Constructing minimal models for complex system dynamics

Baruch Barzel, Yang Yu Liu, Albert László Barabási

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


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.

Original languageEnglish
Article number7186
JournalNature Communications
StatePublished - 20 May 2015

Bibliographical note

Funding Information:
This work was supported by the Templeton Foundation: Mathematical and Physical Sciences grant no. PFI-777; Army Research Laboratories (ARL) Network Science (NS) Collaborative Technology Alliance (CTA) grant: ARL NS-CTA W911NF-09-2-0053; European Union grant no. FP7 317532 (MULTIPLEX).

Publisher Copyright:
© 2015 Macmillan Publishers Limited. All rights reserved.


Dive into the research topics of 'Constructing minimal models for complex system dynamics'. Together they form a unique fingerprint.

Cite this