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We propose a Hermite-Galerkin spectral method to numerically solve the spatially homogeneous Fokker-Planck-Landau equation with singular quadratic collision model. To compute the collision model, we adopt a novel approximation formulated by…

Numerical Analysis · Mathematics 2020-06-16 Ruo Li , Yanli Wang , Yixuan Wang

We study the convergence properties of a general inertial first-order proximal splitting algorithm for solving nonconvex nonsmooth optimization problems. Using the Kurdyka--\L ojaziewicz (KL) inequality we establish new convergence rates…

Optimization and Control · Mathematics 2016-09-14 Patrick R. Johnstone , Pierre Moulin

We study the long time behaviour of the kinetic Fokker-Planck equation with mean field interaction, whose limit is often called Vlasov-Fkker-Planck equation. We prove a uniform (in the number of particles) exponential convergence to…

Analysis of PDEs · Mathematics 2019-12-06 Arnaud Guillin , Wei Liu , Liming Wu , Chaoen Zhang

Strong convergence rates for time-discrete numerical approximations of semilinear stochastic evolution equations (SEEs) with smooth and regular nonlinearities are well understood in the literature. Weak convergence rates for time-discrete…

Probability · Mathematics 2021-11-02 Arnulf Jentzen , Ryan Kurniawan

We introduce a predictor-corrector discretisation scheme for the numerical integration of a class of stochastic differential equations and prove that it converges with weak order 1.0. The key feature of the new scheme is that it builds up…

Computation · Statistics 2024-02-01 Deniz Akyildiz , Dan Crisan , Joaquin Miguez

A numerical method is proposed for a class of stochastic control problems including singular behavior. This method solves an infinite-dimensional linear program equivalent to the stochastic control problem using a finite element type…

Probability · Mathematics 2018-06-11 Martin G. Vieten , Richard H. Stockbridge

We introduce a nonparametric algorithm to learn interaction kernels of mean-field equations for 1st-order systems of interacting particles. The data consist of discrete space-time observations of the solution. By least squares with…

Machine Learning · Statistics 2020-10-30 Quanjun Lang , Fei Lu

We study the strong rate of convergence of the Euler--Maruyama scheme for a multidimensional stochastic differential equation (SDE) $$ dX_t = b(X_t) \, dt + dL_t, $$ with irregular $\beta$-H\"older drift, $\beta > 0$, driven by a L\'evy…

Probability · Mathematics 2024-01-12 Oleg Butkovsky , Konstantinos Dareiotis , Máté Gerencsér

Consider a system of $n$ weakly interacting particles driven by independent Brownian motions. In many instances, it is well known that the empirical measure converges to the solution of a partial differential equation, usually called…

Probability · Mathematics 2020-07-28 Florian Bechtold , Fabio Coppini

We introduce a stochastic system of interacting particles which is expected to furnish as the number of particles goes to infinity a stochastic approach of the 2-D Keller-Segel model. In this note, we prove existence and some uniqueness for…

Probability · Mathematics 2016-02-01 Patrick Cattiaux , Laure Pédèches

We consider the numerical approximation of a general second order semi--linear parabolic stochastic partial differential equation (SPDE) driven by additive space-time noise. We introduce a new modified scheme using a linear functional of…

Numerical Analysis · Mathematics 2016-07-20 Gabriel J Lord , Antoine Tambue

The steady state of the Fokker-Planck equation corresponding to a density dependent one-step process is approximated by a suitable normal distribution. Starting from the master equations of the process, written in terms of the time…

Dynamical Systems · Mathematics 2016-09-16 Peter L. Simon , Eszter Sikolya

We study two schemes for a time-fractional Fokker-Planck equation with space- and time-dependent forcing in one space dimension. The first scheme is continuous in time and is discretized in space using a piecewise-linear Galerkin finite…

Numerical Analysis · Mathematics 2016-10-24 Kim Ngan Le , William McLean , Kassem Mustapha

We consider a system of stochastic interacting particles with general diffusion coefficient and drift functions and we study the types of collisions that arise in them. In particular, interactions between particles are inversely…

Probability · Mathematics 2025-09-30 Sergio Andraus , Nicole Hufnagel , Jacek Małecki

We study the strong approximation of the solutions to singular stochastic kinetic equations (also referred to as second-order SDEs) driven by $\alpha$-stable processes, using an Euler-type scheme inspired by [11]. For these equations, the…

Probability · Mathematics 2025-11-18 Chengcheng Ling

The strong rate of convergence of the Euler-Maruyama scheme for nondegenerate SDEs with irregular drift coefficients is considered. In the case of $\alpha$-H\"older drift in the recent literature the rate $\alpha/2$ was proved in many…

Probability · Mathematics 2021-03-09 Konstantinos Dareiotis , Máté Gerencsér

In this article, we present an $O(N \log N)$ rapidly convergent algorithm for the numerical approximation of the convolution integral with radially symmetric weakly singular kernels and compactly supported densities. To achieve the reduced…

Numerical Analysis · Mathematics 2021-07-09 Awanish Kumar Tiwari , Ambuj Pandey , Jagabandhu Paul , Akash Anand

We consider large systems of stochastic interacting particles through discontinuous kernels which has vision geometrical constrains. We rigorously derive a Vlasov-Fokker-Planck type of kinetic mean-field equation from the corresponding…

Analysis of PDEs · Mathematics 2017-05-12 Young-Pil Choi , Samir Salem

This paper continues our survey about the mean-field derivation of the two-dimensional signal-dependent Keller-Segel system studied in [1]. Therefore, we consider the same system of moderately interacting particles as before. The difference…

Probability · Mathematics 2026-05-18 Lukas Bol , Li Chen

We establish a general framework to study the rate of convergence of a Euler type approximation scheme with decreasing time steps to the invariant measure, for a general class of stochastic systems. The error is measured in general…

Probability · Mathematics 2026-03-03 Aurélien Alfonsi , Vlad Bally , Arturo Kohatsu-Higa