IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0265735

Enzo Marinari, Gleb Oshanin

引用次数: 0

Magnetohydrodynamical thermoresistive instability and the Claws of chaos. 磁流体动力学热阻不稳定性和混沌之爪。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0245096

Raphaël Hardy, Paul Charbonneau, Andrew Cumming

{"title":"Magnetohydrodynamical thermoresistive instability and the Claws of chaos.","authors":"Raphaël Hardy, Paul Charbonneau, Andrew Cumming","doi":"10.1063/5.0245096","DOIUrl":"https://doi.org/10.1063/5.0245096","url":null,"abstract":"Exoplanets known as hot Jupiters offer a unique testbed for the study of the magnetohydrodynamical thermoresistive instability. This instability arises when ohmic heating enhances the electrical conductivity in a positive feedback loop leading to a thermal runaway. The heat equation, coupled with the momentum and magnetic induction equations form a strongly coupled non-linear third order system, from which chaotic behavior emerges naturally. We first illustrate and discuss the dynamical impact of thermoresistive instability in a representative solution in which the instability recurs in the form of periodic bursts. We then focus on the physical parameter regime in which aperiodic behavior occurs and demonstrate its chaotic nature. The chaotic regime turns out to be restricted to a relatively narrow region of parameter space within the domain where the thermoresistive instability occurs, on either side of which different classes of non-chaotic periodic behavior are observed. Through a linear stability analysis, we showcase how chaos appears at the transition between these dynamically distinct oscillatory regimes, which may be understood as overdamped and damped nonlinear oscillations.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144316002","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

Topological data analysis approach to time series and shape analysis of dynamical system. 拓扑数据分析方法的时间序列和形状分析的动力系统。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0268340

W Hussain Shah, S Rafia Fatima, G Huerta-Cuellar, J H García-López, C G Mata Ramirez, R Jaimes-Reátegui

{"title":"Topological data analysis approach to time series and shape analysis of dynamical system.","authors":"W Hussain Shah, S Rafia Fatima, G Huerta-Cuellar, J H García-López, C G Mata Ramirez, R Jaimes-Reátegui","doi":"10.1063/5.0268340","DOIUrl":"https://doi.org/10.1063/5.0268340","url":null,"abstract":"In a dynamical system, the time series and phase space play vital roles, and we applied topological data analysis to these characteristics. More precisely, we consider the well-known Rössler-like attractor to analyze time-series and phase-space images. We studied persistent homology representations directly from the time series of the system to obtain point cloud data. In our approach, we converted the time series to a point cloud and computed homology using the Rips complex. This enabled us to measure the topological features of the system behavior. We also applied cubical homology to phase-space images for the first time, a novel contribution that represents an image-based approach to analyze phase portraits. This article provides a review of the topological data analysis of time series using examples with the Python function. Finally, we computed topological machine learning features, such as persistent landscapes, persistence images, and Betti curves. These features enable the automated analysis and classification of dynamical behaviors and, hence, connect topological data analysis with machine learning. This study is new in that it presents a comprehensive topological data analysis pipeline tailored to dynamical systems. The goal is to make these approaches accessible and usable for nonlinear dynamics to analyze their temporal series and phase portraits.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144316005","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 chaotic time-averages from few periodic or non-periodic orbits. 从几个周期或非周期轨道计算混沌时间平均。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0264212

Joshua L Pughe-Sanford, Sam Quinn, Teodor Balabanski, Roman O Grigoriev

引用次数: 0

Fine structure of phase diagram for social impact theory. 社会影响理论相图的精细结构。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0272091

Krzysztof Malarz, Maciej Wołoszyn

{"title":"Fine structure of phase diagram for social impact theory.","authors":"Krzysztof Malarz, Maciej Wołoszyn","doi":"10.1063/5.0272091","DOIUrl":"https://doi.org/10.1063/5.0272091","url":null,"abstract":"In this paper, the social impact theory introduced by Latané is reconsidered. A fully differentiated society is considered; that is, initially every actor has their own opinion. The equivalent of Muller's ratchet guards that-even for the non-deterministic case (with a positive social temperature)-any opinion once removed from the opinion space does not appear again. With computer simulation, we construct the phase diagram for the Latané model based on the number of surviving opinions after various evolution times. The phase diagram is constructed on the two-dimensional plane of model control parameters responsible for the effective range of interaction among actors and the social temperature. Introducing Muller's ratchet-like mechanism gives a non-zero chance for any opinion to be removed from the system. We believe that in such a case, for any positive temperature, ultimately, a consensus is reached. However, even for a moderate system size, the time to reach a consensus is very long. In contrast, for the deterministic case (without social temperature), the system may be frozen with clusters of actors having several different opinions or even reach the cycle limit (with blinking structures).","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198349","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

Motifs-based link prediction for multiplexed networks. 基于motif的多路网络链路预测。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0269197

Yafang Liu, Aiwen Li, Jiaying Yang, Jianlin Zhou, An Zeng, Ying Fan, Zengru Di

{"title":"Motifs-based link prediction for multiplexed networks.","authors":"Yafang Liu, Aiwen Li, Jiaying Yang, Jianlin Zhou, An Zeng, Ying Fan, Zengru Di","doi":"10.1063/5.0269197","DOIUrl":"https://doi.org/10.1063/5.0269197","url":null,"abstract":"Link prediction on multiplexed networks has wide applications in various fields such as social networks and recommendation systems. Some algorithms have been proposed to solve link prediction on multiplexed networks, which often rely on single-layer node characteristics, inter-layer similarity, and layer fusion. In this paper, we attempt to address this issue from the perspective of the local structure that can be constructed by two nodes. We propose a motifs-based naïve Bayes model for link prediction in multiplex networks, which considers the number of motif predictors and the role of nodes in the motif composition of different network layers. We apply this method to multiple empirical networks, and the results show that our method not only outperforms other existing algorithms in link prediction but also has high prediction accuracy. In addition, the role functions of the nodes included in the model can, indeed, help improve the performance of link prediction methods based solely on motifs. The motifs-based link prediction method effectively leverages the heterogeneity of edges and provides ideas for a more in-depth study of multiplexed networks.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198353","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

Robust oscillatory dynamics in a mixed population of excitable and self-oscillatory Izhikevich neurons: Influence of second-order linear and nonlinear interactions. 可兴奋和自振荡Izhikevich神经元混合种群的鲁棒振荡动力学：二阶线性和非线性相互作用的影响。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0274541

Soorya Pp, Biswambhar Rakshit, Kazuyuki Aihara

引用次数: 0

A bounded confidence model to predict how group work affects student math anxiety. 预测小组作业如何影响学生数学焦虑的有限置信模型。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0276020

Matthew S Mizuhara, Katherine Toms, Maya Williams

引用次数: 0

Power law distribution and multi-scale analysis in Earth sciences, finance, and other fields: Some guidelines to parameter estimation. 地球科学、金融和其他领域的幂律分布和多尺度分析：参数估计的一些准则。