Constructing minimal models for complex system dynamics

B. Barzel, Y.-Y. Liu, A.-L. Barabási
Nature Communications
6:7186, 1-8 (2015)
May 20, 2015


One of the  strengths of statistical physics is the ability to reduce macroscopic  observations into  microscopic  models,   offering  a  mechanistic   description  of  a   system's  dynamics.This  paradigm, rooted in Boltzmann's gas theory, has found applications from  magnetic phenomena to subcellular processes and epidemic spreading. Yet, each  of these advances were the result of decades of meticulous model building and  validation, which are impossible to replicate in most complex biological,  social or technological systems that lack accurate microscopic models. Here we  develop a method to infer the microscopic dynamics of a complex system from  observations of its response to external perturbations, allowing us  to construct the most general class of nonlinear pairwise dynamics that are  guaranteed to recover the observed behaviour. The result,  which we test against both  numerical and empirical data, is an  effective dynamic model that can predict the system's behaviour and provide  crucial insights into its inner workings.

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