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PyQMC: An all-Python real-space quantum Monte Carlo module in PySCF.

William A Wheeler1, Shivesh Pathak2, Kevin G Kleiner3

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We introduce PyQMC, a new Python package for accurate quantum Monte Carlo (QMC) electron calculations. This open-source tool simplifies complex quantum chemistry workflows and algorithmic development.

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Area of Science:

  • Computational chemistry
  • Quantum mechanics
  • Materials science

Background:

  • Accurate correlated electron calculations are crucial for understanding chemical and physical properties.
  • Quantum Monte Carlo (QMC) methods offer a powerful approach for these calculations.
  • Existing tools may lack accessibility or integration for complex workflows.

Purpose of the Study:

  • To present PyQMC, a novel open-source Python package for real-space quantum Monte Carlo calculations.
  • To provide an accessible platform for developing and implementing advanced QMC algorithms.
  • To facilitate comparisons between QMC and other many-body methods.

Main Methods:

  • Development of the PyQMC package using Python.
  • Implementation of modern quantum Monte Carlo algorithms in real space.
  • Integration with the PySCF computational chemistry environment.

Main Results:

  • PyQMC enables high-accuracy correlated electron calculations.
  • The package offers an accessible format for algorithmic development.
  • Seamless integration with PySCF allows for easy comparison with other wave function techniques.

Conclusions:

  • PyQMC provides a valuable tool for researchers in quantum chemistry and condensed matter physics.
  • The package lowers the barrier to entry for utilizing advanced QMC methods.
  • Its integration capabilities foster further development and application of correlated electron calculations.