mVMC—Open-source software for many-variable variational Monte Carlo method

Takahiro Misawa, Satoshi Morita, Kazuyoshi Yoshimi, Mitsuaki Kawamura, Yuichi Motoyama, Kota Ido, Takahiro Ohgoe, Masatoshi Imada, Takeo Kato

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

mVMC (many-variable Variational Monte Carlo) is an open-source software package based on the variational Monte Carlo method applicable for a wide range of Hamiltonians for interacting fermion systems. In mVMC, we introduce more than ten thousands variational parameters and simultaneously optimize them by using the stochastic reconfiguration (SR) method. In this paper, we explain basics and user interfaces of mVMC. By using mVMC, users can perform the calculation by preparing only one input file of about ten lines for widely studied quantum lattice models, and can also perform it for general Hamiltonians by preparing several additional input files. We show the benchmark results of mVMC for the Hubbard model, the Heisenberg model, and the Kondo-lattice model. These benchmark results demonstrate that mVMC provides ground-state and low-energy-excited-state wave functions for interacting fermion systems with high accuracy. Program summary: Program title: mVMC Program Files doi: http://dx.doi.org/10.17632/xhgyp6ncvt.1 Licensing provisions: GNU General Public License version 3 Programming language: C External routines/libraries: MPI, BLAS, LAPACK, Pfapack, ScaLAPACK (optional) Nature of problem: Physical properties (such as the charge/spin structure factors) of strongly correlated electrons at zero temperature. Solution method: Application software based on the variational Monte Carlo method for quantum lattice model such as the Hubbard model, the Heisenberg model and the Kondo model. Unusual features: It is possible to perform the highly-accurate calculations for ground states in a wide range of theoretical Hamiltonians in quantum many-body systems. In addition to the conventional orders such as magnetic and/or charge orders, user can treat the anisotropic superconductivities within the same framework. This flexibility is the main advantage of mVMC.

Original languageEnglish
Pages (from-to)447-462
Number of pages16
JournalComputer Physics Communications
Volume235
DOIs
Publication statusPublished - 2019 Feb 1
Externally publishedYes

Fingerprint

Monte Carlo method
Monte Carlo methods
computer programs
Hamiltonians
Hubbard model
Fermions
files
Ground state
C (programming language)
Wave functions
Superconductivity
fermions
Application programs
Excited states
Software packages
Computer programming languages
User interfaces
licensing
ground state
Physical properties

Keywords

  • Lattice fermion models
  • Numerical linear algebra
  • Variational Monte Carlo method

ASJC Scopus subject areas

  • Hardware and Architecture
  • Physics and Astronomy(all)

Cite this

Misawa, T., Morita, S., Yoshimi, K., Kawamura, M., Motoyama, Y., Ido, K., ... Kato, T. (2019). mVMC—Open-source software for many-variable variational Monte Carlo method. Computer Physics Communications, 235, 447-462. https://doi.org/10.1016/j.cpc.2018.08.014

mVMC—Open-source software for many-variable variational Monte Carlo method. / Misawa, Takahiro; Morita, Satoshi; Yoshimi, Kazuyoshi; Kawamura, Mitsuaki; Motoyama, Yuichi; Ido, Kota; Ohgoe, Takahiro; Imada, Masatoshi; Kato, Takeo.

In: Computer Physics Communications, Vol. 235, 01.02.2019, p. 447-462.

Research output: Contribution to journalArticle

Misawa, T, Morita, S, Yoshimi, K, Kawamura, M, Motoyama, Y, Ido, K, Ohgoe, T, Imada, M & Kato, T 2019, 'mVMC—Open-source software for many-variable variational Monte Carlo method', Computer Physics Communications, vol. 235, pp. 447-462. https://doi.org/10.1016/j.cpc.2018.08.014
Misawa, Takahiro ; Morita, Satoshi ; Yoshimi, Kazuyoshi ; Kawamura, Mitsuaki ; Motoyama, Yuichi ; Ido, Kota ; Ohgoe, Takahiro ; Imada, Masatoshi ; Kato, Takeo. / mVMC—Open-source software for many-variable variational Monte Carlo method. In: Computer Physics Communications. 2019 ; Vol. 235. pp. 447-462.
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