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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
Information geometric bound on general chemical reaction networks
| Title: | Information geometric bound on general chemical reaction networks |
| Authors: | Mizohata, Tsuyoshi Browse this author | | Kobayashi, Tetsuya J. Browse this author | | Bouchard, Louis-S. Browse this author | | Miyahara, Hideyuki Browse this author →KAKEN DB |
| Keywords: | Chemical reactions | | Network flow optimization | | Stochastic thermodynamics |
| Issue Date: | 11-Apr-2024 |
| Publisher: | American Physical Society (APS) |
| Journal Title: | Physical Review E |
| Volume: | 109 |
| Issue: | 4 |
| Start Page: | 044308 |
| Publisher DOI: | 10.1103/PhysRevE.109.044308 |
| Abstract: | We investigate the convergence of chemical reaction networks (CRNs), aiming to establish an upper bound on their reaction rates. The nonlinear characteristics and discrete composition of CRNs pose significant challenges in this endeavor. To circumvent these complexities, we adopt an information geometric perspective, utilizing the natural gradient to formulate a nonlinear system. This system effectively determines an upper bound for the dynamics of CRNs. We corroborate our methodology through numerical simulations, which reveal that our constructed system converges more rapidly than CRNs within a particular class of reactions. This class is defined by the count of chemicals, the highest stoichiometric coefficients in the reactions, and the total number of reactions involved. Further, we juxtapose our approach with traditional methods, illustrating that the latter falls short in providing an upper bound for CRN reaction rates. Although our investigation centers on CRNs, the widespread presence of hypergraphs across various disciplines, ranging from natural sciences to engineering, indicates potential wider applications of our method, including in the realm of information science. |
| Rights: | Copyright (2024) by The American Physical Society. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/92617 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 宮原 英之
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