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We review the Random Batch Methods (RBM) for interacting particle systems consisting of $N$-particles, with $N$ being large. The computational cost of such systems is of $O(N^2)$, which is prohibitively expensive. The RBM methods use small…

Numerical Analysis · Mathematics 2021-04-12 Shi Jin , Lei Li

Random Batch Methods (RBM) for mean-field interacting particle systems enable the reduction of the quadratic computational cost associated with particle interactions to a near-linear cost. The essence of these algorithms lies in the random…

Numerical Analysis · Mathematics 2024-01-02 Lorenzo Pareschi , Mattia Zanella

The Random Batch Method (RBM) is an effective technique to reduce the computational complexity when solving certain stochastic differential problems (SDEs) involving interacting particles. It can transform the computational complexity from…

Numerical Analysis · Mathematics 2024-12-23 Yanshun Zhao , Jingrun Chen , Zhiwen Zhang

The Random Batch Method (RBM) proposed in [Jin et al. J Comput Phys, 2020] is an efficient algorithm for simulating interacting particle systems (IPS). In this paper, we investigate the Random Batch Method with replacement (RBM-r), which is…

Numerical Analysis · Mathematics 2025-11-04 Zhenhao Cai , Jian-Guo Liu , Yuliang Wang

We investigate several important issues regarding the Random Batch Method (RBM) for second order interacting particle systems. We first show the uniform-in-time strong convergence for second order systems under suitable contraction…

Numerical Analysis · Mathematics 2020-12-02 Shi Jin , Lei Li , Yiqun Sun

In many real-world scenarios, the underlying random fluctuations are non-Gaussian, particularly in contexts where heavy-tailed data distributions arise. A typical example of such non-Gaussian phenomena calls for L\'evy noise, which…

Numerical Analysis · Mathematics 2025-11-27 Jian-Guo Liu , Yuliang Wang

The random batch method (RBM) proposed in [Jin et al., J. Comput. Phys., 400(2020), 108877] for large interacting particle systems is an efficient with linear complexity in particle numbers and highly scalable algorithm for $N$-particle…

Numerical Analysis · Mathematics 2024-03-14 Zhenyu Huang , Shi Jin , Lei Li

In this article, we focus on two toy models : the Curie-Weiss model and the system of $N$ particles in linear interactions in a double well confining potential. Both models, which have been extensively studied, describe a large system of…

Probability · Mathematics 2023-08-04 Arnaud Guillin , Pierre Le Bris , Pierre Monmarché

We consider in this paper random batch interacting particle methods for solving the Poisson-Nernst-Planck (PNP) equations, and thus the Poisson-Boltzmann (PB) equation as the equilibrium, in the external unbounded domain. To justify the…

Numerical Analysis · Mathematics 2022-03-25 Lei Li , Jian-Guo Liu , Yijia Tang

This paper discusses a numerical method for computing the evolution of large interacting system of quantum particles. The idea of the random batch method is to replace the total interaction of each particle with the $N-1$ other particles by…

Analysis of PDEs · Mathematics 2019-12-17 François Golse , Shi Jin , Thierry Paul

A random-batch method for multi-species interacting particle systems is proposed, extending the method of S. Jin, L. Li, and J.-G. Liu [J. Comput. Phys. 400 (2020), 108877]. The idea of the algorithmus is to randomly divide, at each time…

Numerical Analysis · Mathematics 2022-05-18 Esther S. Daus , Markus Fellner , Ansgar Jüngel

The Random Batch Method (RBM) [S. Jin, L. Li and J.-G. Liu, Random Batch Methods (RBM) for interacting particle systems, J. Comput. Phys. 400 (2020) 108877] is not only an efficient algorithm for simulating interacting particle systems, but…

Numerical Analysis · Mathematics 2025-10-30 Shi Jin , Yuelin Wang , Yuliang Wang

The Random Batch Method proposed in our previous work [Jin et al., J. Comput. Phys., 400(1), 2020] is not only a numerical method for interacting particle systems and its mean-field limit, but also can be viewed as a model of particle…

Probability · Mathematics 2020-11-24 Shi Jin , Lei Li

The random batch method provides an efficient algorithm for computing statistical properties of a canonical ensemble of interacting particles. In this work, we study the error estimates of the fully discrete random batch method, especially…

Probability · Mathematics 2022-09-01 Xuda Ye , Zhennan Zhou

Random batch algorithms are constructed for quantum Monte Carlo simulations. The main objective is to alleviate the computational cost associated with the calculations of two-body interactions, including the pairwise interactions in the…

Computational Physics · Physics 2020-09-01 Shi Jin , Xiantao Li

An efficient sampling method, the pmmLang+RBM, is proposed to compute the quantum thermal average in the interacting quantum particle system. Benefiting from the random batch method (RBM), the pmmLang+RBM reduces the complexity due to the…

Quantum Physics · Physics 2021-06-16 Xuda Ye , Zhennan Zhou

The goal of these expository notes is to give an introduction to random matrices for non-specialist of this topic focusing on the link between random matrices and systems of particles in interaction. We first recall some general results…

Analysis of PDEs · Mathematics 2026-02-09 Valentin Pesce

We consider in this paper random batch particle methods for efficiently solving the homogeneous Landau equation in plasma physics. The methods are stochastic variations of the particle methods proposed by Carrillo et al. [J. Comput. Phys.:…

Numerical Analysis · Mathematics 2022-04-13 José Antonio Carrillo , Shi Jin , Yijia Tang

Research on crowd simulation has important and wide range of applications. The main difficulty is how to lead all particles with a same and simple rule, especially when particles are numerous. In this paper, we firstly propose a two…

Numerical Analysis · Mathematics 2022-09-08 Tianlu Chen , Chang Yang , Léon Matar Tine , Zhichang Guo

We model, simulate and control the guiding problem for a herd of evaders under the action of repulsive drivers. The problem is formulated in an optimal control framework, where the drivers (controls) aim to guide the evaders (states) to a…

Optimization and Control · Mathematics 2020-05-01 Dongnam Ko , Enrique Zuazua
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