seminars

Sizes of connected components during bond percolation in multiplex networks

Date
Wednesday, March 13, 2019

Time
12.00 p.m.

Location
ISI seminar room 1st floor

Speaker(s)
Dr. Ivan Kryven - University of Amsterdam

ABSTRACT

Percolation is the process that mimics degradation of complex networks, but it also serves as a tool that reveals mesoscopic peculiarities of a network structure. In the studies of dynamic spreading on networks, percolation relates to the steady state of this process. In this talk, I will discuss bond percolation on the random multiplex network that is modelled by the infinite configuration model, i.e. a random graph in which the node’s degree is given by a known random variable. In order to capture the multiplex structure, i.e. nodes having edges in N different layers, this random variable is made N-variate. I will then establish the connection between the random variable and the size distribution of connected components, and will discuss the implications these results have for bond percolation. The most important of which are: first, the existence of multiple phase transitions, and second, a qualitatively new type of phase transition that may emerge when edges are removed with variable probability that may be different for each layer.

BIO

Applied mathematician by training, Ivan Kryven works at the University of Amsterdam in the interdisciplinary intersection of network science, statistical physics, and computational science with applications reaching out deeply into the subject areas of soft matter, chemical kinetics, and physics of living systems. He defended his thesis in 2014 at the University of Amsterdam, and, after staying at a short postdoc position at the same university received support for independent research from the Netherlands Organisation of Scientific Research through NWO VENI grant. He also held several stays as a guest researcher in the leading research groups around the world, including the Biocomputing group at the Free University of Berlin, Morbidelli group at ETH Zurich, and Complex Systems and Network group at Queen Marry University of London.