IF 2.7 2区数学

Chaos Pub Date : 2024-10-01 DOI: 10.1063/5.0225731

Yongwang Gong, Michael Small

{"title":"Misinformation spreading on activity-driven networks with heterogeneous spreading rates.","authors":"Yongwang Gong, Michael Small","doi":"10.1063/5.0225731","DOIUrl":"https://doi.org/10.1063/5.0225731","url":null,"abstract":"The spread of misinformation on social media is inextricably related to each user's forwarding habits. In this paper, given that users have heterogeneous forwarding probabilities to their neighbors with varied relationships when they receive misinformation, we present a novel ignorant-spreader-refractory (ISR) spreading model with heterogeneous spreading rates on activity-driven networks with various types of links that encode these differential relationships. More exactly, in this model, the same type of links has an identical spreading rate, while different types of links have distinct ones. Using a mean-field approach and Monte Carlo simulations, we investigate how the heterogeneity of spreading rates affects the outbreak threshold and final prevalence of misinformation. It is demonstrated that the heterogeneity of spreading rates has no effect on the threshold when the type of link follows a uniform distribution. However, it has a significant impact on the threshold for non-uniform distributions. For example, the heterogeneity of spreading rates increases the threshold for normal distribution while it lowers the threshold for an exponent distribution. In comparison to the situation of a homogeneous spreading rate, whether the heterogeneity of spreading rates improves or decreases the final prevalence of misinformation is also determined by the distributions of the type of links.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142342592","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

Mpox outbreak: Time series analysis with multifractal and deep learning network. Mpox 爆发：利用多分形和深度学习网络进行时间序列分析。

IF 2.7 2区数学

Chaos Pub Date : 2024-10-01 DOI: 10.1063/5.0236082

T M C Priyanka, A Gowrisankar, Santo Banerjee

引用次数: 0

Parameter inference from a non-stationary unknown process. 非稳态未知过程的参数推断。

IF 2.7 2区数学

Chaos Pub Date : 2024-10-01 DOI: 10.1063/5.0228236

Kieran S Owens, Ben D Fulcher

{"title":"Parameter inference from a non-stationary unknown process.","authors":"Kieran S Owens, Ben D Fulcher","doi":"10.1063/5.0228236","DOIUrl":"https://doi.org/10.1063/5.0228236","url":null,"abstract":"Non-stationary systems are found throughout the world, from climate patterns under the influence of variation in carbon dioxide concentration to brain dynamics driven by ascending neuromodulation. Accordingly, there is a need for methods to analyze non-stationary processes, and yet, most time-series analysis methods that are used in practice on important problems across science and industry make the simplifying assumption of stationarity. One important problem in the analysis of non-stationary systems is the problem class that we refer to as parameter inference from a non-stationary unknown process (PINUP). Given an observed time series, this involves inferring the parameters that drive non-stationarity of the time series, without requiring knowledge or inference of a mathematical model of the underlying system. Here, we review and unify a diverse literature of algorithms for PINUP. We formulate the problem and categorize the various algorithmic contributions into those based on (1) dimension reduction, (2) statistical time-series features, (3) prediction error, (4) phase-space partitioning, (5) recurrence plots, and (6) Bayesian inference. This synthesis will allow researchers to identify gaps in the literature and will enable systematic comparisons of different methods. We also demonstrate that the most common systems that existing methods are tested on-notably, the non-stationary Lorenz process and logistic map-are surprisingly easy to perform well on using simple statistical features like windowed mean and variance, undermining the practice of using good performance on these systems as evidence of algorithmic performance. We then identify more challenging problems that many existing methods perform poorly on and which can be used to drive methodological advances in the field. Our results unify disjoint scientific contributions to analyzing the non-stationary systems and suggest new directions for progress on the PINUP problem and the broader study of non-stationary phenomena.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544064","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

Epidemic spreading on mixing group with face-to-face interaction. 在面对面互动的混合群体中传播流行病。

