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Geometric Origin of Exact Mean-Field Reductions: M{ö}bius Symmetry and the Lorentzian Ansatz

Hugues Berry

Abstract

Low-dimensional descriptions of large systems of coupled oscillators and spiking neurons rely heavily on the Lorentzian Ansatz. We show that its privileged role is geometric rather than heuristic: for the transport induced by Riccati dynamics, the Cauchy-Lorentz family indeed emerges as the unique connected two-dimensional family of continuous probability densities that is invariant under the induced projective transport. The key step of the demonstration is to reformulate the dynamics on the ci...

Submitted: May 25, 2026Subjects: Neuroscience; Neuroscience

Description / Details

Low-dimensional descriptions of large systems of coupled oscillators and spiking neurons rely heavily on the Lorentzian Ansatz. We show that its privileged role is geometric rather than heuristic: for the transport induced by Riccati dynamics, the Cauchy-Lorentz family indeed emerges as the unique connected two-dimensional family of continuous probability densities that is invariant under the induced projective transport. The key step of the demonstration is to reformulate the dynamics on the circle, where the problem reduces to the uniqueness of the rotation-invariant probability measure. Under stereographic projection, this yields the standard Cauchy law and, under the full projective action, the Lorentzian family. This result gives a unified geometric foundation for the Ott-Antonsen [Chaos 18, 037113 (2008)] and Montbri{ó}-Paz{ó}-Roxin [Phys. Rev. X 5, 021028 (2015)] reductions, explains the failure of Gaussian closures, and identifies the structural condition underlying exact two-parameter reductions.


Source: arXiv:2605.23669v1 - http://arxiv.org/abs/2605.23669v1 PDF: https://arxiv.org/pdf/2605.23669v1 Original Link: http://arxiv.org/abs/2605.23669v1

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Date:
May 25, 2026
Topic:
Neuroscience
Area:
Neuroscience
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Geometric Origin of Exact Mean-Field Reductions: M{ö}bius Symmetry and the Lorentzian Ansatz | Researchia