A stochastic approximation for the finite-size Kuramoto–Sakaguchi model

IF 2.7 3区 数学 Q1 MATHEMATICS, APPLIED
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引用次数: 0

Abstract

We perform a stochastic model reduction of the Kuramoto–Sakaguchi model for finitely many coupled phase oscillators with phase frustration. Whereas in the thermodynamic limit coupled oscillators exhibit stationary states and a constant order parameter, finite-size networks exhibit persistent temporal fluctuations of the order parameter. These fluctuations are caused by the interaction of the synchronised oscillators with the non-entrained oscillators. We present numerical results suggesting that the collective effect of the non-entrained oscillators on the synchronised cluster can be approximated by a Gaussian process. This allows for an effective closed evolution equation for the synchronised oscillators driven by a Gaussian process which we approximate by a two-dimensional Ornstein–Uhlenbeck process. Our reduction reproduces the stochastic fluctuations of the order parameter and leads to a simple stochastic differential equation for the order parameter.

有限尺寸仓本坂口模型的随机近似值
我们对具有相位挫折的有限多个耦合相位振荡器的仓本-阪口模型进行了随机模型还原。在热力学极限中,耦合振荡器表现出静止状态和恒定的阶次参数,而有限大小的网络则表现出持续的阶次参数时间波动。这些波动是由同步振荡器与非约束振荡器的相互作用引起的。我们给出的数值结果表明,非约束振荡器对同步集群的集体影响可以用高斯过程来近似。这就为我们用二维奥恩斯坦-乌伦贝克过程近似表示的高斯过程驱动的同步振荡器提供了一个有效的封闭演化方程。我们的还原再现了阶次参数的随机波动,并为阶次参数引出了一个简单的随机微分方程。
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来源期刊
Physica D: Nonlinear Phenomena
Physica D: Nonlinear Phenomena 物理-物理:数学物理
CiteScore
7.30
自引率
7.50%
发文量
213
审稿时长
65 days
期刊介绍: Physica D (Nonlinear Phenomena) publishes research and review articles reporting on experimental and theoretical works, techniques and ideas that advance the understanding of nonlinear phenomena. Topics encompass wave motion in physical, chemical and biological systems; physical or biological phenomena governed by nonlinear field equations, including hydrodynamics and turbulence; pattern formation and cooperative phenomena; instability, bifurcations, chaos, and space-time disorder; integrable/Hamiltonian systems; asymptotic analysis and, more generally, mathematical methods for nonlinear systems.
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