CCS2021 Satellite Symposium

Data-based diagnosis of networked dynamical systems

Philippe Jacquod

University of Geneva

Reconstructing Network Structures from Partial Measurements
9:55 am, Room St Clair 3B

The dynamics of systems of interacting agents is determined by the structure of their coupling network. The knowledge of the latter is therefore highly desirable, for instance to develop efficient control schemes, to accurately predict the dynamics or to better understand inter-agent processes. In many important and interesting situations, the network structure is not known, however, and previous investigations have shown how it may be inferred from complete measurement time series, on each and every agent. These methods implicitly presuppose that, even though the network is not known, all its nodes are, and that they are furthermore accessible to signal injection or detection, or both. A further shortcoming of theirs is that they cannot provide any reliable information, not even on partial network structures, as soon as some agents are unobservable.


In this talk, I will describe a novel method that determines partial network structures even when not all agents are measurable. I will describe analytically and illustrate numerically that velocity signal correlators encode not only direct couplings, but also geodesic distances in the coupling network, within the subset of measurable agents. When dynamical data are accessible for all agents, the method is furthermore algorithmically more efficient than the traditional ones, because it does not rely on matrix inversion.


Work in collaboration with Melvyn Tyloo (U of Geneva) and Robin Delabays (UCSB).

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