Discrete Laplacian thermostat for flocks and swarms: the fully conserved Inertial Spin Model

TL;DR

This paper introduces a fully conservative Inertial Spin Model for flocks and swarms, preserving spin conservation laws and capturing key dynamical features, with numerical results aligning with theoretical predictions.

Contribution

The paper develops a novel conservative version of the ISM that strictly respects spin conservation, extending the model's applicability to equilibrium and active regimes.

Findings

The conservative ISM reproduces spin wave phenomena in ordered phases.

Numerical critical exponents match theoretical predictions.

Model captures both equilibrium and active flock dynamics.

Abstract

Experiments on bird flocks and midge swarms reveal that these natural systems are well described by an active theory in which conservation laws play a crucial role. By building a symplectic structure that couples the particles' velocities to the generator of their internal rotations (spin), the Inertial Spin Model (ISM) reinstates a second-order temporal dynamics that captures many phenomenological traits of flocks and swarms. The reversible structure of the ISM predicts that the total spin is a constant of motion, the central conservation law responsible for all the novel dynamical features of the model. However, fluctuations and dissipation introduced in the original model to make it relax, violate the spin conservation law, so that the ISM aligns with the biophysical phenomenology only within finite-size regimes, beyond which the overdamped dynamics characteristic of the Vicsek model takes over. Here, we introduce a novel version of the ISM, in which the irreversible terms needed to relax the dynamics strictly respect the conservation of the spin. We perform a numerical investigation of the fully conservative model, exploring both the fixed-network case, which belongs to the equilibrium class of Model G, and the active case, characterized by self-propulsion of the agents and an out-of-equilibrium reshuffling of the underlying interaction network. Our simulations not only capture the correct spin wave phenomenology of the ordered phase, but they also yield dynamical critical exponents in the near-ordering phase that agree very well with the theoretical predictions.