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SUMMARY:Learning the topology of complex systems from their dynamics - Pro
 fessor Ginestra Bianconi - Queen Mary University of London
DTSTART:20230510T140500Z
DTEND:20230510T145500Z
UID:TALK199387@talks.cam.ac.uk
CONTACT:Ben Karniely
DESCRIPTION:From the brain to the climate\, complex systems constitute a r
 eal challenge for scientists and mathematicians as they are giving rise to
  dynamical phenomena notoriously difficult to understand\, model and predi
 ct.\n\nIn the last twenty years the scientific community has made unpreced
 ented progress in unveiling the structure of complex systems encoded in th
 eir network skeleton formed by the set of their pairwise interactions. How
 ever networks are not able to characterize the ubiquitous higher-order int
 eractions between more than two nodes that give rise to the complex system
 s topology captured by higher-order networks and simplicial complexes.\n\n
 Here we reveal how non-linear dynamical processes can be used to learn the
  topology\, by defining Topological Kuramoto model and Topological global 
 synchronization. These critical phenomena capture the synchronization of t
 opological signals\, i.e. dynamical signals defined not only on nodes but 
 also on links\, triangles and higher-dimensional simplices in simplicial c
 omplexes. Moreover will discuss how the Dirac operator can be used to coup
 le and process topological signal of different dimensions\, formulating Di
 rac signal processing. Finally we will reveal how non-linear dynamics can 
 shape topology by formulating triadic percolation. In triadic percolation 
 triadic interactions can turn percolation into a fully-fledged dynamical p
 rocess in which nodes can turn on and off intermittently in a periodic fas
 hion or even chaotically leading to period doubling and a route to chaos o
 f the percolation order parameter.  Triadic percolation changes drasticall
 y our understanding of percolation and can describe real systems in which 
 the giant component varies significantly in time such as in brain function
 al networks and in climate.\n\n\nLink to join virtually: https://zoom.us/j
 /98901725392?pwd=UWNVZVFTcVQxL2JkS0V1WVBoelBuUT09\n\nA recording of this t
 alk is available at the following link: https://www.cl.cam.ac.uk/seminars/
 wednesday/video/
LOCATION:Lecture Theatre 1\, Computer Laboratory\, William Gates Building
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