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  • mVMC

mVMC

  • Openness:3 ★★★
  • Document quality:2 ★★☆

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.

Machine learning and ab initio analyses of cuprate high-temperature superconductors

Masatoshi IMADA

ISSP Activity Report 2020, p. 184-186

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  • The Institute for Solid State Physics
  • The University of Tokyo
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