"We have developed a mathematical model that describes the probability of global collapse, regardless of the details of the particular network," said Dr Jingfang Fan from the Potsdam Institute for Climate Impact Research and first author of the study. This could in priniciple be applied to the interaction of proteins with regard to Alzheimer’s disease, to financial markets and climate phenomena.
Jan Nagler, professor of computer science and head of the Deep Dynamics Group at the Frankfurt School of Finance & Management led the team of researchers. “Our research was helped by a concept from the financial world that quantifies extreme changes in fluctuating financial markets,” he adds. “We have shown that this concept also describes rapid growth or collapse of large-scale networks.”
In their interdisciplinary work, the scientists combined methods from finance, physics, biochemistry, engineering and social sciences, and were able to establish for the first time a conceptual link between small and large-scale network disruptions. In the future, the theory may help to rein in percolation with timely countermeasures - such as closing airports when an epidemic spreads.
The next step for the researchers is to work out how their theory can be used to better estimate risk of sudden collapse of ecological networks and networked banks; how to identify tipping elements in Earth’s climate system, and how to anticipate disruptive weather phenomena. “Through our work, we want to ensure that we can better respond to future crises - regardless of whether economic, due to climate change or even disease. We have taken an important first step with our model," conclude Jan Nagler together with Jürgen Kurths who is a co-author of the paper and head of PIK’s research department “Complexity Science”.
Article:Fan, J., Meng, J., Liu, Y., Saberi, A.A., Kurths, J., Nagler, J. (2020): Universal gap scaling in percolation. Nature Physics [DOI:10.1038/s41567-019-0783-2]
Weblink to the article: https://www.nature.com/articles/s41567-019-0783-2
