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Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree–Fock and density functional theory but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate an...

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Autores principales: Babbush, Ryan, Huggins, William J., Berry, Dominic W., Ung, Shu Fay, Zhao, Andrew, Reichman, David R., Neven, Hartmut, Baczewski, Andrew D., Lee, Joonho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333266/
https://www.ncbi.nlm.nih.gov/pubmed/37429883
http://dx.doi.org/10.1038/s41467-023-39024-0
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author Babbush, Ryan
Huggins, William J.
Berry, Dominic W.
Ung, Shu Fay
Zhao, Andrew
Reichman, David R.
Neven, Hartmut
Baczewski, Andrew D.
Lee, Joonho
author_facet Babbush, Ryan
Huggins, William J.
Berry, Dominic W.
Ung, Shu Fay
Zhao, Andrew
Reichman, David R.
Neven, Hartmut
Baczewski, Andrew D.
Lee, Joonho
author_sort Babbush, Ryan
collection PubMed
description Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree–Fock and density functional theory but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate and costly classical methods for treating electron correlation. However, here we tighten bounds showing that certain first-quantized quantum algorithms enable exact time evolution of electronic systems with exponentially less space and polynomially fewer operations in basis set size than conventional real-time time-dependent Hartree–Fock and density functional theory. Although the need to sample observables in the quantum algorithm reduces the speedup, we show that one can estimate all elements of the k-particle reduced density matrix with a number of samples scaling only polylogarithmically in basis set size. We also introduce a more efficient quantum algorithm for first-quantized mean-field state preparation that is likely cheaper than the cost of time evolution. We conclude that quantum speedup is most pronounced for finite-temperature simulations and suggest several practically important electron dynamics problems with potential quantum advantage.
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spelling pubmed-103332662023-07-12 Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods Babbush, Ryan Huggins, William J. Berry, Dominic W. Ung, Shu Fay Zhao, Andrew Reichman, David R. Neven, Hartmut Baczewski, Andrew D. Lee, Joonho Nat Commun Article Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree–Fock and density functional theory but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate and costly classical methods for treating electron correlation. However, here we tighten bounds showing that certain first-quantized quantum algorithms enable exact time evolution of electronic systems with exponentially less space and polynomially fewer operations in basis set size than conventional real-time time-dependent Hartree–Fock and density functional theory. Although the need to sample observables in the quantum algorithm reduces the speedup, we show that one can estimate all elements of the k-particle reduced density matrix with a number of samples scaling only polylogarithmically in basis set size. We also introduce a more efficient quantum algorithm for first-quantized mean-field state preparation that is likely cheaper than the cost of time evolution. We conclude that quantum speedup is most pronounced for finite-temperature simulations and suggest several practically important electron dynamics problems with potential quantum advantage. Nature Publishing Group UK 2023-07-10 /pmc/articles/PMC10333266/ /pubmed/37429883 http://dx.doi.org/10.1038/s41467-023-39024-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Babbush, Ryan
Huggins, William J.
Berry, Dominic W.
Ung, Shu Fay
Zhao, Andrew
Reichman, David R.
Neven, Hartmut
Baczewski, Andrew D.
Lee, Joonho
Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title_full Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title_fullStr Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title_full_unstemmed Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title_short Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
title_sort quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333266/
https://www.ncbi.nlm.nih.gov/pubmed/37429883
http://dx.doi.org/10.1038/s41467-023-39024-0
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