Development of composite control-variate stratified sampling approach for efficient stochastic calculation of molecular integrals
Michael G. Bayne, Arindam Chakraborty

TL;DR
This paper introduces the CCSS method, a Monte Carlo-based approach for directly calculating molecular integrals without AO transformation, improving efficiency for large systems and broad applications.
Contribution
The paper presents the novel CCSS method that combines stratified sampling, control variates, and direct integration for efficient MO integral calculation without AO transformation.
Findings
CCSS reduces computational cost for large molecular systems.
It achieves variance reduction through control variates.
Applied successfully to excitonic properties in quantum dots.
Abstract
In this work, the composite control-variate stratified sampling (CCSS) method is presented for calculation of MO integrals without transformation of AO integrals. The central idea of this approach is to obtain the 2-electron MO integrals by direct integration of 2-electron coordinates. This method does not require or use pre-computed AO integrals and the value of the MOs at any point in space is obtained directly from the linear combination of AOs. The integration over the electronic coordinates was performed using stratified sampling Monte Carlo method. This approach was implemented by dividing the integration region into a set of non-overlapping segments and performing Monte Carlo calculations on each segment. The Monte Carlo sampling points for each segment were optimized to minimize the total variance of the sample mean. Additional variance reduction of the overall calculations was…
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Taxonomy
TopicsAnalytical Chemistry and Chromatography
