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Carleman linearization approach for chemical kinetics integration toward quantum computation

The Harrow, Hassidim, Lloyd (HHL) algorithm, known as the pioneering algorithm for solving linear equations in quantum computers, is expected to accelerate solving large-scale linear ordinary differential equations (ODEs). To efficiently combine classical and quantum computers for high-cost chemical...

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Autores principales: Akiba, Takaki, Morii, Youhi, Maruta, Kaoru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998465/
https://www.ncbi.nlm.nih.gov/pubmed/36894647
http://dx.doi.org/10.1038/s41598-023-31009-9
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author Akiba, Takaki
Morii, Youhi
Maruta, Kaoru
author_facet Akiba, Takaki
Morii, Youhi
Maruta, Kaoru
author_sort Akiba, Takaki
collection PubMed
description The Harrow, Hassidim, Lloyd (HHL) algorithm, known as the pioneering algorithm for solving linear equations in quantum computers, is expected to accelerate solving large-scale linear ordinary differential equations (ODEs). To efficiently combine classical and quantum computers for high-cost chemical problems, non-linear ODEs (e.g., chemical reactions) must be linearized to the highest possible accuracy. However, the linearization approach has not been fully established yet. In this study, Carleman linearization was examined to transform nonlinear first-order ODEs of chemical reactions into linear ODEs. Although this linearization theoretically requires the generation of an infinite matrix, the original nonlinear equations can be reconstructed. For the practical use, the linearized system should be truncated with finite size and the extent of the truncation determines analysis precision. Matrix should be sufficiently large so that the precision is satisfied because quantum computers can treat such huge matrix. Our method was applied to a one-variable nonlinear [Formula: see text] system to investigate the effect of truncation orders and time step sizes on the computational error. Subsequently, two zero-dimensional homogeneous ignition problems for H(2)–air and CH(4)–air gas mixtures were solved. The results revealed that the proposed method could accurately reproduce reference data. Furthermore, an increase in the truncation order improved accuracy with large time-step sizes. Thus, our approach can provide accurate numerical simulations rapidly for complex combustion systems.
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spelling pubmed-99984652023-03-11 Carleman linearization approach for chemical kinetics integration toward quantum computation Akiba, Takaki Morii, Youhi Maruta, Kaoru Sci Rep Article The Harrow, Hassidim, Lloyd (HHL) algorithm, known as the pioneering algorithm for solving linear equations in quantum computers, is expected to accelerate solving large-scale linear ordinary differential equations (ODEs). To efficiently combine classical and quantum computers for high-cost chemical problems, non-linear ODEs (e.g., chemical reactions) must be linearized to the highest possible accuracy. However, the linearization approach has not been fully established yet. In this study, Carleman linearization was examined to transform nonlinear first-order ODEs of chemical reactions into linear ODEs. Although this linearization theoretically requires the generation of an infinite matrix, the original nonlinear equations can be reconstructed. For the practical use, the linearized system should be truncated with finite size and the extent of the truncation determines analysis precision. Matrix should be sufficiently large so that the precision is satisfied because quantum computers can treat such huge matrix. Our method was applied to a one-variable nonlinear [Formula: see text] system to investigate the effect of truncation orders and time step sizes on the computational error. Subsequently, two zero-dimensional homogeneous ignition problems for H(2)–air and CH(4)–air gas mixtures were solved. The results revealed that the proposed method could accurately reproduce reference data. Furthermore, an increase in the truncation order improved accuracy with large time-step sizes. Thus, our approach can provide accurate numerical simulations rapidly for complex combustion systems. Nature Publishing Group UK 2023-03-09 /pmc/articles/PMC9998465/ /pubmed/36894647 http://dx.doi.org/10.1038/s41598-023-31009-9 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Akiba, Takaki
Morii, Youhi
Maruta, Kaoru
Carleman linearization approach for chemical kinetics integration toward quantum computation
title Carleman linearization approach for chemical kinetics integration toward quantum computation
title_full Carleman linearization approach for chemical kinetics integration toward quantum computation
title_fullStr Carleman linearization approach for chemical kinetics integration toward quantum computation
title_full_unstemmed Carleman linearization approach for chemical kinetics integration toward quantum computation
title_short Carleman linearization approach for chemical kinetics integration toward quantum computation
title_sort carleman linearization approach for chemical kinetics integration toward quantum computation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998465/
https://www.ncbi.nlm.nih.gov/pubmed/36894647
http://dx.doi.org/10.1038/s41598-023-31009-9
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