Turbulence - "motion of multitude": a multi-agent spin model for complex flows

TL;DR

This paper introduces a multi-agent spin model to simulate complex turbulent flows as emergent phenomena from collective information exchange among agents, aiming to understand turbulence's disordered nature.

Contribution

It presents a novel multi-agent spin model that captures the emergence of macroscopic flows without relying on a fixed spacetime background, linking turbulence to spin glass and neural network dynamics.

Findings

Model demonstrates how collective agent interactions produce flow patterns.

Relational dynamics without spatio-temporal background.

Potential implications for quantum gravity theories.

Abstract

We propose a new paradigm for emergence of macroscopic flows. The latter are considered as a collective phenomenon created by many agents that exchange abstract information. The information exchange causes agents to change their relative positions which results in a flow. This paradigm, aimed at the study of the nature of turbulence, appeals to the original meaning of the word: "turbulence" siginifies "disordered motions of crowds". We give a preliminary discussion on a model of multi-agent dynamics that realizes the paradigm. This dynamics is reminiscent of spin glasses and neural networks. The model is relational, i. e. it assumes no spatio-temporal background and may serve as a basis for an approach to quantum gravity via spin models.