Thermodynamic bound on spectral perturbations, with applications to oscillations and relaxation dynamics

被引:8
作者
Kolchinsky, Artemy [1 ,2 ]
Ohga, Naruo [3 ]
Ito, Sosuke [2 ,3 ]
机构
[1] Univ Pompeu Fabra, Complex Syst Lab, ICREA, Barcelona 08003, Spain
[2] Univ Tokyo, Universal Biol Inst, Grad Sch Sci, 7-3-1 Hongo,Bunkyo ku, Tokyo 1130033, Japan
[3] Univ Tokyo, Grad Sch Sci, Dept Phys, 7-3-1 Hongo,Bunkyo Ku, Tokyo 1130033, Japan
来源
PHYSICAL REVIEW RESEARCH | 2024年 / 6卷 / 01期
基金
欧盟地平线“2020”;
关键词
SENSITIVITY;
D O I
10.1103/PhysRevResearch.6.013082
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In discrete-state Markovian systems, many important properties of correlation functions and relaxation dynamics depend on the spectrum of the rate matrix. Here we demonstrate the existence of a universal trade-off between thermodynamic and spectral properties. We show that the entropy production rate, the fundamental thermodynamic cost of a nonequilibrium steady state, bounds the difference between the eigenvalues of a nonequilibrium rate matrix and a reference equilibrium rate matrix. Using this result, we derive thermodynamic bounds on the spectral gap, which governs autocorrelation times and the speed of relaxation to a steady state. We also derive the thermodynamic bounds on the imaginary eigenvalues, which govern the speed of oscillations. We illustrate our approach using a simple model of biomolecular sensing.
引用
收藏
页数:9
相关论文
共 57 条
[1]  
Allen LJS., 2010, An introduction to stochastic processes with applications to biology
[2]  
Andrieux D, 2011, Arxiv, DOI arXiv:1103.2243
[3]   Inflow rate, a time-symmetric observable obeying fluctuation relations [J].
Baiesi, Marco ;
Falasco, Gianmaria .
PHYSICAL REVIEW E, 2015, 92 (04)
[4]  
Bao RC, 2023, Arxiv, DOI arXiv:2303.06428
[5]   Coherence of biochemical oscillations is bounded by driving force and network topology [J].
Barato, Andre C. ;
Seifert, Udo .
PHYSICAL REVIEW E, 2017, 95 (06)
[6]  
Bhatia R., 1997, MATRIX ANAL, DOI 10.1007/978-1-4612-0653-8
[7]   Non-reversible Metropolis-Hastings [J].
Bierkens, Joris .
STATISTICS AND COMPUTING, 2016, 26 (06) :1213-1228
[8]  
Bremaud P., 2001, Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues, V31
[9]   Accelerating reversible Markov chains [J].
Chen, Ting-Li ;
Hwang, Chii-Ruey .
STATISTICS & PROBABILITY LETTERS, 2013, 83 (09) :1956-1962
[10]  
Dechant A., 2023, Phys. Rev. Lett, V131