability · Mathematics 2021-05-13 Victor Chernozhukov , Denis Chetverikov , Yuta Koike

We consider a convex constrained Gaussian sequence model and characterize necessary and sufficient conditions for the least squares estimator (LSE) to be minimax optimal. For a closed convex set $K\subset \mathbb{R}^n$ we observe…

Statistics Theory · Mathematics 2026-03-06 Akshay Prasadan , Matey Neykov

We derive novel anti-concentration bounds for the difference between the maximal values of two Gaussian random vectors across various settings. Our bounds are dimension-free, scaling with the dimension of the Gaussian vectors only through…

Statistics Theory · Mathematics 2024-08-27 Alexandre Belloni , Ethan X. Fang , Shuting Shen

We consider the problem of estimating the parameters a Gaussian Mixture Model with K components of known weights, all with an identity covariance matrix. We make two contributions. First, at the population level, we present a sharper…

Machine Learning · Computer Science 2021-09-24 Nimrod Segol , Boaz Nadler

The non-Gaussian distribution of primordial perturbations has the potential to reveal the physical processes at work in the very early Universe. Local models provide a well-defined class of non-Gaussian distributions that arise naturally…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 David Wands

Let $\Gamma=\langle \alpha, \beta \rangle$ be a numerical semigroup. In this article we consider the dual $\Delta^*$ of a $\Gamma$-semimodule $\Delta$; in particular we deduce a formula that expresses the minimal set of generators of…

Combinatorics · Mathematics 2013-12-20 Julio José Moyano-Fernández , Jan Uliczka

Nonlocal magic quantifies the irreducible nonstabilizerness of a bipartite quantum state after optimizing over local basis changes. We study nonlocal magic for pure fermionic Gaussian states, and derive a simple closed-form entanglement…

Quantum Physics · Physics 2026-05-01 Mario Collura , Benjamin Béri , Emanuele Tirrito

We consider random Hermitian matrices with independent upper triangular entries. Wigner's semicircle law says that under certain additional assumptions, the empirical spectral distribution converges to the semicircle distribution. We…

Probability · Mathematics 2022-06-14 Calvin Wooyoung Chin

A physical system is said to satisfy a thermal area law if the mutual information between two adjacent regions in the Gibbs state is controlled by the area of their boundary. Thermal area laws have been derived for systems with bounded…

Quantum Physics · Physics 2023-08-16 Marius Lemm , Oliver Siebert

Let L be a positive line bundle over a projective complex manifold X. Consider the space of holomorphic sections of the tensor power of order p of L. The determinant of a basis of this space, together with some given probability measure on…

Complex Variables · Mathematics 2016-03-14 Tien-Cuong Dinh , Viet-Anh Nguyen

We develop a regularization of the quantum microcanonical ensemble, called a Gaussian ensemble, which can be used for derivation of the canonical ensemble from microcanonical principles. The derivation differs from the usual methods by…

Statistical Mechanics · Physics 2008-11-26 Jani Lukkarinen