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We propose a novel non-parametric learning paradigm for the identification of drift and diffusion coefficients of multi-dimensional non-linear stochastic differential equations, which relies upon discrete-time observations of the state. The…

Machine Learning · Computer Science 2025-03-11 Riccardo Bonalli , Alessandro Rudi

We investigate the Cauchy problem and the diffusion asymptotics for a spatially inhomogeneous kinetic model associated to a nonlinear Fokker-Planck operator. We derive the global well-posedness result with instantaneous smoothness effect,…

Analysis of PDEs · Mathematics 2024-03-13 Francesca Anceschi , Yuzhe Zhu

The engineering and control of devices at the quantum-mechanical level--such as those consisting of small numbers of atoms and photons--is a delicate business. The fundamental uncertainty that is inherently present at this scale manifests…

Probability · Mathematics 2009-05-02 Luc Bouten , Ramon van Handel , Matthew R. James

While accurate simulations of dense gas flows far from the equilibrium can be achieved by Direct Simulation adapted to the Enskog equation, the significant computational demand required for collisions appears as a major constraint. In order…

Computational Physics · Physics 2023-08-11 Mohsen Sadr , M. Hossein Gorji

We investigate the effects of relatively rapid variations of the boundaries of an overmoded cavity on the stochastic properties of its interior acoustic or electromagnetic field. For quasi-static variations, this field can be represented as…

Classical Physics · Physics 2009-11-13 L. R. Arnaut

Given a solution of a nonlinear wave equation on the flat space-time (with a real analytic nonlinearity), we relate its Cauchy data at two different times by nonlinear representation formulas in terms of asymptotic series. We first show how…

Analysis of PDEs · Mathematics 2008-02-27 Dikanaina Harrivel , Fréderic Hélein

Over the last decade, nonparametric methods have gained increasing attention for modeling complex data structures due to their flexibility and minimal structural assumptions. In this paper, we study a general multivariate nonparametric…

Methodology · Statistics 2026-03-18 Kunal Rai , Archi Roy , Itai Dattner , Soudeep Deb

Starting from microscopic interaction rules we derive kinetic models of Fokker--Planck type for vehicular traffic flow. The derivation is based on taking a suitable asymptotic limit of the corresponding Boltzmann model. As particular cases,…

Mathematical Physics · Physics 2010-09-16 M. Herty , L. Pareschi

We introduce an efficient method to simulate dynamics of an interacting quantum impurity coupled to non-interacting fermionic reservoirs. Viewing the impurity as an open quantum system, we describe the reservoirs by their Feynman-Vernon…

Strongly Correlated Electrons · Physics 2023-06-07 Julian Thoenniss , Michael Sonner , Alessio Lerose , Dmitry A. Abanin

We argue that the complex numbers are an irreducible object of quantum probability. This can be seen in the measurements of geometric phases that have no classical probabilistic analogue. Having complex phases as primitive ingredient…

General Relativity and Quantum Cosmology · Physics 2014-11-17 Charis Anastopoulos

To describe stochastic quantum processes I propose an integral equation of Volterra type which is not generally transformable to any differential one. The process is a composition of ordinary quantum evolution which admits presence of a…

Quantum Physics · Physics 2007-05-23 Jerzy Stryla

A possible approach to description of the non equilibrium system has been proposed. Based on the Fokker-Plank equation in term of energy for non equilibrium distribution function of macroscopical system was obtained the stationary solution…

Statistical Mechanics · Physics 2008-08-08 Bohdan Lev

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over…

Statistical Mechanics · Physics 2009-10-31 J. C. Lemm , J. Uhlig , A. Weiguny

In this work, our prime focus is to study the one to one correspondence between the conduction phenomena in electrical wires with impurity and the scattering events responsible for particle production during stochastic inflation and…

High Energy Physics - Theory · Physics 2019-04-16 Sayantan Choudhury , Arkaprava Mukherjee , Prashali Chauhan , Sandipan Bhattacherjee

We consider the development of high order asymptotic-preserving linear multistep methods for kinetic equations and related problems. The methods are first developed for BGK-like kinetic models and then extended to the case of the full…

Numerical Analysis · Mathematics 2016-03-06 Giacomo Dimarco , Lorenzo Pareschi

We recently showed that the S&P500 stock market index is well described by Tsallis non-extensive statistics and nonlinear Fokker-Planck time evolution. We argued that these results should be applicable to a broad range of markets and…

Statistical Mechanics · Physics 2008-12-02 Fredrick Michael , M. D. Johnson

In this work, we develop novel structure-preserving numerical schemes for a class of nonlinear Fokker--Planck equations with nonlocal interactions. Such equations can cover many cases of importance, such as porous medium equations with…

Numerical Analysis · Mathematics 2020-08-18 Chenghua Duan , Wenbin Chen , Chun Liu , Xingye Yue , Shenggao Zhou

Stochastic nonequilibrium exclusion models are treated using a real space scaling approach. The method exploits the mapping between nonequilibrium and quantum systems, and it is developed to accommodate conservation laws and duality…

Statistical Mechanics · Physics 2009-11-11 T. Hanney , R. B. Stinchcombe

We consider several stochastic service systems, and study the asymptotic behavior of the moments of various quantities that have application to models for random interval graphs and algorithms for searching for an idle server or empty…

Probability · Mathematics 2011-08-04 Patrick Eschenfeldt , Ben Gross , Nicholas Pippenger

Stochastic differential equations play an important role in various applications when modeling systems that have either random perturbations or chaotic dynamics at faster time scales. The time evolution of the probability distribution of a…

Numerical Analysis · Mathematics 2022-11-11 Yao Li , Caleb Meredith