Enhanced synchronization due to intermittent noise

Shajan, Emilda; Asir, M. Paul; Dixit, Shiva; Kurths, Jürgen; Shrimali, Manish Dev

doi:10.1088/1367-2630/ac3885

Cited by 16 publications

(2 citation statements)

References 52 publications

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“…It was also observed that the time spent by the trajectories in the contraction region can be improved by restricting the noise infusion to a limited range of the state space resulting in an enhanced synchronization. 39 Realistic systems, such as the Pikovski-Rabinovich (PR) circuit model and the Hindmarsh-Rose (HR) neuron model, also show noise-induced synchronization. 40 In fact, neuron models are known to have high sensitivity to channel noises.…”

Section: Articlementioning

confidence: 99%

Direction-dependent noise-induced synchronization in mobile oscillators

Shajan

Ghosh

Kurths

et al. 2023

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Synchronization among uncoupled oscillators can emerge when common noise is applied on them and is famously known as noise-induced synchronization. In previous studies, it was assumed that common noise may drive all the oscillators at the same time when they are static in space. Understanding how to develop a mathematical model that apply common noise to only a fraction of oscillators is of significant importance for noise-induced synchronization. Here, we propose a direction-dependent noise field model for noise-induced synchronization of an ensemble of mobile oscillators/agents, and the effective noise on each moving agent is a function of its direction of motion. This enables the application of common noise if the agents are oriented in the same direction. We observe not only complete synchronization of all the oscillators but also clustered states as a function of the ensemble density beyond a critical value of noise intensity, which is a characteristic of the internal dynamics of the agents. Our results provide a deeper understanding on noise-induced synchronization even in mobile agents and how the mobility of agents affects the synchronization behaviors.

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Section: Articlementioning

confidence: 99%

Direction-dependent noise-induced synchronization in mobile oscillators

Shajan

Ghosh

Kurths

et al. 2023

Chaos: An Interdisciplinary Journal of Nonlinear Science

Self Cite

View full text Add to dashboard Cite

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“…Noise-induced behaviors could trigger a large-range transition in the transient process [9][10][11]. Generally, the probabilistic description of the stochastic response is governed by Fokker-Planck-Kolmogorov (FPK) equation, but it is difcult to obtain the exact solution for the second-order parabolic partial diferential equation.…”

Section: Introductionmentioning

confidence: 99%

A Short‐Time Non‐Gaussian Probability Approximation Based Method for Response Transitions of a Lévy‐Driven Nonsmooth System

Wang

Kang

et al. 2023

Mathematical Problems in Engineering

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This paper proposes an efficient short-time probability approximation with Lévy excitation to capture the transient probability distribution and its evolving path. Using principal component analysis (PCA), the method constructs a probability core to exclude outliers beyond it. The statistics of samples that fall inside the core are treated, with a prescribed fiducial probability, as an easy-to-estimate Gaussian type. The idea is verified numerically by compared with Monte-Carlo results. Then, it is integrated into the path integral (PI) method, combined with evolving probabilistic vector (EPV) techniques, to efficiently obtain probability distributions in each time step of PI. This scheme is semianalytical, only dependent on a relatively small amount of response samples to form the probability core; thus, it can have very computational advantages over full Monte-Carlo simulation to capture transient responses and probability distributions. The application to investigating response transitions of a nonsmooth system driven by Lévy shock and jump has revealed the performance of the proposed method. Also, the exit times of stochastic response are characterized quantitatively from the perspective of global dynamic transition. These investigations will be helpful to achieve the efficient probability estimation for nonlinear system with non-Gaussian inputs and quantify the reliability of the mechanical system.

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