Compressing the chronology of a temporal network with graph commutators

Fuente: arXiv
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Main Authors: Allen, Andrea J., Moore, Cristopher, Hébert-Dufresne, Laurent
Format: Preprint
Published: 2022
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author Allen, Andrea J.
Moore, Cristopher
Hébert-Dufresne, Laurent
author_facet Allen, Andrea J.
Moore, Cristopher
Hébert-Dufresne, Laurent
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2205_11566
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Compressing the chronology of a temporal network with graph commutators
Allen, Andrea J.
Moore, Cristopher
Hébert-Dufresne, Laurent
Social and Information Networks
Physics and Society
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.
title Compressing the chronology of a temporal network with graph commutators
topic Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2205.11566