Suppr超能文献

非平衡反应网络的状态空间重整化群理论:任意维度超立方晶格的精确解

State-space renormalization group theory of nonequilibrium reaction networks: Exact solutions for hypercubic lattices in arbitrary dimensions.

作者信息

Yu Qiwei, Tu Yuhai

机构信息

Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.

IBM T. J. Watson Research Center, Yorktown Heights, New York 10598, USA.

出版信息

Phys Rev E. 2022 Apr;105(4-1):044140. doi: 10.1103/PhysRevE.105.044140.

Abstract

Nonequilibrium reaction networks (NRNs) underlie most biological functions. Despite their diverse dynamic properties, NRNs share the signature characteristics of persistent probability fluxes and continuous energy dissipation even in the steady state. Dynamics of NRNs can be described at different coarse-grained levels. Our previous work showed that the apparent energy dissipation rate at a coarse-grained level follows an inverse power-law dependence on the scale of coarse-graining. The scaling exponent is determined by the network structure and correlation of stationary probability fluxes. However, it remains unclear whether and how the (renormalized) flux correlation varies with coarse-graining. Following Kadanoff's real space renormalization group (RG) approach for critical phenomena, we address this question by developing a state-space renormalization group theory for NRNs, which leads to an iterative RG equation for the flux correlation function. In square and hypercubic lattices, we solve the RG equation exactly and find two types of fixed point solutions. There is a family of nontrivial fixed points where the correlation exhibits power-law decay, characterized by a power exponent that can take any value within a continuous range. There is also a trivial fixed point where the correlation vanishes beyond the nearest neighbors. The power-law fixed point is stable if and only if the power exponent is less than the lattice dimension n. Consequently, the correlation function converges to the power-law fixed point only when the correlation in the fine-grained network decays slower than r^{-n} and to the trivial fixed point otherwise. If the flux correlation in the fine-grained network contains multiple stable solutions with different exponents, the RG iteration dynamics select the fixed point solution with the smallest exponent. The analytical results are supported by numerical simulations. We also discuss a possible connection between the RG flows of flux correlation with those of the Kosterlitz-Thouless transition.

摘要

非平衡反应网络(NRNs)是大多数生物学功能的基础。尽管它们具有多样的动态特性,但即使在稳态下,NRNs也具有持续概率流和连续能量耗散的标志性特征。NRNs的动力学可以在不同的粗粒化水平上进行描述。我们之前的工作表明,粗粒化水平下的表观能量耗散率遵循与粗粒化尺度的幂律反比关系。标度指数由网络结构和平稳概率流的相关性决定。然而,目前尚不清楚(重整化后的)流相关性是否以及如何随粗粒化而变化。遵循Kadanoff针对临界现象的实空间重整化群(RG)方法,我们通过为NRNs发展一种状态空间重整化群理论来解决这个问题,这导致了一个关于流相关函数的迭代RG方程。在正方形和超立方晶格中,我们精确求解了RG方程,发现了两种类型的不动点解。存在一族非平凡不动点,其相关性呈现幂律衰减,其特征是幂指数可以在一个连续范围内取任意值。还存在一个平凡不动点,在该点处相关性在最近邻之外消失。当且仅当幂指数小于晶格维度n时,幂律不动点是稳定的。因此,只有当细粒化网络中的相关性衰减比r^{-n}慢时,相关函数才会收敛到幂律不动点,否则收敛到平凡不动点。如果细粒化网络中的流相关性包含多个具有不同指数的稳定解,RG迭代动力学将选择指数最小的不动点解。数值模拟支持了这些分析结果。我们还讨论了流相关性的RG流与Kosterlitz-Thouless转变的RG流之间可能的联系。

