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We show that the Newton polytope of a polynomial has a strong impact on the distribution of its mass and zeros. The basic theme is that Newton polytopes determine allowed and forbidden regions for these distributions. We equip the space of…

Algebraic Geometry · Mathematics 2007-05-23 Bernard Shiffman , Steve Zelditch

This paper first strictly proved that the growth of the second moment of a large class of Gaussian processes is not greater than power function and the covariance matrix is strictly positive definite. Under these two conditions, the maximum…

Statistics Theory · Mathematics 2022-07-21 Shifei Luo

Motivated by recently discovered relations between logarithmically correlated Gaussian processes and characteristic polynomials of large random $N \times N$ matrices $H$ from the Gaussian Unitary Ensemble (GUE), we consider the problem of…

Mathematical Physics · Physics 2016-09-28 Yan V. Fyodorov , Nicholas J. Simm

In this work, we study asymptotic zero distribution of random multi-variable polynomials which are random linear combinations $\sum_{j}a_jP_j(z)$ with i.i.d coefficients relative to a basis of orthonormal polynomials $\{P_j\}_j$ induced by…

Complex Variables · Mathematics 2018-05-07 Turgay Bayraktar

We prove matching direct and inverse theorems for (algebraic) polynomial approximation with doubling weights $w$ having finitely many zeros and singularities (i.e., points where $w$ becomes infinite) on an interval and not too ``rapidly…

Classical Analysis and ODEs · Mathematics 2015-07-20 Kirill A. Kopotun

Suppose that A_1,\dots, A_N are independent random matrices whose atoms are iid copies of a random variable \xi of mean zero and variance one. It is known from the works of Newman et. al. in the late 80s that when \xi is gaussian then…

Probability · Mathematics 2016-07-13 Hoi H. Nguyen

Stochastic partial differential equations driven by Poisson random measures (PRM) have been proposed as models for many different physical systems, where they are viewed as a refinement of a corresponding noiseless partial differential…

Probability · Mathematics 2012-09-25 Amarjit Budhiraja , Jiang Chen , Paul Dupuis

Gaussian distributions can be generalized from Euclidean space to a wide class of Riemannian manifolds. Gaussian distributions on manifolds are harder to make use of in applications since the normalisation factors, which we will refer to as…

Probability · Mathematics 2023-02-16 Simon Heuveline , Salem Said , Cyrus Mostajeran

The random convex hull of a Poisson point process in $\mathbb{R}^d$ whose intensity measure is a multiple of the standard Gaussian measure on $\mathbb{R}^d$ is investigated. The purpose of this paper is to invent a new viewpoint on these…

Probability · Mathematics 2018-04-10 Julian Grote , Christoph Thaele

The main goal of this article is to study the effect of small, highly nonlinear, unbounded drifts (small time large deviation principle (LDP) based on exponential equivalence arguments) for a class of stochastic partial differential…

Probability · Mathematics 2022-12-27 Ankit Kumar , Manil T. Mohan

In this paper we investigate the asymptotic distribution of the zeros of polynomials $P_{n}(x)$ satisfying a first order differential-difference equation. We give several examples of orthogonal and non-orthogonal families.

Classical Analysis and ODEs · Mathematics 2013-12-04 Diego Dominici , Walter Van Assche

We obtain an asymptotic H\"older estimate for expectations of a quite general class of discrete stochastic processes. Such expectations can also be described as solutions to a dynamic programming principle or as solutions to discretized…

Analysis of PDEs · Mathematics 2022-11-21 Ángel Arroyo , Pablo Blanc , Mikko Parviainen

Second-order partial differential equations in non-divergence form are considered. Equations of this kind typically arise as subproblems for the solution of Hamilton-Jacobi-Bellman equations in the context of stochastic optimal control, or…

Numerical Analysis · Mathematics 2020-08-13 Jan Blechschmidt , Roland Herzog , Max Winkler

We study the 'critical moments' of subcritical Gaussian multiplicative chaos (GMCs) in dimensions $d \leq 2$. In particular, we establish a fully explicit formula for the leading order asymptotics, which is closely related to large…

Probability · Mathematics 2023-08-02 Jonathan P. Keating , Mo Dick Wong

In this work, we provide the first strong convergence result of numerical approximation of a general second order semilinear stochastic fractional order evolution equation involving a Caputo derivative in time of order $\alpha\in(\frac 34,…

Numerical Analysis · Mathematics 2021-09-08 Aurelien Junior Noupelah , Antoine Tambue

We establish large deviation formulas for linear statistics on the $N$ transmission eigenvalues $\{T_i\}$ of a chaotic cavity, in the framework of Random Matrix Theory. Given any linear statistics of interest $A=\sum_{i=1}^N a(T_i)$, the…

Mesoscale and Nanoscale Physics · Physics 2015-05-14 Pierpaolo Vivo , Satya N. Majumdar , Oriol Bohigas

In this paper we obtain some new estimates for the number of large values of Dirichlet polynomials. Our results imply new zero density estimates for the Riemann zeta function which give a small improvement on results of Bourgain and Jutila.

Number Theory · Mathematics 2019-09-27 Bryce Kerr

We provide a generalisation of Pinelis' Rademacher-Gaussian tail comparison to complex coefficients. We also establish uniform bounds on the probability that the magnitude of weighted sums of independent random vectors uniform on Euclidean…

Probability · Mathematics 2022-03-15 Giorgos Chasapis , Ruoyuan Liu , Tomasz Tkocz

We consider the problem of finding, for a given quadratic measure of non-uniformity of a set of $N$ points (such as $L_2$ star-discrepancy or diaphony), the asymptotic distribution of this discrepancy for truly random points in the limit…

Computational Physics · Physics 2009-10-30 Andre van Hameren , Ronald Kleiss , Jiri Hoogland

In this paper, we study the large deviation principle of invariant measures of stochastic reaction-diffusion lattice systems driven by multiplicative noise. We first show that any limit of a sequence of invariant measures of the stochastic…

Probability · Mathematics 2024-05-07 Bixiang Wang