Lyapunov exponents for temporal networks
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Date
2023Author
Caligiuri, A.
Eguíluz, V.M.
Di Gaetano, L.
Galla, T.
Lacasa, L.
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Physical Review E: 107 (4): 44305 (2023)
Abstract
By interpreting a temporal network as a trajectory of a latent graph dynamical system, we introduce the concept of dynamical instability of a temporal network and construct a measure to estimate the network maximum Lyapunov exponent (nMLE) of a temporal network trajectory. Extending conventional algorithmic methods from nonlinear time-series analysis to networks, we show how to quantify sensitive dependence on initial conditions and estimate the nMLE directly from a single network trajectory. We validate our method for a range of synthetic generative network models displaying low- and high-dimensional chaos and finally discuss potential applications.