Correlations of network trajectories

Temporal networks model how the interaction between elements in a complex system evolves over time. Just as systems display collective dynamics, here we interpret temporal trajectories performing motion graph space, following latent dynamical system. Under this paradigm, propose way to measure network pulsates and collectively fluctuates time space. To aim, extend notion of linear correlation functions case sequences snapshots, i.e., trajectory. We construct stochastic deterministic show that emergent correlations are well captured by simple measures, illustrate these patterns revealed empirical arising different domains.Received 31 January 2022Revised 29 June 2022Accepted 23 August 2022DOI:https://doi.org/10.1103/PhysRevResearch.4.L042008Published American Physical Society under terms Creative Commons Attribution 4.0 International license. Further distribution work must maintain attribution author(s) published article's title, journal citation, DOI.Published SocietyPhysics Subject Headings (PhySH)Research AreasComplex systemsNetwork structurePattern formationPhysical SystemsDynamical systemsStochastic systemsInterdisciplinary Physics