Random batch algorithms for quantum monte carlo simulations

Shi Jin, Xiantao Li

Research output: Contribution to journalArticlepeer-review

Abstract

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 potential energy, and the two-body terms in the Jastrow factor. In the framework of variational Monte Carlo methods, the random batch algorithm is constructed based on the over-damped Langevin dynamics, so that updating the position of each particle in an N-particle system only requires O(1) operations, thus for each time step the computational cost for N particles is reduced from O(N2) to O(N). For diffusion Monte Carlo methods, the random batch algorithm uses an energy decomposition to avoid the computation of the total energy in the branching step. The effectiveness of the random batch method is demonstrated using a system of liquid 4He atoms interacting with a graphite surface.

Original languageEnglish (US)
Pages (from-to)1907-1936
Number of pages30
JournalCommunications in Computational Physics
Volume28
Issue number5
DOIs
StatePublished - Nov 2020

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy (miscellaneous)

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