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Complex systems are characterized by multiple spatial and temporal scales. Anatural framework to capture their multiscale nature is that of multilayernetworks, where different layers represent distinct physical processes thatoften regulate each other indirectly. We model these regulatory mechanismsthrough triadic higher-order interactions between nodes and edges. In thiswork, we focus on how the different timescales associated with each layerimpact their effective couplings in terms of their mutual information. Weunravel the general principles governing how such information propagates acrossthe multiscale structure, and apply them to study archetypal examples ofbiological signaling networks and effective environmental dependencies instochastic processes. Our framework generalizes to any dynamics on multilayernetworks, paving the way for a deeper understanding of how the multiscalenature of real-world systems shapes their information content and complexity.

Information propagation in multilayer systems with higher-order interactions across timescales