Random Batch Methods for classical and quantum interacting particle systems and statistical samplings

2021/04/09 by Shi Jin, Lei Li, Jin, Shi +1 · 1 citation
Decision Sciences · #Forecasting Techniques and Applications

paper · pdf · doi:10.48550/arxiv.2104.04337

Abstract

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(N²), which is prohibitively expensive. The RBM methods use small but random batches so the computational cost is reduced, per time step, to O(N). In this article we discuss these methods for both classical and quantum systems, the corresponding theory, and applications from molecular dynamics, statistical samplings, to agent-based models for collective behavior, and quantum Monte-Carlo methods.

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