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Akari Matsuki

Publications and source records attributed to Akari Matsuki.

4 recordsLinked to original sources

An Isochron-Free Framework for Phase Reduction and Coupling Inference

Phase description provides a compact and powerful framework for analyzing synchronization dynamics in weakly coupled limit-cycle oscillators. While its classical formulation relies on the asymptotic phase defined by isochrons, reconstructing isochrons from observed trajectories is often challenging for complex models and real-world systems. Here we develop an isochron-free framework based on a readily computable generalized phase, such as the polar angle computed from observed trajectories. We theoretically show that, under near-uniform rotation of the generalized phase and sufficiently stable amplitude dynamics, a one-period stroboscopic description yields a closed circle map. The interaction term of the resulting circle map coincides, to leading order, with the phase coupling function obtained from the conventional phase reduction. Based on this circle map, we propose a method to infer coupling from oscillatory time series. The method is validated using synthetic data from van der Pol oscillators. Our framework broadens the applicability of phase reduction and provides a theoretically grounded method for coupling inference from oscillatory data.

nlin.AO

Network inference applicable to both synchronous and desynchronous systems from oscillatory signals

Synchronization is ubiquitous in nature, which is mathematically described by coupled oscillators. Synchronization strongly depends on the interaction network, and the network plays a crucial role in controlling the dynamics. To understand and control synchronization dynamics in the real world, it is essential to identify the network from the observed data. While previous studies have developed the methods for inferring the network of asynchronous systems, it remains challenging to infer the network of well-synchronized oscillators. In this study, we develop a method for inferring the network of synchronized and desynchronized oscillators from time series. Our method expands the applicability of network inference to a wider class of oscillatory systems. The proposed method discards a large part of data used for inference, which may seem counterintuitive. However, the effectiveness of the method is supported by the phase reduction theory, a well-established theory for weakly coupled oscillators. We verify the proposed method by applying it to simulated data of the limit-cycle oscillators. This study provides an important step towards understanding synchronization in real-world systems from a network perspective.

nlin.AO

An extended Hilbert transform method for reconstructing the phase from an oscillatory signal

Rhythmic activity is ubiquitous in biological systems from the cellular to organism level. Reconstructing the instantaneous phase is the first step in analyzing the essential mechanism leading to a synchronization state from the observed signals. A popular method of phase reconstruction is based on the Hilbert transform, which can only reconstruct the interpretable phase from a limited class of signals, e.g., narrow band signals. To address this issue, we propose an extended Hilbert transform method that accurately reconstructs the phase from various oscillatory signals. The proposed method is developed by analyzing the reconstruction error of the Hilbert transform method with the aid of Bedrosian's theorem. We validate the proposed method using synthetic data and show its systematically improved performance compared with the conventional Hilbert transform method with respect to accurately reconstructing the phase. Finally, we demonstrate that the proposed method is potentially useful for detecting the phase shift in an observed signal. The proposed method is expected to facilitate the study of synchronization phenomena from experimental data.

nlin.AO

Intervention Threshold for Epidemic Control in Susceptible-Infected-Recovered Metapopulation Models

Metapopulation epidemic models describe epidemic dynamics in networks of spatially distant patches connected with pathways for migration of individuals. In the present study, we deal with a susceptible-infected-recovered (SIR) metapopulation model where the epidemic process in each patch is represented by an SIR model and the mobility of individuals is assumed to be a homogeneous diffusion. Our study focuses on two types of patches including high-risk and low-risk ones, in order to evaluate intervention strategies for epidemic control. We theoretically analyze the intervention threshold, indicating the critical fraction of low-risk patches for preventing a global epidemic outbreak. We show that targeted intervention to high-degree patches is more effective for epidemic control than random intervention. The theoretical results are validated by Monte Carlo simulation for synthetic and realistic scale-free patch networks. Our approach is useful for exploring better local interventions aimed at containment of epidemics.

physics.soc-ph