4.7 Article

Stochastic evaluation of four-component relativistic second-order many-body perturbation energies: A potentially quadratic-scaling correlation method

Journal

JOURNAL OF CHEMICAL PHYSICS
Volume 156, Issue 22, Pages -

Publisher

AIP Publishing
DOI: 10.1063/5.0091973

Keywords

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Funding

  1. CONACYT [620190]
  2. JSPS KAKENHI [21H01881, 21K18931]
  3. U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, as a part of the Computational Chemical Sciences Program
  4. U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory [DE-AC02-05CH11231]
  5. U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences [DE-SC0006028]
  6. U.S. Department of Energy Office of Science [DE-AC02-05CH11231]
  7. U.S. Department of Energy Office of Science using NERSC Award (2022) [m3196]
  8. Grants-in-Aid for Scientific Research [21K18931, 21H01881] Funding Source: KAKEN

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This paper evaluates a second-order many-body perturbation correction to the relativistic Dirac-Hartree-Fock energy using a stochastic approach. The integration is performed using the Monte Carlo method in both real space and imaginary time domain, resulting in improved computational efficiency and scalability.
A second-order many-body perturbation correction to the relativistic Dirac-Hartree-Fock energy is evaluated stochastically by integrating 13-dimensional products of four-component spinors and Coulomb potentials. The integration in the real space of electron coordinates is carried out by the Monte Carlo (MC) method with the Metropolis sampling, whereas the MC integration in the imaginary-time domain is performed by the inverse-cumulative distribution function method. The computational cost to reach a given relative statistical error for spatially compact but heavy molecules is observed to be no worse than cubic and possibly quadratic with the number of electrons or basis functions. This is a vast improvement over the quintic scaling of the conventional, deterministic second-order many-body perturbation method. The algorithm is also easily and efficiently parallelized with 92% strong scalability going from 64 to 4096 processors. Published under an exclusive license by AIP Publishing.

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