Self-learning quantum Monte Carlo method in interacting fermion systems
Name
PhysRevB.96.041119.pdf
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332.42 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Xu, Xiao Yan
Qi, Yang
Liu, Junwei
Fu, Liang
Meng, Zi Yang
Date Issued
July 2017
Journal
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
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Materials Processing Center
Massachusetts Institute of Technology. Department of Physics
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DOI of Published Version
https://doi.org/10.1103/PhysRevB.96.041119
