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We consider classical solutions to the kinetic Fokker-Planck equation on a bounded domain $\mathcal O \subset~\mathbb{R}^d$ in position, and we obtain a probabilistic representation of the solutions using the Langevin diffusion process with…

Probability · Mathematics 2022-03-16 Tony Lelièvre , Mouad Ramil , Julien Reygner

We lay the theoretical and mathematical foundations of the square root of Browniam motion and we prove the existence of such a process. In doing so, we consider Brownian motion on quantized noncommutative Riemannian manifolds and show how a…

Quantum Physics · Physics 2021-05-13 Marco Frasca , Alfonso Farina , Moawia Alghalith

We demonstrate the equivalence of a Non--Markovian evolution equation with a linear memory--coupling and a Fokker--Planck equation (FPE). In case the feedback term offers a direct and permanent coupling of the current probability density to…

Statistical Mechanics · Physics 2009-11-11 Knud Zabrocki , Steffen Trimper , Svetlana Tatur , Reinhard Mahnke

A dynamical picture of phylogenetic evolution is given in terms of Markov models on a state space, comprising joint probability distributions for character types of taxonomic classes. Phylogenetic branching is a process which augments the…

Populations and Evolution · Quantitative Biology 2009-11-10 P. D. Jarvis , J. D. Bashford , J. G. Sumner

We study the asymptotic behavior of continuous-time, time-inhomogeneous Markovian quantum dynamics in a stationary random environment. Under mild faithfulness and eventually positivity-improving assumptions, the normalized evolution…

Quantum Physics · Physics 2025-09-12 Lubashan Pathirana , Jeffrey Schenker

We consider the problem to steer a linear dynamical system with full state observation from an initial gaussian distribution in state-space to a final one with minimum energy control. The system is stochastically driven through the control…

Systems and Control · Computer Science 2014-08-12 Yongxin Chen , Tryphon Georgiou , Michele Pavon

A large class of physically important nonlinear and nonhomogeneous evolution problems, characterized by advection-like and diffusion-like processes, can be usefully studied by a time-differential form of Kolmogorov's solution of the…

Data Analysis, Statistics and Probability · Physics 2007-08-24 R. G. Keanini

The Feynman-Kac formula provides a way to understand solutions to elliptic partial differential equations in terms of expectations of continuous time Markov processes. This connection allows for the creation of numerical schemes for…

Numerical Analysis · Mathematics 2021-08-11 Cameron Martin , Hongyuan Zhang , Julia Costacurta , Mihai Nica , Adam R Stinchcombe

In this paper, when a given symmetric Markov process X satisfies the stability of global heat kernel two-sided (upper) estimates by Markov perturbations, we give a necessary and sufficient condition on the stability of global two-sided…

Probability · Mathematics 2022-04-05 Daehong Kim , Panki Kim , Kazuhiro Kuwae

Functionals of a stochastic process Y(t) model many physical time-extensive observables, e.g. particle positions, local and occupation times or accumulated mechanical work. When Y(t) is a normal diffusive process, their statistics are…

Statistical Mechanics · Physics 2017-04-05 Andrea Cairoli , Adrian Baule

In this work, we investigate the compactness and the long time behavior of killed Feynman-Kac semigroups of various processes arising from statistical physics with very general singular Schr{\"o}dinger potentials. The processes we consider…

Probability · Mathematics 2026-04-08 Arnaud Guillin , D I Lu , Boris Nectoux , Liming Wu

This work focuses on the mean field stochastic partial differential equations with nonlinear kernels. We first prove the existence and uniqueness of strong and weak solutions for mean field stochastic partial differential equations in the…

Probability · Mathematics 2025-08-19 Wei Hong , Shihu Li , Wei Liu

The diffusion equation is the primary tool to study the movement dynamics of a free Brownian particle, but when spatial heterogeneities in the form of permeable interfaces are present, no fundamental equation has been derived. Here we…

Statistical Mechanics · Physics 2022-09-14 Toby Kay , Luca Giuggioli

Motivated by the phenomenon of duality for interacting particle systems we introduce two classes of Pfaffian kernels describing a number of Pfaffian point processes in the `bulk' and at the `edge'. Using the probabilistic method due to Mark…

Probability · Mathematics 2023-05-04 Will FitzGerald , Roger Tribe , Oleg Zaboronski

We extend the unified kernel framework for transport equations and Koopman eigenfunctions, developed in previous work by the authors for deterministic systems, to stochastic differential equations (SDEs). In the deterministic setting, three…

Dynamical Systems · Mathematics 2026-03-03 Boumediene Hamzi , Houman Owhadi , Umesh Vaidya

In this article we investigate entropic interpolations. These measure valued curves describe the optimal solutions of the Schr{\"o}dinger problem [Sch31], which is the problem of finding the most likely evolution of a system of independent…

Analysis of PDEs · Mathematics 2021-07-09 Gauthier Clerc , Giovanni Conforti , Ivan Gentil

In 1905, Einstein's theory of Brownian motion supported the molecular basis of the diffusion equation and introduced two complementary viewpoints: a deterministic field description and a probabilistic formulation based on stochastic…

We study a class of dynamical semigroups $(\mathbb{L}^n)_{n\in\mathbb{N}}$ that emerge, by a Feynman--Kac type formalism, from a random quantum dynamical system…

Mathematical Physics · Physics 2024-09-25 Jean-François Bougron , Alain Joye , Claude-Alain Pillet

We derive, through subordination techniques, a generalized Feynman-Kac equation in the form of a time fractional Schrodinger equation. We relate such equation to a functional which we name the subordinated local time. We demonstrate through…

Statistical Mechanics · Physics 2023-05-01 Toby Kay , Luca Giuggioli

Kingman derived the Ewens sampling formula for random partitions describing the genetic variation in a neutral mutation model defined by a Poisson process of mutations along lines of descent governed by a simple coalescent process, and…

Probability · Mathematics 2007-05-23 Rui Dong , Alexander Gnedin , Jim Pitman