Stochastic tensor contraction for quantum chemistry

Fuente: arXiv
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Autori principali: Sun, Jiace, Chan, Garnet Kin-Lic
Natura: Preprint
Pubblicazione: 2026
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author Sun, Jiace
Chan, Garnet Kin-Lic
author_facet Sun, Jiace
Chan, Garnet Kin-Lic
contents Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.
format Preprint
id arxiv_https___arxiv_org_abs_2602_17158
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Stochastic tensor contraction for quantum chemistry
Sun, Jiace
Chan, Garnet Kin-Lic
Chemical Physics
Strongly Correlated Electrons
Computational Physics
Quantum Physics
Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.
title Stochastic tensor contraction for quantum chemistry
topic Chemical Physics
Strongly Correlated Electrons
Computational Physics
Quantum Physics
url https://arxiv.org/abs/2602.17158