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Abstract model of rhythm synchronization driven by asymmetric dissipation under VNAE.

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VNAE-Synchronization-of-Biological-Rythms

Overview

Abstract model of rhythm synchronization driven by asymmetric dissipation under VNAE.

Rather than pursuing biological realism, the objective is to expose a geometric mechanism of global convergence driven by asymmetric dissipation.

We reinterpret synchronization as a manifestation of asymmetric dissipation.

This example does not aim to compete with classical biological oscillator models (e.g. Kuramoto, Winfree).  Instead, it provides a structural explanation for convergence in heterogeneous systems.


Model

We consider a network of ( N ) abstract oscillatory units, each represented by a scalar phase variable ( \phi_i(t) ).

The dynamics are given by:

    dφ/dt = − L φ − Θ φ

where:

  • φ ∈ ℝⁿ is the vector of phase states  
  • L is the graph Laplacian encoding network coupling  
  • Θ = diag(θ₁, …, θₙ) is a diagonal matrix of asymmetric dissipation parameters

Interpretation

  • The Laplacian term promotes coordination between neighboring units.
  • The asymmetric dissipation term introduces heterogeneous contraction rates.
  • No sinusoidal coupling, frequency tuning, or phase-locking assumptions are required.

In this framework, we can see it is clear and understandable that synchronization emerges as a consequence of global dissipation geometry, not parameter fine-tuning.


Victoria-Nash Asymmetric Equilibrium (VNAE): The Proposed Framework

Within the VNAE framework:

  • Asymmetry is not treated as a perturbation or defect.
  • Heterogeneity induces an effective positive curvature in the system’s state space.
  • Global convergence follows structurally, even without symmetric equilibria.

In this sense, synchronization appears as an operational manifestation of positive curvature, rather than a classical phase-locking phenomenon.


Relevance

The same structural principle applies to:

  • abstract neural synchronization
  • circadian rhythm coordination
  • coupled chemical oscillators
  • distributed dynamical systems beyond biology

Implementation

The simulation is implemented in R, Python, Julia, and Matlab, using:

  • explicit Euler integration
  • simple ring network topology
  • heterogeneous dissipation parameters

The code demonstrates how asymmetric agents converge to a synchronized regime without symmetry assumptions.


Reference

Pereira, D. H. (2025). Riemannian Manifolds of Asymmetric Equilibria: The Victoria-Nash Geometry.

License

MIT License