相似文献

2
Inverse Power Law Scaling of Energy Dissipation Rate in Nonequilibrium Reaction Networks.
Phys Rev Lett. 2021 Feb 26;126(8):080601. doi: 10.1103/PhysRevLett.126.080601.
4
Inverted Berezinskii-Kosterlitz-Thouless singularity and high-temperature algebraic order in an Ising model on a scale-free hierarchical-lattice small-world network.
Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jun;73(6 Pt 2):066126. doi: 10.1103/PhysRevE.73.066126. Epub 2006 Jun 27.
5
Analytically Solvable Renormalization Group for the Many-Body Localization Transition.
Phys Rev Lett. 2019 Feb 1;122(4):040601. doi: 10.1103/PhysRevLett.122.040601.
6
Universal critical behavior of noisy coupled oscillators: a renormalization group study.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jul;72(1 Pt 2):016130. doi: 10.1103/PhysRevE.72.016130. Epub 2005 Jul 29.
7
Pair contact process with diffusion: failure of master equation field theory.
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Nov;70(5 Pt 2):056114. doi: 10.1103/PhysRevE.70.056114. Epub 2004 Nov 17.
8
Fixed-point properties of the Ising ferromagnet on the Hanoi networks.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Feb;83(2 Pt 1):021103. doi: 10.1103/PhysRevE.83.021103. Epub 2011 Feb 9.
9
Construction of coarse-grained order parameters in nonequilibrium systems.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Jun;79(6 Pt 1):061107. doi: 10.1103/PhysRevE.79.061107. Epub 2009 Jun 11.
10
Renormalization group crossover in the critical dynamics of field theories with mode coupling terms.
Phys Rev E. 2019 Dec;100(6-1):062130. doi: 10.1103/PhysRevE.100.062130.

引用本文的文献

2
A nonequilibrium allosteric model for receptor-kinase complexes: The role of energy dissipation in chemotaxis signaling.
Proc Natl Acad Sci U S A. 2023 Oct 17;120(42):e2303115120. doi: 10.1073/pnas.2303115120. Epub 2023 Oct 12.
3
Energy Cost for Flocking of Active Spins: The Cusped Dissipation Maximum at the Flocking Transition.
Phys Rev Lett. 2022 Dec 30;129(27):278001. doi: 10.1103/PhysRevLett.129.278001.

本文引用的文献

1
Scaling of entropy production under coarse graining in active disordered media.
Phys Rev E. 2022 Apr;105(4):L042601. doi: 10.1103/PhysRevE.105.L042601.
2
Inverse Power Law Scaling of Energy Dissipation Rate in Nonequilibrium Reaction Networks.
Phys Rev Lett. 2021 Feb 26;126(8):080601. doi: 10.1103/PhysRevLett.126.080601.
3
Broken detailed balance and non-equilibrium dynamics in living systems: a review.
Rep Prog Phys. 2018 Jun;81(6):066601. doi: 10.1088/1361-6633/aab3ed. Epub 2018 Mar 5.
5
Information Integration and Energy Expenditure in Gene Regulation.
Cell. 2016 Jun 30;166(1):234-44. doi: 10.1016/j.cell.2016.06.012.
6
Broken detailed balance at mesoscopic scales in active biological systems.
Science. 2016 Apr 29;352(6285):604-7. doi: 10.1126/science.aac8167.
7
The energy-speed-accuracy tradeoff in sensory adaptation.
Nat Phys. 2012 May 1;8(5):422-428. doi: 10.1038/nphys2276. Epub 2012 Mar 25.
8
Nonperturbative renormalization group for the Kardar-Parisi-Zhang equation.
Phys Rev Lett. 2010 Apr 16;104(15):150601. doi: 10.1103/PhysRevLett.104.150601. Epub 2010 Apr 14.
9
The nonequilibrium mechanism for ultrasensitivity in a biological switch: sensing by Maxwell's demons.
Proc Natl Acad Sci U S A. 2008 Aug 19;105(33):11737-41. doi: 10.1073/pnas.0804641105. Epub 2008 Aug 7.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验