Title: Maximum entropy network states for coalescence processes Show Chinese title

Title: 共聚过程的最大熵网络状态

Abstract: Complex network states are characterized by the interplay between system's structure and dynamics. One way to represent such states is by means of network density matrices, whose von Neumann entropy characterizes the number of distinct microstates compatible with given topology and dynamical evolution. In this Letter, we propose a maximum entropy principle to characterize network states for systems with heterogeneous, generally correlated, connectivity patterns and non-trivial dynamics. We focus on three distinct coalescence processes, widely encountered in the analysis of empirical interconnected systems, and characterize their entropy and transitions between distinct dynamical regimes across distinct temporal scales. Our framework allows one to study the statistical physics of systems that aggregate, such as in transportation infrastructures serving the same geographic area, or correlate, such as inter-brain synchrony arising in organisms that socially interact, and active matter that swarm or synchronize. Show Chinese abstract

Abstract: 复杂网络状态由系统结构与动态之间的相互作用所表征。 表示这些状态的一种方法是通过网络密度矩阵，其冯·诺依曼熵表征与给定拓扑和动态演化相容的不同微观状态的数量。 在本文中，我们提出一种最大熵原理，用于表征具有异质性、通常相关联的连接模式和非平凡动态的系统网络状态。 我们关注三种不同的凝聚过程，这些过程在分析经验互连系统时广泛出现，并研究其熵以及在不同时间尺度上不同动态范式之间的转换。 我们的框架允许研究聚合系统（如服务于同一地理区域的交通基础设施）或相关系统（如社会互动生物之间的脑间同步或群体物质的群集或同步）的统计物理特性。