Variance-reduced random batch Langevin dynamics
The random batch method is advantageous in accelerating force calculations in particle simulations, but it poses a challenge of removing the artificial heating effect in application to the Langevin dynamics. We develop an approach to solve this issue by estimating the force variance, resulting in a variance-reduced random batch Langevin dynamics. Theoretical analysis shows the high-order local truncation error of the time step in the numerical discretization scheme, consistent with the fluctuation-dissipation theorem. The numerical results indicate that the method can achieve a significant variance reduction since a smaller batch size provides accurate approximation, demonstrating the attractive feature of the variance-reduced random batch method for Langevin dynamics.
Authors
- Yue Zhao (ORCID: https://orcid.org/0000-0002-3316-4330)
- Zhenli Xu (ORCID: https://orcid.org/0000-0001-7645-4998)
- Qi Zhou (ORCID: https://orcid.org/0000-0003-4894-2198)
Institutions
- Shanghai Jiao Tong University (CN)
- Michigan State University (US)
Publication Details
- Journal
- The Journal of Chemical Physics
- Published
- 2024-12-28
- DOI
- https://doi.org/10.1063/5.0246661
- Citations
- 1
- Primary Topic
- Markov Chains and Monte Carlo Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- National Natural Science Foundation of China
- Science and Technology Commission of Shanghai Municipality