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Here we consider the problem of small oscillations of a rotating inviscid incompressible fluid. From a mathematical point of view, new exact solutions to the two-dimensional Poincar\'e-Sobolev equation in a class of domains including…

Fluid Dynamics · Physics 2016-10-24 S. D. Troitskaya

We investigate the spatial statistics of the energy eigenfunctions on large quantum graphs. It has previously been conjectured that these should be described by a Gaussian Random Wave Model, by analogy with quantum chaotic systems, for…

Chaotic Dynamics · Physics 2015-05-18 S. Gnutzmann , J. P. Keating , F. Piotet

In this paper, we study the level-set of the zero-average Gaussian Free Field on a uniform random $d$-regular graph above an arbitrary level $h\in (-\infty, h_{\star})$, where $h_{\star}$ is the level-set percolation threshold of the GFF on…

Probability · Mathematics 2023-02-03 Guillaume Conchon--Kerjan

The paper investigates uniform convergence of wavelet expansions of Gaussian random processes. The convergence is obtained under simple general conditions on processes and wavelets which can be easily verified. Applications of the developed…

Probability · Mathematics 2013-07-29 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

We prove two universality results for random tensors of arbitrary rank D. We first prove that a random tensor whose entries are N^D independent, identically distributed, complex random variables converges in distribution in the large N…

Probability · Mathematics 2013-05-07 Razvan Gurau

We show that there exists a family of groups $G_n$ and nontrivial irreducible representations $\rho_n$ such that, for any constant $t$, the average of $\rho_n$ over $t$ uniformly random elements $g_1, \ldots, g_t \in G_n$ has operator norm…

Combinatorics · Mathematics 2015-08-07 Shachar Lovett , Cristopher Moore , Alexander Russell

Spectral decomposition of the covariance operator is one of the main building blocks in the theory and applications of Gaussian processes. Unfortunately it is notoriously hard to derive in a closed form. In this paper we consider the…

Probability · Mathematics 2020-05-19 P. Chigansky , M. Kleptsyna , D. Marushkevych

In this paper, we consider a stochastic system described by a differential equation admitting a spatially varying random coefficient. The differential equation has been employed to model various static physics systems such as elastic…

Probability · Mathematics 2013-09-18 Jingchen Liu , Xiang Zhou

We present a solution of the problem of level-set percolation for multivariate Gaussians defined in terms of weighted graph Laplacians on complex networks. It is achieved using a cavity or message passing approach, which allows one to…

Disordered Systems and Neural Networks · Physics 2024-10-08 Reimer Kuehn

We consider a Gaussian random matrix with correlated entries that have a power law decay of order $d>2$ and prove universality for the extreme eigenvalues. A local law is proved using the self-consistent equation combined with a…

Probability · Mathematics 2018-01-24 Arka Adhikari , Ziliang Che

Gaussian Process is a non-parametric prior which can be understood as a distribution on the function space intuitively. It is known that by introducing appropriate prior to the weights of the neural networks, Gaussian Process can be…

Machine Learning · Statistics 2021-01-08 Erdong Guo , David Draper

The truncated Korteweg-De Vries (TKdV) system, a shallow-water wave model with Hamiltonian structure that exhibits weakly turbulent dynamics, has been found to accurately predict the anomalous wave statistics observed in recent laboratory…

Fluid Dynamics · Physics 2022-05-10 Hui Sun , Nicholas J. Moore

We establish central and non-central limit theorems for sequences of functionals of the Gaussian output of an infinitely-wide random neural network on the d-dimensional sphere . We show that the asymptotic behaviour of these functionals as…

Probability · Mathematics 2026-04-24 Simmaco Di Lillo , Leonardo Maini , Domenico Marinucci

The generic behavior of quantum systems has long been of theoretical and practical interest. Any quantum process is represented by a sequence of quantum channels. We consider general ergodic sequences of stochastic channels with arbitrary…

Quantum Physics · Physics 2022-07-08 Ramis Movassagh , Jeffrey Schenker

Observables in random tensor theory are polynomials in the entries of a tensor of rank $d$ which are invariant under $U(N)^d$. It is notoriously difficult to evaluate the expectations of such polynomials, even in the Gaussian distribution.…

Mathematical Physics · Physics 2014-11-26 Valentin Bonzom , Frédéric Combes

Consider a random regular graph of fixed degree $d$ with $n$ vertices. We study spectral properties of the adjacency matrix and of random Schr\"odinger operators on such a graph as $n$ tends to infinity. We prove that the integrated density…

Mathematical Physics · Physics 2014-05-09 Leander Geisinger

The aim of this paper is twofold. First, we study eigenvalues and eigenvectors of the adjacency matrix of a bond percolation graph when the base graph is finite and well approximated locally by an infinite regular graph. We relate…

Mathematical Physics · Physics 2023-07-19 Charles Bordenave

We prove well-posedness for very general linear wave- and diffusion equations on compact or non-compact metric graphs allowing various different conditions in the vertices. More precisely, using the theory of strongly continuous operator…

Analysis of PDEs · Mathematics 2020-06-08 Klaus-Jochen Engel , Marjeta Kramar Fijavž

We provide sufficient conditions for a regular graph $G$ of growing degree $d$, guaranteeing a phase transition in its random subgraph $G_p$ similar to that of $G(n,p)$ when $p\cdot d\approx 1$. These conditions capture several well-studied…

Combinatorics · Mathematics 2025-11-17 Sahar Diskin , Michael Krivelevich

We study a class of interacting particle systems on $\mathbb{R}$ which was recently investigated by F. G\"otze and the second author [GV14]. These ensembles generalize eigenvalue ensembles of Hermitian random matrices by allowing different…

Probability · Mathematics 2018-05-31 Thomas Kriecherbauer , Martin Venker