This talk will be presented by CSH visitor Deb Panja (Complex Systems Studies at Utrecht University) on Friday, November 18 at 3 pm in the Salon.
If you would like to attend, please email to office@csh.ac.at.
Title: Optimised for efficiency and vulnerable to spreading: a perspective from temporal networks
Abstract:
The concepts of build-up and spontaneous relaxation of “tensions” due to reorganizations within complex systems have been the defining characteristics of self-organised criticality. They have also found their places in econophysics literature. I will take this further for socio-technical systems such as transport and supply chains: using extensive real-life operational data from the Dutch railways, I will demonstrate that a temporal network is a very well-suited language for describing such tensions in the system to trace out its systemic vulnerability to spreading [1]. Touching upon “a system more optimized for efficiency is more vulnerable to spreading phenomena”, I will develop “entanglement entropy” as a measure for tension in temporal networks [2]. The framework will also bring us to a completely different application: spreading of infectious diseases (the specific application is reanalysing/modelling the first COVID-19 wave in the Netherlands for policy purposes).
[1] M. M. Dekker and D. Panja. Cascading dominates large-scale disruptions in transport over complex networks. PLOS ONE 16, e0246077 (2021).
[2] M. M. Dekker, R. D. Schram, J. Ou and D. Panja. Hidden dependence of spreading vulnerability on topological complexity. Phys. Rev. E 105,054301 (2022).
[3] M. M. Dekker, L. E. Coffeng, F. P. Pijpers, D. Panja and S. J. de Vlas. Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation. https://www.medrxiv.org/content/10.1101/2022.03.31.22273222.abstract (in revision for eLife).
About:
Deb Panja is an Complex Systems scientist and the vice-director of the Centre for Complex Systems Studies at Utrecht University. Working in the interface of Physics, Applied Mathematics and Computational Science, his keen interest lies in addressing real-world problems and issues. His collaborations include a broad spectrum of disciplines, e.g., biology, ecology, neuroscience, epidemiology, transport systems and economic complexity.