Chaos最新文献_第3页

Data driven discovery of escape phenomena in stochastic systems. 随机系统中逃逸现象的数据驱动发现。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0264403

Jiangyan Liu, Jiaqian Zhao, Ming Yi, Jinqiao Duan, Xiaoli Chen

{"title":"Data driven discovery of escape phenomena in stochastic systems.","authors":"Jiangyan Liu, Jiaqian Zhao, Ming Yi, Jinqiao Duan, Xiaoli Chen","doi":"10.1063/5.0264403","DOIUrl":"https://doi.org/10.1063/5.0264403","url":null,"abstract":"Stochastic dynamical systems, influenced by random disturbances, exhibit complex behaviors that are critical to understanding in various fields, such as physics, biology, and finance. The study of escape phenomena, where systems transition from stable states under the influence of noise, is essential for analyzing the dynamical behavior and learning the stochastic dynamics. This paper focuses on two key deterministic quantities, the mean exit time and the escape probability, which are widely used to analyze escape characteristics in stochastic dynamical systems. Traditional methods for computing escape problems, such as the finite difference method, finite element method, finite volume method, and Monte Carlo simulations, face challenges in high-dimensional systems and irregular domains. To address these limitations, we propose a comprehensive framework based on physics-informed neural networks. This framework is designed to solve both forward and inverse problems of escape phenomena in stochastic systems driven by Brownian motion. Our approach eliminates the need for mesh generation and naturally accommodates irregular domains, achieving a better balance between computational efficiency and accuracy. It not only overcomes the drawbacks of traditional numerical methods in solving mean exit time and escape probability but also enables learning stochastic dynamics from escape data. Through a series of numerical examples, we demonstrate the effectiveness and accuracy of the proposed method.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144109975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intermittent spike train processing through fractional leaky integrate-and-fire neuromorphic unit. 断断续续的尖峰序列处理通过分数泄漏整合-火神经形态单元。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0251233

R T Sibatov, A K Gavrilova, A I Savitskiy, Yu P Shaman, A V Sysa

引用次数: 0

Geodesic vortex detection on curved surfaces: Analyzing the 2002 austral stratospheric polar vortex warming event. 曲面上的测地线涡旋探测：分析2002年南方平流层极地涡旋变暖事件。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0256314

F Andrade-Canto, F J Beron-Vera, G Bonner

{"title":"Geodesic vortex detection on curved surfaces: Analyzing the 2002 austral stratospheric polar vortex warming event.","authors":"F Andrade-Canto, F J Beron-Vera, G Bonner","doi":"10.1063/5.0256314","DOIUrl":"https://doi.org/10.1063/5.0256314","url":null,"abstract":"Geodesic vortex detection is a tool in nonlinear dynamical systems to objectively identify transient vortices with flow-invariant boundaries that defy the typical deformation found in 2D turbulence. Initially formulated for flows on the Euclidean plane with Cartesian coordinates, we have extended this technique to flows on 2D Riemannian manifolds with arbitrary coordinates. This extension required further formulation of the concept of objectivity on manifolds. Moreover, a recently proposed birth-and-death vortex framing algorithm, based on geodesic detection, has been adapted to address the limited temporal validity of 2D motion in otherwise 3D flows, like those found in the Earth's stratosphere. With these adaptations, we focused on the Lagrangian, i.e., kinematic, aspects of the austral stratospheric polar vortex during the exceptional sudden warming event of 2002, which resulted in the splitting of the vortex. This study involved applying geodesic vortex detection to isentropic winds from reanalysis data. We provide a detailed analysis of the vortex's life cycle, covering its birth, splitting process, and eventual death. In addition, we offer new kinematic insights into ozone depletion within the vortex.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143961211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coherence resonance in a nonlinear aeroelastic system. 非线性气动弹性系统的相干共振。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0261296

Varun H S, M S Aswathy, Sunetra Sarkar

{"title":"Coherence resonance in a nonlinear aeroelastic system.","authors":"Varun H S, M S Aswathy, Sunetra Sarkar","doi":"10.1063/5.0261296","DOIUrl":"https://doi.org/10.1063/5.0261296","url":null,"abstract":"This study is a novel attempt to investigate and establish coherence resonance in a nonlinear aeroelastic system under additive Gaussian white noise. It offers a fresh perspective compared to the earlier studies in this field, which mostly focused on the undesirable disordered responses due to noise, while the present study explores the ability of noise to induce \"order\" in the system. The baseline deterministic model considered is a classical representative of a fluid-structure interaction system displaying subcritical Hopf bifurcation and is well-studied due to its engineering relevance. The interplay between the input noise and the nonlinearity has a profound impact on the dynamics, and at an optimum level of noise, the system exhibits nearly periodic, coherent oscillations. This is identified as the phenomenon of coherence resonance commonly exhibited by nonlinear systems, marked by a peak coherency in response at an intermediate noise level. The coherency is quantified by the signal-to-noise ratio, correlation time, and inter-spike intervals for conclusive evidence of the phenomenon. The effects of the findings could be far-reaching in aeroelasticity: noise could be used constructively to excite the desired coherent responses to increase the energy harvested from the structure, or conversely, trigger flutter instability which is detrimental to the structure.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143955807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computing classical escape rates from periodic orbits in chaotic hydrogen. 计算混沌氢周期轨道的经典逃逸率。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0237613

Ethan T Custodio, Sulimon Sattari, Kevin A Mitchell

{"title":"Computing classical escape rates from periodic orbits in chaotic hydrogen.","authors":"Ethan T Custodio, Sulimon Sattari, Kevin A Mitchell","doi":"10.1063/5.0237613","DOIUrl":"https://doi.org/10.1063/5.0237613","url":null,"abstract":"When placed in parallel magnetic and electric fields, the electron trajectories of a classical hydrogen atom are chaotic. The classical escape rate of such a system can be computed with classical trajectory Monte Carlo techniques, but these computations require enormous numbers of trajectories, provide little understanding of the dynamical mechanisms involved, and must be completely rerun for any change of system parameters, no matter how small. We demonstrate an alternative technique to classical trajectory Monte Carlo computations based on classical periodic orbit theory. In this technique, escape rates are computed from a relatively modest number (a few thousand) of periodic orbits of the system. One only needs the orbits' periods and stability eigenvalues. A major advantage of this approach is that one does not need to repeat the entire analysis from scratch as system parameters are varied; one can numerically continue the periodic orbits instead. We demonstrate the periodic orbit technique for the ionization of a hydrogen atom in applied parallel electric and magnetic fields. Using fundamental theories of phase space geometry, we also show how to generate nontrivial symbolic dynamics for acquiring periodic orbits in physical systems. A detailed analysis of heteroclinic tangles and how they relate to bifurcations in periodic orbits is also presented.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143970481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A note on the coexistence of infinitely many attractors. 关于无穷多个吸引子共存的注解。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0272999

Xu Zhang, Mingtao Chen, Ran Zhang, Guanrong Chen

引用次数: 0

Excitable response of a noisy adaptive network of spiking lasers. 尖峰激光噪声自适应网络的可激响应。

IF 2.7 2区数学

Chaos Pub Date : 2025-05-01 DOI: 10.1063/5.0252964

S Barland, O D'Huys, R Veltz

引用次数: 0

Hamiltonian chaos for one particle with two waves: Self-consistent dynamics. 具有两波的一粒子的哈密顿混沌：自洽动力学。