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Random fields in nature often have, to a good approximation, Gaussian characteristics. We present the mathematical framework for a new and simple method for investigating the non-Gaussian contributions, based on counting the maxima and…

Statistical Mechanics · Physics 2012-10-26 T. H. Beuman , A. M. Turner , V. Vitelli

We study deviation probabilities for the number of high positioned particles in branching Brownian motion, and confirm a conjecture of Derrida and Shi (2016). We also solve the corresponding problem for the two-dimensional discrete Gaussian…

Probability · Mathematics 2019-08-22 Elie Aïdékon , Yueyun Hu , Zhan Shi

We prove that under fairly general conditions properly rescaled determinantal random point field converges to a generalized Gaussian random process.

Probability · Mathematics 2007-05-23 Alexander Soshnikov

We consider parabolic PDEs with randomly switching boundary conditions. In order to analyze these random PDEs, we consider more general stochastic hybrid systems and prove convergence to, and properties of, a stationary distribution.…

Probability · Mathematics 2020-03-13 Sean D. Lawley , Jonathan C. Mattingly , Michael C. Reed

We investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial…

Numerical Analysis · Mathematics 2022-01-05 Erika Hausenblas , Mihály Kovács

We consider the limit behavior of partition function of directed polymers in random environment represented by linear model instead of a family of i.i.d.variables in $1+1$ dimensions. Under the assumption that the correlation decays…

Probability · Mathematics 2019-12-19 Guanglin Rang

In this article, we establish a probabilistic representation for the second-order moment of the solution of stochastic heat equation in $[0,1] \times \bR^d$, with multiplicative noise, which is fractional in time and colored in space. This…

Probability · Mathematics 2009-05-19 Raluca Balan

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise…

Probability · Mathematics 2010-10-12 Eulalia Nualart , Lluís Quer-Sardanyons

Polarization of light signifies transversal, anisotropic and asymmetrical statistical property of electromagnetic radiation about direction of propagation. Traditionally, optical-polarization is characterized by Stokes theory susceptible to…

Optics · Physics 2015-06-15 Ravi S. Singh , Hari Prakash

In this paper, we study the stochastic heat equation with a general multiplicative Gaussian noise that is white in time and colored in space. Both regularity and strict positivity of the densities of the solution have been established. The…

Probability · Mathematics 2019-02-08 Le Chen , Jingyu Huang

We consider a system of d non-linear stochastic heat equations in spatial dimension 1 driven by d-dimensional space-time white noise. The non-linearities appear both as additive drift terms and as multipliers of the noise. Using techniques…

Probability · Mathematics 2007-05-23 Robert C. Dalang , Davar Khoshnevisan , Eulalia Nualart

We establish a probabilistic representation for a wide class of linear deterministic p.d.e.s with potential term, including the wave equation in spatial dimensions 1 to 3. Our representation applies to the heat equation, where it is related…

Probability · Mathematics 2011-02-18 Robert C. Dalang , Carl Mueller , Roger Tribe

This work is concerned with a simple model for a polar fluid, a Gaussian field model based on the excess density and on the polarization. It is a convenient framework to implement the dielectric properties of correlated liquids that stem…

Chemical Physics · Physics 2018-04-04 Hélène Berthoumieux

We consider the numerical approximation of Gaussian random fields on closed surfaces defined as the solution to a fractional stochastic partial differential equation (SPDE) with additive white noise. The SPDE involves two parameters…

Numerical Analysis · Mathematics 2024-05-17 Andrea Bonito , Diane Guignard , Wenyu Lei

We consider the polarization of thermal emission in the near-field of various materials including dielectrics and metallic systems with resonant surface modes. We find that at thermal equilibrium, the degree of polarization exhibits spatial…

Optics · Physics 2016-05-25 Manabu Machida , Evgenii Narimanov , John C. Schotland

This paper investigates an inverse potential problem for the stochastic heat equation driven by space-time Gaussian noise, which is spatially colored and temporally white. The objective is to determine the covariance operator of the random…

Probability · Mathematics 2025-02-10 Peijun Li , Xiangchan Zhu , Yichun Zhu

Random fields in nature often have, to a good approximation, Gaussian characteristics. For such fields, the relative densities of umbilical points -- topological defects which can be classified into three types -- have certain fixed values.…

Statistical Mechanics · Physics 2013-08-09 A. M. Turner , T. H. Beuman , V. Vitelli

Polar duality is a well-known concept from convex geometry and analysis. In the present paper, we study two symplectically covariant versions of polar duality keeping in mind their applications to quantum mechanics. The first variant makes…

Mathematical Physics · Physics 2023-09-15 Maurice de Gosson , Charlyne de Gosson

We solve the infinite-dimensional stochastic differential equations (ISDEs) describing an infinite number of Brownian particles in $ \mathbb{R}^+$ interacting through the two-dimensional Coulomb potential. The equilibrium states of the…

Probability · Mathematics 2015-05-12 Ryuich Honda , Hirofumi Osada

Numerical methods for stochastic partial differential equations typically estimate moments of the solution from sampled paths. Instead, we shall directly target the deterministic equations satisfied by the first and second moments, as well…

Numerical Analysis · Mathematics 2020-11-17 Kristin Kirchner