Hosted by The
International Conference on Statistical Physics SigmaPhi 2023, this
Workshop aims to stimulate discussions towards an in-depth understanding of higher-order connectivity in emergent functional properties of complex systems by covering recent developments in the field.
The influence of network structure on dynamics in many complex systems has been demonstrated in numerous studies with a detailed analysis of empirical data and theoretical approaches. Recent studies of networks representing various complex systems from the brain to large-scale social dynamics have revealed their higher-order architecture, which can be described as aggregates of simplexes (triangles, tetrahedrons, and higher cliques). Beyond the standard graph theory, these hidden structures are quantified by algebraic topology methods. This Special Session will bring together presentations exploring different complex systems concerning a) the structure of simplicial complexes, including the properties of the underlying topological graph (network); b) dynamic processes in a particular or co-evolving network structure; c) information topology and graph representations of time series. We expect research results based on empirical data analysis and theoretical and numerical modeling. The aim is to cover recent developments in these areas of research and to stimulate discussion towards an in-depth understanding of the role of higher-order connectivity in the emergence of functional properties of complex systems.
PROGRAM ORGANIZERS: Neelima Gupte, Marija Mitrovic Dankulov, Bosiljka Tadic
