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QMCTorch

Use and design neural network ansatz wave function for real-space quantum Monte Carlo simulations of molecular systems.

2
contributors

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What QMCTorch can do for you

  • Easily use and implement new neural network ansatz
  • Use ADF or pySCF as SCF backend
  • Use Horovod to deploy on GPU clusters

In QMCTorch the trial wave function is calculated by a small, physically motivated network. Starting from the electronic positions, R, the first layer computes the values of all atomic orbitals for all electrons. From there a linear map computes the values of all relevant molecular orbitals. A Slater Pooling mask is then applied to compute all Slater determinants that are finally combined by a fully connected layer. The Jastrow factors are computed in parallel and combined with the CI expansion to obtain the value of the wave function

Logo of QMCTorch
Keywords
Programming languages
  • Python 98%
  • TeX 2%
License
</>Source code

Participating organisations

Natural Sciences & Engineering
Natural Sciences & Engineering
Netherlands eScience Center

Contributors

Felipe Zapata
Felipe Zapata
Nicolas Renaud
Nicolas Renaud

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