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mVMC Tutorial

mvmc-dev / mVMC Tutorial

Strong correlation/effective modelsCC BY 4.0
Updated: 2024-03-08

Overview

mVMC is a low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection. This repository provides the sample data including input and output data for mVMC.

URL
https://isspns-gitlab.issp.u-tokyo.ac.jp/mvmc-dev/mvmc-tutorial
DOI
10.1016/j.cpc.2018.08.014
Citations
97 (OpenAlex, as of 2026-10-05)
Authors
Takahiro Misawa, Satoshi Morita, Kota Ido, Mitsuaki Kawamura, Yuichi Motoyama, Kazuyoshi Yoshimi, Masatoshi Imada, Takeo Kato
License
CC BY 4.0
Keywords
variational Monte Carlointeracting fermionsquantum lattice modelsHubbard modelHeisenberg modelKondo lattice modelstrongly correlated electronsground state wave function (keywords of the paper, from OpenAlex)
Category
Strong correlation/effective models
References
Computer Physics Communications Volume 235, February 2019, Pages 447-462
Related software
mVMC (Links to: PASUMS software catalog)
Contact
mvmc-dev__at__issp.u-tokyo.ac.jp (Please replace __at__ with @.)

Paper and citation

If you use this data, please cite the following paper.

Takahiro Misawa et al., "mVMC—Open-source software for many-variable variational Monte Carlo method", Computer Physics Communications 235, 447–462 (2018). https://doi.org/10.1016/j.cpc.2018.08.014

Read the paper (open access) ↗
Show BibTeX
@article{Misawa_2019, title={mVMC—Open-source software for many-variable variational Monte Carlo method}, volume={235}, ISSN={0010-4655}, url={http://dx.doi.org/10.1016/j.cpc.2018.08.014}, DOI={10.1016/j.cpc.2018.08.014}, journal={Computer Physics Communications}, publisher={Elsevier BV}, author={Misawa, Takahiro and Morita, Satoshi and Yoshimi, Kazuyoshi and Kawamura, Mitsuaki and Motoyama, Yuichi and Ido, Kota and Ohgoe, Takahiro and Imada, Masatoshi and Kato, Takeo}, year={2019}, month=Feb, pages={447–462} }

Bibliographic details and the open-access link are from OpenAlex; the BibTeX is from doi.org (as registered by the publisher).

Links

README

mVMC Tutorial

About

mVMC is a low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection. This repository provides the sample data including input and output data for mVMC.

License
  • Documents: CC BY 4.0
  • Source codes: GNU General Public License v3.0 or later

The mVMC package is developed based on the mVMC-mini program. The license of mVMC-mini is "The BSD 3-Clause License".

We would appreciate if you cite the following article in your research with mVMC, our data or codes: 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, Computer Physics Communications, 235, 447-462 (2019).

Folder structures
  • LICENSE
  • README.md
  • HandsOn
    • 2017_0830
      • Refs
      • Samples
    • 2022_1128
      • Refs
      • Samples
Contact
  • mvmc-dev__at__issp.u-tokyo.ac.jp

please replace __at__ by @.

Source: https://isspns-gitlab.issp.u-tokyo.ac.jp/mvmc-dev/mvmc-tutorial README

Activity

UpdatedLast updated: 2024-03-08 ()