Broken detailed balance and entropy production in directed networks.

IF 2.2 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS Physical Review E Pub Date : 2024-09-01 DOI:10.1103/PhysRevE.110.034313
Ramón Nartallo-Kaluarachchi, Malbor Asllani, Gustavo Deco, Morten L Kringelbach, Alain Goriely, Renaud Lambiotte
{"title":"Broken detailed balance and entropy production in directed networks.","authors":"Ramón Nartallo-Kaluarachchi, Malbor Asllani, Gustavo Deco, Morten L Kringelbach, Alain Goriely, Renaud Lambiotte","doi":"10.1103/PhysRevE.110.034313","DOIUrl":null,"url":null,"abstract":"<p><p>The structure of a complex network plays a crucial role in determining its dynamical properties. In this paper , we show that the the degree to which a network is directed and hierarchically organized is closely associated with the degree to which its dynamics break detailed balance and produce entropy. We consider a range of dynamical processes and show how different directed network features affect their entropy production rate. We begin with an analytical treatment of a two-node network followed by numerical simulations of synthetic networks using the preferential attachment and Erdös-Renyi algorithms. Next, we analyze a collection of 97 empirical networks to determine the effect of complex real-world topologies. Finally, we present a simple method for inferring broken detailed balance and directed network structure from multivariate time series and apply our method to identify non-equilibrium dynamics and hierarchical organisation in both human neuroimaging and financial time series. Overall, our results shed light on the consequences of directed network structure on non-equilibrium dynamics and highlight the importance and ubiquity of hierarchical organisation and non-equilibrium dynamics in real-world systems.</p>","PeriodicalId":48698,"journal":{"name":"Physical Review E","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Review E","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1103/PhysRevE.110.034313","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, FLUIDS & PLASMAS","Score":null,"Total":0}
引用次数: 0

Abstract

The structure of a complex network plays a crucial role in determining its dynamical properties. In this paper , we show that the the degree to which a network is directed and hierarchically organized is closely associated with the degree to which its dynamics break detailed balance and produce entropy. We consider a range of dynamical processes and show how different directed network features affect their entropy production rate. We begin with an analytical treatment of a two-node network followed by numerical simulations of synthetic networks using the preferential attachment and Erdös-Renyi algorithms. Next, we analyze a collection of 97 empirical networks to determine the effect of complex real-world topologies. Finally, we present a simple method for inferring broken detailed balance and directed network structure from multivariate time series and apply our method to identify non-equilibrium dynamics and hierarchical organisation in both human neuroimaging and financial time series. Overall, our results shed light on the consequences of directed network structure on non-equilibrium dynamics and highlight the importance and ubiquity of hierarchical organisation and non-equilibrium dynamics in real-world systems.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
有向网络中被打破的详细平衡和熵产生。
复杂网络的结构在决定其动态特性方面起着至关重要的作用。在本文中,我们证明了网络的有向性和层次组织程度与其动力学打破详细平衡和产生熵的程度密切相关。我们考虑了一系列动力学过程,并展示了不同的有向网络特征如何影响它们的熵产生率。我们首先对双节点网络进行分析处理,然后使用优先附着算法和埃尔德斯-雷尼算法对合成网络进行数值模拟。接下来,我们分析了 97 个经验网络集合,以确定复杂现实世界拓扑结构的影响。最后,我们提出了一种简单的方法,用于从多元时间序列中推断破碎的详细平衡和有向网络结构,并将我们的方法应用于识别人类神经成像和金融时间序列中的非平衡动态和分层组织。总之,我们的研究结果揭示了有向网络结构对非均衡动态的影响,并强调了分层组织和非均衡动态在现实世界系统中的重要性和普遍性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
期刊最新文献
Efficient machine learning approach for accurate free-energy profiles and kinetic rates. Emergence of unitary symmetry of microcanonically truncated operators in chaotic quantum systems. Eshelby problem in amorphous solids. Exactly solvable Stuart-Landau models in arbitrary dimensions. Hydrodynamic behavior near dynamical criticality of a facilitated conservative lattice gas.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1