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Related papers: Linearization of ergodic McKean SDEs and applicati…

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We consider certain random matrix eigenvalue dynamics, akin to Dyson Brownian motion, introduced by Rider and Valko. We show that from every initial condition, including ones involving coinciding coordinates, the dynamics, enhanced with…

Probability · Mathematics 2024-08-27 Theodoros Assiotis , Zahra Sadat Mirsajjadi

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the…

Methodology · Statistics 2024-11-12 Ajay Jasra , Mohamed Maama , Raul Tempone

We demonstrate the non-ergodicity of a simple Markovian stochastic processes with space-dependent diffusion coefficient $D(x)$. For power-law forms $D(x) \simeq|x|^{\alpha}$, this process yield anomalous diffusion of the form $\ < x^2(t)\ >…

Statistical Mechanics · Physics 2015-06-15 Andrey G. Cherstvy , Aleksei V. Chechkin , Ralf Metzler

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently appear in applications…

Methodology · Statistics 2026-02-03 Elsiddig Awadelkarim , Neil K. Chada , Ajay Jasra

We distinguish a mechanical representation of the world in terms of point masses with positions and momenta and the chemical representation of the world in terms of populations of different individuals, each with intrinsic stochasticity,…

Statistical Mechanics · Physics 2019-05-07 Hong Qian

The propagation of electromagnetic waves in general media is modeled by the time-dependent Maxwell's partial differential equations (PDEs), coupled with constitutive laws that describe the response of the media. In this work, we focus on…

Numerical Analysis · Mathematics 2017-10-11 Vrushali A. Bokil , Yingda Cheng , Yan Jiang , Fengyan Li

We study generalizations of It\^{o}-Langevin dynamics consistent within nonextensive thermostatistics. The corresponding stochastic differential equations are shown to be connected with a wide class of nonlinear Fokker-Planck equations…

Statistical Mechanics · Physics 2022-07-14 Leonardo Santos

In this article, we solve the problem of the long time behaviour of transition probabilities of time-inhomogeneous Markov processes and give a unified approach to stochastic differential equations (SDEs) with periodic, quasi-periodic,…

Probability · Mathematics 2023-07-18 Chunrong Feng , Baoyou Qu , Huaizhong Zhao

Of stochastic differential equations, diffusion processes have been adopted in numerous applications, as more relevant and flexible models. This paper studies diffusion processes in a different setting, where for a given stationary…

Probability · Mathematics 2024-12-31 Saber Jafarizadeh

We study the limiting behaviour of the empirical measure of a system of diffusions interacting through their ranks when the number of diffusions tends to infinity. We prove that the limiting dynamics is given by a McKean-Vlasov evolution…

Probability · Mathematics 2010-08-30 Mykhaylo Shkolnikov

Pathwise uniqueness for multi-dimensional stochastic McKean--Vlasov equation is established under moderate regularity conditions on the drift and diffusion coefficients. Both drift and diffusion depend on the marginal measure of the…

Probability · Mathematics 2023-01-02 Alexander Veretennikov

We study the long time behavior of an advection-diffusion equation with a random shear flow which depends on a stationary Ornstein-Uhlenbeck (OU) process in parallel-plate channels enforcing the no-flux boundary conditions. We derive a…

Analysis of PDEs · Mathematics 2020-12-15 Lingyun Ding , Richard M. McLaughlin

We derive a general scheme to construct infinitely many probabilistic counterparts for solutions to nonlinear PDEs by recasting the latter as different nonlinear Fokker--Planck equations and by constructing, for each of these equations, a…

Probability · Mathematics 2026-04-29 Ehsan Abedi , Florian Bechtold , Marco Rehmeier

The aim of this article is to construct solutions to second order in time stochastic partial differential equations and to show hypocoercivity of the corresponding transition semigroups. More generally, we analyze non-linear…

Probability · Mathematics 2023-06-21 Benedikt Eisenhuth , Martin Grothaus

This paper establishes a quantitative, uniform-in-time diffusion approximation for the joint law of a broad class of fully coupled multiscale stochastic systems. We derive a precise characterization of the limiting joint distribution as a…

Probability · Mathematics 2026-04-02 Longjie Xie , Xicheng Zhang

In this paper, we investigate the well-posedness of the martingale problem associated to non-linear stochastic differential equations (SDEs) in the sense of McKean-Vlasov under mild assumptions on the coefficients as well as classical…

Classical Analysis and ODEs · Mathematics 2021-04-23 Paul-Eric Chaudru de Raynal , Noufel Frikha

In this paper, we first establish well-posedness results for one-dimensional McKean-Vlasov stochastic differential equations (SDEs) and related particle systems with a measure-dependent drift coefficient that is discontinuous in the spatial…

Probability · Mathematics 2024-03-29 Gunther Leobacher , Christoph Reisinger , Wolfgang Stockinger

The long time behavior of an absorbed Markov process is well described by the limiting distribution of the process conditioned to not be killed when it is observed. Our aim is to give an approximation's method of this limit, when the…

Probability · Mathematics 2009-05-25 Denis Villemonais

The paper studies an improved estimate for the rate of convergence for nonlinear homogeneous discrete-time Markov chains. These processes are nonlinear in terms of the distribution law. Hence, the transition kernels are dependent on the…

Probability · Mathematics 2021-05-21 Aleksandr Shchegolev