Self-learning quantum Monte Carlo method in interacting fermion systems
Author(s)
Xu, Xiao Yan; Qi, Yang; Liu, Junwei; Fu, Liang; Meng, Zi Yang
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The self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally reduce the computational complexity and moreover can greatly suppress the autocorrelation time near a critical point. This enables us to simulate an interacting fermion system on a 100×100 lattice even at the critical point and obtain critical exponents with high precision.
Date issued
2017-07Department
Massachusetts Institute of Technology. Materials Processing Center; Massachusetts Institute of Technology. Department of PhysicsJournal
Physical Review B
Publisher
American Physical Society
Citation
Xu, Xiao Yan et al. “Self-Learning Quantum Monte Carlo Method in Interacting Fermion Systems.” Physical Review B 96.4 (2017): n. pag. © 2017 American Physical Society
Version: Final published version
ISSN
2469-9950
2469-9969