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It is long known that the Fokker-Planck equation with prescribed constant coefficients of diffusion and linear friction describes the ensemble average of the stochastic evolutions in velocity space of a Brownian test particle immersed in a…

Mathematical Physics · Physics 2009-11-11 Michael Kiessling , Carlo Lancellotti

We characterize a stochastic dynamical system with tempered stable noise, by examining its probability density evolution. This probability density function satisfies a nonlocal Fokker-Planck equation. First, we prove a superposition…

Dynamical Systems · Mathematics 2021-06-02 Li Lin , Jinqiao Duan , Xiao Wang , Yanjie Zhang

The unified description of diffusion processes that cross over from a ballistic behavior at short times to normal or anomalous diffusion (sub- or superdiffusion) at longer times is constructed on the basis of a non-Markovian generalization…

Statistical Mechanics · Physics 2013-03-26 Valery Ilyin , Itamar Procaccia , Anatoly Zagorodny

Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical properties, such as mean-field convergence results for non-convex loss functions. In this work, we…

Optimization and Control · Mathematics 2025-07-01 Tim Roith , Leon Bungert , Philipp Wacker

In recent years, the paradigm of cloud computing has emerged as an architecture for computing that makes use of distributed (networked) computing resources. In this paper, we consider a distributed computing algorithmic scheme for…

Optimization and Control · Mathematics 2017-09-22 Shi Pu , Alfredo Garcia

In this paper, we develop a theoretical framework for nonlinear stochastic optimal control problems with optimal stopping by establishing a density-based deterministic representation of the underlying diffusion. For state-independent…

Optimization and Control · Mathematics 2026-04-15 Akan Selim , Siddhartha Ganguly , Ali Pakniyat , Panagiotis Tsiotras

Diffusion processes have been applied with great success to model the dynamics of large populations throughout science, in particular biology. One advantage is that they bridge two different scales: the microscopic and the macroscopic one.…

Neurons and Cognition · Quantitative Biology 2013-09-11 Marc de Kamps

We consider a stochastic logistic growth model involving both birth and death rates in the drift and diffusion coefficients for which extinction eventually occurs almost surely. The associated complete Fokker-Planck equation describing the…

Statistics Theory · Mathematics 2013-07-09 Fabien Campillo , Marc Joannides , Irène Larramendy-Valverde

As a counterpoint to classical stochastic particle methods for diffusion, we develop a deterministic particle method for linear and nonlinear diffusion. At first glance, deterministic particle methods are incompatible with diffusive partial…

Analysis of PDEs · Mathematics 2019-03-05 José Antonio Carrillo , Katy Craig , Francesco S. Patacchini

We consider a pure-jump stable Cox-Ingersoll-Ross ($\alpha$-stable CIR) process driven by a non-symmetric stable L{\'e}vy process with jump activity $\alpha$ $\in$ (1, 2) and we address the joint estimation of drift, scaling and jump…

Probability · Mathematics 2024-02-13 Elise Bayraktar , Emmanuelle Clément

This report provides a description of unbunched beam stochastic cooling in the framework of control theory. The main interest in the investigation is concentrated on the beam stability in an active cooling system. A stochastic cooling…

acc-phys · Physics 2008-02-03 O. Meincke

We present a new algorithm to optimize distributions defined implicitly by parameterized stochastic diffusions. Doing so allows us to modify the outcome distribution of sampling processes by optimizing over their parameters. We introduce a…

We obtain equilibration rates for a one-dimensional nonlocal Fokker-Planck equation with time-dependent diffusion coefficient and drift, modeling the relaxation of a large swarm of robots, feeling each other in terms of their distance,…

Analysis of PDEs · Mathematics 2023-06-06 Ferdinando Auricchio , Giuseppe Toscani , Mattia Zanella

Path integral techniques for the pricing of financial options are mostly based on models that can be recast in terms of a Fokker-Planck differential equation and that, consequently, neglect jumps and only describe drift and diffusion. We…

Pricing of Securities · Quantitative Finance 2010-11-08 L. Z. J. Liang , D. Lemmens , J. Tempere

We propose a systematic method to derive the asymptotic behaviour of the persistence distribution, for a large class of stochastic processes described by a general Fokker-Planck equation in one dimension. Theoretical predictions are…

Statistical Mechanics · Physics 2009-10-31 Jean Farago

We discuss kinetic-based particle optimization methods and variable-sample strategies for problems where the cost function represents the expected value of a random mapping. Kinetic-based optimization methods rely on a consensus mechanism…

Optimization and Control · Mathematics 2025-07-08 Sabrina Bonandin , Michael Herty

Identification of nonlinear dynamical systems is crucial across various fields, facilitating tasks such as control, prediction, optimization, and fault detection. Many applications require methods capable of handling complex systems while…

Machine Learning · Statistics 2024-11-05 Luc Brogat-Motte , Riccardo Bonalli , Alessandro Rudi

We present a theoretical investigation of the stochastic dynamics of a damped particle in a tilted periodic potential with a double well per period. By applying the matrix continued fraction technique to the Fokker-Planck equation in…

Statistical Mechanics · Physics 2024-08-15 Martin Žonda , Wolfgang Belzig , Edward Goldobin , Tomáš Novotný

We consider the parametric estimation of the volatility and jump activity in a stable Cox-Ingersoll-Ross ($\alpha$-stable CIR) model driven by a standard Brownian Motion and a non-symmetric stable L\'evy process with jump activity $\alpha…

Statistics Theory · Mathematics 2024-08-01 Elise Bayraktar , Emmanuelle Clément

Solving the Fokker-Planck equation for high-dimensional complex dynamical systems remains a pivotal yet challenging task due to the intractability of analytical solutions and the limitations of traditional numerical methods. In this work,…

Machine Learning · Computer Science 2025-09-04 Naoufal El Bekri , Lucas Drumetz , Franck Vermet