Date:
Mon, 29/04/201912:00-13:30
Location:
Levin building, Lecture Hall No. 8
Lecturer: Dr. Baruch Barzel, Bar-Ilan University
Abstract:
A major achievement in the study of complex networks is the observation that diverse systems, from sub-cellular biology to social networks, exhibit universal topological characteristics, such as the small world or the scale-free phenomena. Yet this universality does not naturally translate to the dynamics of these systems, hindering our progress towards a theoretical framework of network dynamics. The source of this theoretical gap is the fact that the behavior of a complex system cannot be uniquely predicted from its topology, but rather depends also on the dynamic mechanisms of interaction between the nodes, hence systems with similar structure may exhibit profoundly different dynamic behavior. To bridge this gap, we derive the patterns of network information flow, indeed, the essence of a network's behavior, by offering systematic translations of topological characteristics into the actual spatio-temporal propagation of perturbative signals.
Relevant papers:
Spatiotemporal propagation of signals in complex networks. Nature Physics 15, 403 (2019)
Patterns of information flow in complex networks. Nature Communications 8, 2181 (2017)
Universal resilience patterns in complex networks. Nature 530, 307 (2016)
Universality in network dynamics. Nature Physics 9, 673 (2013)
Abstract:
A major achievement in the study of complex networks is the observation that diverse systems, from sub-cellular biology to social networks, exhibit universal topological characteristics, such as the small world or the scale-free phenomena. Yet this universality does not naturally translate to the dynamics of these systems, hindering our progress towards a theoretical framework of network dynamics. The source of this theoretical gap is the fact that the behavior of a complex system cannot be uniquely predicted from its topology, but rather depends also on the dynamic mechanisms of interaction between the nodes, hence systems with similar structure may exhibit profoundly different dynamic behavior. To bridge this gap, we derive the patterns of network information flow, indeed, the essence of a network's behavior, by offering systematic translations of topological characteristics into the actual spatio-temporal propagation of perturbative signals.
Relevant papers:
Spatiotemporal propagation of signals in complex networks. Nature Physics 15, 403 (2019)
Patterns of information flow in complex networks. Nature Communications 8, 2181 (2017)
Universal resilience patterns in complex networks. Nature 530, 307 (2016)
Universality in network dynamics. Nature Physics 9, 673 (2013)