Billiards with Spatial Memory

TL;DR

This paper introduces a mathematical billiards framework where particles with spatial memory exhibit complex, non-ergodic dynamics and pattern formation, revealing how memory influences long-term behaviour and chaos in active matter systems.

Contribution

It presents a novel billiards-based model for particles with spatial memory, analyzing their non-ergodic and chaotic dynamics through extensive numerical simulations.

Findings

Particles with spatial memory show highly intermittent, complex patterns.

Memory induces non-ergodic behaviour and chaos in the system.

Pattern formation depends on billiard geometry and memory effects.

Abstract

Many classes of active matter develop spatial memory by encoding information in space, leading to complex pattern formation. It has been proposed that spatial memory can lead to more efficient navigation and collective behaviour in biological systems and influence the fate of synthetic systems. This raises important questions about the fundamental properties of dynamical systems with spatial memory. We present a framework based on mathematical billiards in which particles remember their past trajectories and react to them. Despite the simplicity of its fundamental deterministic rules, such a system is strongly non-ergodic and exhibits highly-intermittent statistics, manifesting in complex pattern formation. We show how these self-memory-induced complexities emerge from the temporal change of topology and the consequent chaos in the system. We study the fundamental properties of these billiards and particularly the long-time behaviour when the particles are self-trapped in an arrested state. We exploit numerical simulations of several millions of particles to explore pattern formation and the corresponding statistics in polygonal billiards of different geometries. Our work illustrates how the dynamics of a single-body system can dramatically change when particles feature spatial memory and provide a scheme to further explore systems with complex memory kernels.