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Recently, Hessian geometry - an extension of information geometry - has emerged as a framework to naturally connect the geometries appearing in the theory of chemical reaction networks (CRN) to their inherent thermodynamical and kinetic…

统计力学 · 物理学 2023-08-10 Dimitri Loutchko , Yuki Sughiyama , Tetsuya J. Kobayashi

We establish a Hessian geometric structure in chemical thermodynamics which describes chemical reaction networks (CRNs) with equilibrium states. In our setup, the ideal gas assumption and mass action kinetics are not required. The existence…

统计力学 · 物理学 2022-08-30 Yuki Sughiyama , Dimitri Loutchko , Atsushi Kamimura , Tetsuya J. Kobayashi

We establish a generalized work theorem for stochastic chemical reaction networks (CRNs). By using a compensated Poisson jump process, we identify a martingale structure in a generalized entropy defined relative to an auxiliary backward…

统计力学 · 物理学 2026-01-21 Xiangting Li , Tom Chou

The study of the dynamics of chemical reactions, and in particular phenomena such as oscillating reactions, has led to the recognition that many dynamical properties of a chemical reaction can be predicted from graph theoretical properties…

动力系统 · 数学 2022-11-08 J. J. P. Veerman , Tessa Whalen-Wagner , Ewan Kummel

We derive the nonequilibrium conductance matrix for open stationary Chemical Reaction Networks (CRNs) described by a deterministic mass action kinetic equation. As an illustration, we determine the nonequilibrium conductance matrix of a CRN…

统计力学 · 物理学 2025-06-27 Paul Raux , Christophe Goupil , Gatien Verley

A chemical reaction network (CRN) is composed of reactions that can be seen as interactions among entities called species, which exist within the system. Endowed with kinetics, CRN has a corresponding set of ordinary differential equations…

动力系统 · 数学 2021-04-20 Bryan S. Hernandez , Ralph John L. De la Cruz

Chemical reaction networks (CRNs) are prototypical complex systems because reactions are nonlinear and connected in intricate ways, and they are also essential to understand living systems. Here, I discuss how recent developments in…

统计力学 · 物理学 2020-12-23 Massimiliano Esposito

The theory of chemical kinetics form the basis to describe the dynamics of chemical systems. Owing to physical and thermodynamic constraints, chemical reaction systems possess various structures, which can be utilized to characterize…

生物物理 · 物理学 2022-01-03 Tetsuya J. Kobayashi , Dimitri Loutchko , Atsushi Kamimura , Yuki Sughiyama

The modern thermodynamics of discrete systems is based on graph theory, which provides both algebraic methods to define observables and a geometric intuition of their meaning and role. However, because chemical reactions are usually…

统计力学 · 物理学 2023-04-04 Sara Dal Cengio , Vivien Lecomte , Matteo Polettini

We investigate the dynamics of chemical reaction networks (CRNs) with the goal of deriving an upper bound on their reaction rates. This task is challenging due to the nonlinear nature and discrete structure inherent in CRNs. To address…

化学物理 · 物理学 2023-09-20 Tsuyoshi Mizohata , Tetsuya J. Kobayashi , Louis-S. Bouchard , Hideyuki Miyahara

Living systems operate out of equilibrium, continuously consuming energy to sustain organised, functional states. Their emergent behaviour usually relies on a set of interconnected chemical reaction networks (CRNs) driven by external fluxes…

统计力学 · 物理学 2026-02-03 Shiling Liang , Paolo De Los Rios , Daniel Maria Busiello

We obtain bounds on the Kullback--Leibler divergence to equilibrium for mass-action chemical reaction networks (CRNs) with equilibrium. The associated decay rates are characterized in terms of the singular values of the stoichiometric…

分子网络 · 定量生物学 2026-02-24 Keisuke Sugie , Dimitri Loutchko , Tetsuya J. Kobayashi

Understanding the emergent behavior of chemical reaction networks (CRNs) is a fundamental aspect of biology and its origin from inanimate matter. A closed CRN monotonically tends to thermal equilibrium, but when it is opened to external…

分子网络 · 定量生物学 2024-05-16 Masanari Shimada , Pegah Behrad , Eric De Giuli

Chemical reaction networks (CRNs) provide a convenient language for modelling a broad variety of biological systems. These models are commonly studied with respect to the time series they generate in deterministic or stochastic simulations.…

分子网络 · 定量生物学 2019-07-11 Ozan Kahramanoğulları

Random graph models have been instrumental in characterizing complex networks, but chemical reaction networks (CRNs) are better represented as hypergraphs. Traditional models of random CRNs often reduce CRNs to bipartite graphs,…

统计力学 · 物理学 2025-07-15 Shesha Gopal Marehalli Srinivas , Massimiliano Esposito , Nahuel Freitas

In an earlier paper, we proved the validity of large deviations theory for the particle approximation of quite general chemical reaction networks (CRNs). In this paper, we extend its scope and present a more geometric insight into the…

动力系统 · 数学 2018-08-01 Andrea Agazzi , Amir Dembo , Jean-Pierre Eckmann

Motivation: A Chemical Reaction Network (CRN) is a set of chemical reactions, which can be very complex and difficult to analyze. Indeed, dynamical properties of CRNs can be described by a set of non-linear differential equations that…

计算工程、金融与科学 · 计算机科学 2021-07-02 Lucia Nasti , Roberta Gori , Paolo Milazzo , Federico Poloni

Chemical reaction networks (CRNs) are directed graphs with reactant or product complexes as vertices, and reactions as arcs. A CRN is weakly reversible if each of its connected components is strongly connected. Weakly reversible networks…

Stochastic chemical reaction networks (CRNs) are complex systems which combine the features of concurrent transformation of multiple variables in each elementary reaction event, and nonlinear relations between states and their rates of…

化学物理 · 物理学 2017-12-06 Eric Smith , Supriya Krishnamurthy

Information geometry is based on classical Legendre duality but allows to incorporate additional structure such as algebraic constraints and Bregman divergence functions. It is naturally suited, and has been successfully used, to describe…

分子网络 · 定量生物学 2025-03-26 Dimitri Loutchko , Yuki Sughiyama , Tetsuya J. Kobayashi
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