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Synchronization occurs ubiquitously in nature. The van der Pol oscillator has been a favorite model to investigate synchronization. Here we study the oscillator in the deep quantum regime, where nonclassical effects dominate the dynamics.…

Quantum Physics · Physics 2020-09-23 Wai Keong Mok , Leong Chuan Kwek , Hermanni Heimonen

We analyze the effect of the simultaneous presence of correlated additive and multiplicative noises on the stochastic resonance response of a modulated bistable system. We find that when the correlation parameter is also modulated, the…

Statistical Mechanics · Physics 2009-10-31 Claudio J. Tessone , Horacio S. Wio

The analysis of a birhythmic modified van der Pol type oscillator driven by periodic excitation and L\`evy noise shows the possible occurrence of coherence resonance and stochastic resonance. The frequency of the harmonic excitation in the…

Adaptation and Self-Organizing Systems · Physics 2021-01-14 R. Mbakob Yonkeu , R. Yamapi , G. Filatrella , J. Kurths

Phase reduction is a dimensionality reduction scheme to describe the dynamics of nonlinear oscillators with a single phase variable. While it is crucial in synchronization analysis of coupled oscillators, analytical results are limited to…

Adaptation and Self-Organizing Systems · Physics 2023-10-12 Iván León , Hiroya Nakao

It is a well established result that, in classical dynamical systems with sufficient time-scale separation, the fast chaotic degrees of freedom are well modeled by (Gaussian) white noise. In this paper, we present the stochastic dynamical…

Statistical Mechanics · Physics 2009-12-06 Jun Chul Park

Many time series classification tasks, where labels vary over time, are affected by label noise that also varies over time. Such noise can cause label quality to improve, worsen, or periodically change over time. We first propose and…

Machine Learning · Computer Science 2025-03-18 Sujay Nagaraj , Walter Gerych , Sana Tonekaboni , Anna Goldenberg , Berk Ustun , Thomas Hartvigsen

In this letter we explore how recurrence quantifier, the determinism ($\Delta$), can reveal stationarity breaking and coupling between physical systems. We demonstrate that it is possible to detect small variations in a dynamical system…

We consider dynamical systems arising from substitutions over a finite alphabet. We prove that such a system is linearly repetitive if and only if it is minimal. Based on this characterization we extend various results from primitive…

Dynamical Systems · Mathematics 2015-02-24 D. Damanik , D. Lenz

We introduce a simple method to estimate the system parameters in continuous dynamical systems from the time series. In this method, we construct a modified system by introducing some constants (controlling constants) into the given…

Chaotic Dynamics · Physics 2009-11-10 P. Palaniyandi , M. Lakshmanan

We study the overdamped motion of a particle in a bistable potential subject to the action of a bichromatic force and additive noise, within the context of the vibrational resonance phenomenon. Under appropriate conditions, we obtain…

Statistical Mechanics · Physics 2016-08-16 Jesús Casado-Pascual , José Pablo Baltanás

We analyze the robust character against non-static noise of clock transitions implemented via a method of continuous dynamical decoupling (CDD) in a hyperfine Zeeman multiplet in ^{87}\textrm{Rb}. The emergence of features specific to the…

Quantum Physics · Physics 2023-11-16 J. M. Gomez Llorente , I. Gomez-Ojeda , J. Plata

We propose localized spectral estimators for the quadratic covariation and the spot covolatility of diffusion processes which are observed discretely with additive observation noise. The eligibility of this approach to lead to an…

Statistics Theory · Mathematics 2015-03-19 Markus Bibinger , Markus Reiß

Periodic autoregressive (PAR) time series with finite variance is considered as one of the most common models of second-order cyclostationary processes. However, in the real applications, the signals with periodic characteristics may be…

Methodology · Statistics 2024-03-13 Wojciech Żuławiński , Agnieszka Wyłomańska

When employing non-linear methods to characterise complex systems, it is important to determine to what extent they are capturing genuine non-linear phenomena that could not be assessed by simpler spectral methods. Specifically, we are…

Methodology · Statistics 2021-09-22 Pedro A. M. Mediano , Fernando E. Rosas , Adam B. Barrett , Daniel Bor

This paper is centered around the approximation of dynamical systems by means of Gaussian processes. To this end, trajectories of such systems must be collected to be used as training data. The measurements of these trajectories are…

Systems and Control · Electrical Eng. & Systems 2025-04-02 Tobias M. Wolff , Victor G. Lopez , Matthias A. Müller

We study the effect of additive Brownian noise on an ODE system that has a stable hyperbolic limit cycle, for initial data that are attracted to the limit cycle. The analysis is performed in the limit of small noise - that is, we modulate…

Probability · Mathematics 2016-01-19 Giambattista Giacomin , Christophe Poquet , Assaf Shapira

Noise can induce coherent oscillations in excitable systems without periodic orbits. Here, we establish a method to derive a hybrid system approximating the noise-induced coherent oscillations in excitable systems and further perform phase…

Adaptation and Self-Organizing Systems · Physics 2022-05-26 Jinjie Zhu , Yuzuru Kato , Hiroya Nakao

We consider classical nonlinear oscillators on hexagonal lattices. When the coupling between the elements is repulsive, we observe coexisting states, each one with its own basin of attraction. These states differ by their degree of…

Adaptation and Self-Organizing Systems · Physics 2015-06-16 F. Ionita , D. Labavic , M. A. Zaks , H. Meyer-Ortmanns

We consider the problem of learning the dynamics of a linear system when one has access to data generated by an auxiliary system that shares similar (but not identical) dynamics, in addition to data from the true system. We use a weighted…

Machine Learning · Statistics 2025-01-20 Lei Xin , Lintao Ye , George Chiu , Shreyas Sundaram

Dynamic mode decomposition (DMD) is a popular approach to analyzing and modeling fluid flows. In practice, datasets are almost always corrupted to some degree by noise. The vanilla DMD is highly noise-sensitive, which is why many…

Fluid Dynamics · Physics 2025-01-30 Andre Weiner , Janis Geise