Directed percolation transition to active turbulence driven by non-reciprocal forces

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Hauptverfasser: Klamser, Juliane U., Berthier, Ludovic
Format: Preprint
Veröffentlicht: 2025
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author Klamser, Juliane U.
Berthier, Ludovic
author_facet Klamser, Juliane U.
Berthier, Ludovic
contents We numerically study the collective dynamics of dense particle assemblies driven by non-reciprocal pairwise forces of amplitude $κ$. At a critical value $κ_{\rm c}$, the system undergoes a dynamical phase transition from an absorbing state ($κ< κ_{\rm c}$) to a chaotic steady state ($κ> κ_{\rm c}$). The chaotic phase is marked by nontrivial spatiotemporal velocity correlations and mixing, reminiscent of active turbulence in self-propelled systems. The sharp onset of chaos shows critical scaling consistent with the universality class of directed percolation. We argue that this transition is generic to a broad class of locally-driven, dense disordered materials.
format Preprint
id arxiv_https___arxiv_org_abs_2510_04575
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Directed percolation transition to active turbulence driven by non-reciprocal forces
Klamser, Juliane U.
Berthier, Ludovic
Statistical Mechanics
Disordered Systems and Neural Networks
We numerically study the collective dynamics of dense particle assemblies driven by non-reciprocal pairwise forces of amplitude $κ$. At a critical value $κ_{\rm c}$, the system undergoes a dynamical phase transition from an absorbing state ($κ< κ_{\rm c}$) to a chaotic steady state ($κ> κ_{\rm c}$). The chaotic phase is marked by nontrivial spatiotemporal velocity correlations and mixing, reminiscent of active turbulence in self-propelled systems. The sharp onset of chaos shows critical scaling consistent with the universality class of directed percolation. We argue that this transition is generic to a broad class of locally-driven, dense disordered materials.
title Directed percolation transition to active turbulence driven by non-reciprocal forces
topic Statistical Mechanics
Disordered Systems and Neural Networks
url https://arxiv.org/abs/2510.04575