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We use an expansion in angular mode functions in order to solve the Boltzmann equation for a gluon plasma undergoing longitudinal expansion. By comparing with the exact solution obtained numerically by other means we show that the expansion…

High Energy Physics - Phenomenology · Physics 2019-09-11 Jean-Paul Blaizot , Naoto Tanji

Self-interacting diffusions are solutions to SDEs with a drift term depending on the process and its normalized occupation measure $\mu_t$ (via an interaction potential and a confinement potential). We establish a relation between the…

Probability · Mathematics 2008-02-17 A. Kurtzmann

We study a numerical method to compute probability density functions of solutions of stochastic differential equations. The method is sometimes called the numerical path integration method and has been shown to be fast and accurate in…

Dynamical Systems · Mathematics 2016-11-29 Linghua Chen , Espen Robstad Jakobsen , Arvid Naess

In a celebrated paper, Dyson shows that the spectrum of an n\times n random Hermitian matrix, diffusing according to an Ornstein-Uhlenbeck process, evolves as n noncolliding Brownian motions held together by a drift term. The universal edge…

Probability · Mathematics 2007-05-23 Mark Adler , Pierre van Moerbeke

We develop a Hilbert-space approach to the diffusion process of the Brownian motion in a bounded domain with random jumps from the boundary introduced by Ben-Ari and Pinsky in 2007. The generator of the process is introduced by a diffusion…

Spectral Theory · Mathematics 2021-07-06 David Krejcirik , Vladimir Lotoreichik , Konstantin Pankrashkin , Matěj Tušek

In this paper, we present the asymptotic theory for integrated functions of increments of Brownian local times in space. Specifically, we determine their first-order limit, along with the asymptotic distribution of the fluctuations. Our key…

Probability · Mathematics 2023-11-03 Simon Campese , Nicolas Lengert , Mark Podolskij

We establish sublinear growth of correctors in the context of stochastic homogenization of linear elliptic PDEs. In case of weak decorrelation and "essentially Gaussian" coefficient fields, we obtain optimal (stretched exponential)…

Analysis of PDEs · Mathematics 2015-09-24 Julian Fischer , Felix Otto

In this work, we study the numerical approximation of a class of singular fully coupled forward backward stochastic differential equations. These equations have a degenerate forward component and non-smooth terminal condition. They are…

Numerical Analysis · Mathematics 2022-08-17 Jean-François Chassagneux , Mohan Yang

In contrast with the well-known methods of matching asymptotics and multiscale (or compound) asymptotics, the " functional analytic approach " of Lanza de Cristoforis (Analysis 28, 2008) allows to prove convergence of expansions around…

Analysis of PDEs · Mathematics 2018-07-26 Martin Costabel , Matteo Dalla Riva , Monique Dauge , Paolo Musolino

We introduce Functional Diffusion Processes (FDPs), which generalize score-based diffusion models to infinite-dimensional function spaces. FDPs require a new mathematical framework to describe the forward and backward dynamics, and several…

Machine Learning · Computer Science 2023-12-19 Giulio Franzese , Giulio Corallo , Simone Rossi , Markus Heinonen , Maurizio Filippone , Pietro Michiardi

Sharp asymptotic lower bounds of the expected quadratic variation of discretization error in stochastic integration are given. The theory relies on inequalities for the kurtosis and skewness of a general random variable which are themselves…

Probability · Mathematics 2012-04-04 Masaaki Fukasawa

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

We consider the problem of the approximation of the solution of a one-dimensional SDE with non-globally Lipschitz drift and diffusion coefficients behaving as $x^\alpha$, with $\alpha>1$. We propose an (semi-explicit) exponential-Euler…

Probability · Mathematics 2022-11-30 Mireille Bossy , Jean Francois Jabir , Kerlyns Martinez

Classical diffusion in a random medium involves an exponential functional of Brownian motion. This functional also appears in the study of Brownian diffusion on a Riemann surface of constant negative curvature. We analyse in detail this…

Condensed Matter · Physics 2016-08-31 Alain COMTET , Cecile MONTHUS

Recently there has been a renewed interest in asymptotic Euler-MacLaurin formulas, partly due to applications to spectral theory of differential operators. Using elementary means, we recover such formulas for compactly supported smooth…

Classical Analysis and ODEs · Mathematics 2014-12-01 Yohann Le Floch , Álvaro Pelayo

We study the long-time dynamics of the nonlinear processes modeled by diffusion-transport partial differential equations in non-divergence form with drifts. The solutions are subject to some inhomogeneous Dirichlet boundary condition.…

Analysis of PDEs · Mathematics 2026-02-11 Luan Hoang , Akif Ibragimov

Is studied asymptotic expansion for solution of singularly perturbed equation for functional of Markovian evolution in Rd. The view of regular and singular parts of solution is found.

Probability · Mathematics 2009-10-21 I. V. Samoilenko

In this paper we study perpetual integral functionals of diffusions. Our interest is focused on cases where such functionals can be expressed as first hitting times for some other diffusions. In particular, we generalize the result which…

Probability · Mathematics 2007-05-23 P. Salminen , O. Wallin

We construct asymptotic expansions for ordinary differential equations with highly oscillatory forcing terms, focussing on the case of multiple, non-commensurate frequencies. We derive an asymptotic expansion in inverse powers of the…

Numerical Analysis · Mathematics 2023-07-19 Marissa Condon , Alfredo Deano , Jing Gao , Arieh Iserles

We develop a novel approach towards causal inference. Rather than structural equations over a causal graph, we learn stochastic differential equations (SDEs) whose stationary densities model a system's behavior under interventions. These…

Machine Learning · Computer Science 2024-03-19 Lars Lorch , Andreas Krause , Bernhard Schölkopf
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