Dynamical maximum entropy approach to flocking

Andrea Cavagna*, Irene Giardina, Francesco Ginelli, Thierry Mora, Duccio Piovani, Raffaele Tavarone, Aleksandra M Walczak

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)
9 Downloads (Pure)


We derive a new method to infer from data the out-of-equilibrium alignment dynamics of collectively moving animal groups, by considering the maximum entropy model distribution consistent with temporal and spatial correlations of flight direction. When bird neighborhoods evolve rapidly, this dynamical inference correctly learns the parameters of the model, while a static one relying only on the spatial correlations fails. When neighbors change slowly and the detailed balance is satisfied, we recover the static procedure. We demonstrate the validity of the method on simulated data. The approach is applicable to other systems of active matter.

Original languageEnglish
Article number042707
Number of pages10
JournalPhysical Review. E, Statistical, Nonlinear and Soft Matter Physics
Issue number4
Publication statusPublished - 16 Apr 2014


  • collective animal behavior
  • starflag handbook
  • starling flogs
  • mechanics
  • retina
  • motion
  • birds
  • fish


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