A Partial Differential Equation for the Mean--Return-Time Phase of Planar Stochastic Oscillators
Alexander Cao, Benjamin Lindner, Peter J. Thomas

TL;DR
This paper develops a PDE-based method to define and compute the mean-return-time phase of planar stochastic oscillators, providing a rigorous foundation and validation through examples and simulations.
Contribution
It introduces a boundary condition for the PDE governing the MRT phase and proves the existence and uniqueness of the isochron function, advancing the theoretical understanding of stochastic oscillator phases.
Findings
The PDE for MRT phase is well-posed with the new boundary condition.
Simulations confirm the MRT return time equals the mean first-passage time.
The method applies to various stochastic oscillator models.
Abstract
Stochastic oscillations are ubiquitous in many systems. For deterministic systems, the oscillator's phase has been widely used as an effective one-dimensional description of a higher dimensional dynamics, particularly for driven or coupled systems. Hence, efforts have been made to generalize the phase concept to the stochastic framework. One notion of phase due to Schwabedal and Pikovsky is based on the mean-return time (MRT) of the oscillator but has so far been described only in terms of a numerical algorithm. Here we develop the boundary condition by which the partial differential equation for the MRT has to be complemented in order to obtain the isochrons (lines of equal phase) of a two-dimensional stochastic oscillator, and rigorously establish the existence and uniqueness of the MRT isochron function (up to an additive constant). We illustrate the method with a number of examples:…
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Taxonomy
Topicsstochastic dynamics and bifurcation · Nonlinear Dynamics and Pattern Formation · Neural dynamics and brain function
