计算机科学
追踪
图形
动力学(音乐)
网络动力学
系列(地层学)
算法
基质(化学分析)
统计物理学
理论计算机科学
物理
数学
离散数学
地质学
古生物学
材料科学
声学
复合材料
操作系统
作者
Andrea J. Allen,Cristopher Moore,Laurent Hébert‐Dufresne
标识
DOI:10.1103/physrevlett.132.077402
摘要
Studies of dynamics on temporal networks often represent the network as a series of ``snapshots,'' static networks active for short durations of time. We argue that successive snapshots can be aggregated if doing so has little effect on the overlying dynamics. We propose a method to compress network chronologies by progressively combining pairs of snapshots whose matrix commutators have the smallest dynamical effect. We apply this method to epidemic modeling on real contact tracing data and find that it allows for significant compression while remaining faithful to the epidemic dynamics.
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