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Updated: Jun 18, 2025

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Rapidly convergent quantum Monte Carlo using a Chebyshev projector.

Zijun Zhao1, Maria-Andreea Filip1, Alex J W Thom1

  • 1Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK. zz376@cantab.ac.uk.

Faraday Discussions
|July 31, 2024
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Summary
This summary is machine-generated.

Quantum Monte Carlo methods are improved for complex chemical systems. New algorithms accelerate calculations, making multireference coupled-cluster Monte Carlo (MR-CCMC) more practical for studying strong correlation.

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Area of Science:

  • Quantum chemistry
  • Computational physics
  • Materials science

Background:

  • The multireference coupled-cluster Monte Carlo (MR-CCMC) algorithm offers a balanced treatment of static and dynamic correlation.
  • Previous MR-CCMC applications were limited by computational cost for systems with strong correlation.

Purpose of the Study:

  • To present algorithmic advancements for accelerating MR-CCMC convergence.
  • To enable a more automated approach to multireference quantum chemistry problems.

Main Methods:

  • Developed a logarithmically scaling metric-tree-based excitation acceptance algorithm.
  • Implemented a symmetry-screening procedure for the reference space.
  • Introduced a stochastic wall-Chebyshev projector for accelerating projector-based QMC algorithms.

Main Results:

  • The new search algorithm accelerated MR-CCMC iterations by approximately 8-fold.
  • Symmetry screening reduced reference space determinants with minimal accuracy loss.
  • The wall-Chebyshev projector significantly reduced Hamiltonian applications for statistical convergence.

Conclusions:

  • Recent algorithmic improvements enhance the efficiency and applicability of MR-CCMC.
  • These advancements facilitate the study of challenging chemical systems with strong electron correlation.
  • The developed projector acceleration technique is broadly applicable to projector-based QMC methods.