Novel approaches to Networks of Interacting Autonomes

EPSRC High-performance Computing consortium project on complex systems. Our role was to model earthquakes using cellular automaton modelling to test the hypothesis of maximum entropy production as a driver for emergent order in the scaling properties of model and natural earthquake populations. We also developed statistical techniques for model selection to discriminate between competing models based on natural available data.

The aim of the project was to develop computational models for the evolution of order and pattern in earthquake populations, and assess the implications for prediction of hazard.

Earthquake populations have properties consistent with a phase transition in near but sub-critical state
This state is consistent with maximum entropy production as a driver for order and pattern in the population dynamics.