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Semistochastic Heat-Bath Configuration Interaction Method: Selected Configuration Interaction with Semistochastic
Sandeep Sharma1, Adam A Holmes1,2, Guillaume Jeanmairet3,4
1Department of Chemistry and Biochemistry, University of Colorado Boulder , Boulder, Colorado 80302, United States.
Journal of Chemical Theory and Computation
|March 7, 2017
Summary
We introduce a semistochastic heat-bath configuration interaction (SHCI) algorithm to overcome memory limitations in quantum chemistry calculations. This method enables accurate correlation energy computations for large systems without the sign problem, offering a faster alternative to deterministic approaches.
Area of Science:
- Quantum Chemistry
- Computational Physics
- Materials Science
Background:
- The heat-bath configuration interaction (HCI) method is a powerful tool for calculating electronic correlation energy.
- The original HCI method suffers from significant memory bottlenecks, limiting its application to smaller systems.
- Quantum Monte Carlo methods often encounter the sign problem, complicating accurate calculations.
Purpose of the Study:
- To develop a semistochastic algorithm for multireference Epstein-Nesbet perturbation theory to eliminate memory limitations.
- To enhance the efficiency and applicability of the HCI method for large-scale electronic structure calculations.
- To provide a computationally feasible approach for obtaining highly accurate correlation energies.
Main Methods:
- Introduction of a semistochastic algorithm for heat-bath configuration interaction (SHCI).
- Utilizing the Alias method for direct sampling of determinants, avoiding correlations.
- Implementing multireference Epstein-Nesbet perturbation theory within the SHCI framework.
- Trading memory for computational time as needed.
Main Results:
- The semistochastic HCI (SHCI) algorithm effectively removes the memory bottleneck of the original HCI method.
- SHCI avoids the sign problem encountered in some quantum Monte Carlo methods.
- The method achieves high accuracy (better than 1 mHa) for large active spaces in systems like F2, Mn-Salen, and Cr2.
- SHCI demonstrates improved speed over deterministic methods for acceptable stochastic error levels.
Conclusions:
- The SHCI algorithm significantly extends the applicability of HCI to very large active spaces.
- This method offers a practical and accurate approach for calculating correlation energies in complex molecular systems.
- SHCI provides a valuable advancement in computational quantum chemistry, enabling the study of larger and more intricate systems.
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