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0222847

Wenbin Gu, Wenjie Li, Feng Gao, Sheng Su, Zengping Zhang, Xiaoyang Liu, Wei Wang

{"title":"Epidemic spreading on mixing group with face-to-face interaction.","authors":"Wenbin Gu, Wenjie Li, Feng Gao, Sheng Su, Zengping Zhang, Xiaoyang Liu, Wei Wang","doi":"10.1063/5.0222847","DOIUrl":"https://doi.org/10.1063/5.0222847","url":null,"abstract":"The mixing groups gathered in the enclosed space form a complex contact network due to face-to-face interaction, which affects the status and role of different groups in social communication. The intricacies of epidemic spreading in mixing groups are intrinsically complicated. Multiple interactions and transmission add to the difficulties of understanding and forecasting the spread of infectious diseases in mixing groups. Despite the critical relevance of face-to-face interactions in real-world situations, there is a significant lack of comprehensive study addressing the unique issues of mixed groups, particularly those with complex face-to-face interactions. We introduce a novel model employing an agent-based approach to elucidate the nuances of face-to-face interactions within mixing groups. In this paper, we apply a susceptible-infected-susceptible process to mixing groups and integrate a temporal network within a specified time window to distinguish between individual movement patterns and epidemic spreading dynamics. Our findings highlight the significant impact of both the relative size of mixing groups and the groups' mixing patterns on the trajectory of disease spread within the mixing groups. When group sizes differ significantly, high inter-group contact preference limits disease spread. However, if the minority reduces their intra-group preferences while the majority maintains high inter-group contact, disease spread increases. In balanced group sizes, high intra-group contact preferences can limit transmission, but asymmetrically reducing any group's intra-group preference can lead to increased spread.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131985","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

Investigation of transient extreme events in a mutually coupled star network of theoretical Brusselator system. 布鲁塞尔理论系统相互耦合星形网络中瞬态极端事件的研究。

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0232021

S V Manivelan, S Sabarathinam, K Thamilmaran, I Manimehan

引用次数: 0

Influence of sinusoidal forcing on the master FitzHugh-Nagumo neuron model and global dynamics of a unidirectionally coupled two-neuron system. 正弦强迫对单向耦合双神经元系统的 FitzHugh-Nagumo 主神经元模型和全局动力学的影响

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0219640

Nívea D Bosco, Paulo C Rech, Marcus W Beims, Cesar Manchein

{"title":"Influence of sinusoidal forcing on the master FitzHugh-Nagumo neuron model and global dynamics of a unidirectionally coupled two-neuron system.","authors":"Nívea D Bosco, Paulo C Rech, Marcus W Beims, Cesar Manchein","doi":"10.1063/5.0219640","DOIUrl":"https://doi.org/10.1063/5.0219640","url":null,"abstract":"In this paper, we investigate a seven-parameter, five-dimensional dynamical system, specifically a unidirectional coupling of two FitzHugh-Nagumo neuron models, with one neuron being sinusoidally driven. This master-slave configuration features neuron N1 as the master, subjected to an external sinusoidal electrical current, and neuron N2 as the slave, interacting with N1 through an electrical force. We report numerical results for three distinct scenarios where N1 operates in (i) periodic, (ii) quasiperiodic, and (iii) chaotic regimes. The primary objective is to explore how the dynamics of the master neuron N1 influence the coupled system's behavior. To achieve this, we generated cross sections of the seven-dimensional parameter space, known as parameter planes. Our findings reveal that in the periodic regime of N1, the coupled system exhibits period-adding sequences of Arnold tongue-like structures in the parameter planes. Furthermore, regions of multistability can also be identified in these parameter planes of the coupled system. In the quasiperiodic regime, regions of periodic motion are absent, with only regions of quasiperiodic and chaotic dynamics present. In the chaotic regime of N1, the parameter planes display regions of chaos, hyperchaos, and transient hyperchaos.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281131","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

Symbolic extended dynamic mode decomposition. 符号扩展动态模式分解

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0223615

Connor Kennedy, John Kaushagen, Hong-Kun Zhang

引用次数: 0

Two coupled population growth models driven by Gaussian white noises. 由高斯白噪声驱动的两个耦合人口增长模型

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0226621

Kwok Sau Fa

引用次数: 0

Self-organization in computation and chemistry: Return to AlChemy. 计算和化学中的自组织：回到 AlChemy。

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0207358

Cole Mathis, Devansh Patel, Westley Weimer, Stephanie Forrest

{"title":"Self-organization in computation and chemistry: Return to AlChemy.","authors":"Cole Mathis, Devansh Patel, Westley Weimer, Stephanie Forrest","doi":"10.1063/5.0207358","DOIUrl":"https://doi.org/10.1063/5.0207358","url":null,"abstract":"How do complex adaptive systems, such as life, emerge from simple constituent parts? In the 1990s, Walter Fontana and Leo Buss proposed a novel modeling approach to this question, based on a formal model of computation known as the λ calculus. The model demonstrated how simple rules, embedded in a combinatorially large space of possibilities, could yield complex, dynamically stable organizations, reminiscent of biochemical reaction networks. Here, we revisit this classic model, called AlChemy, which has been understudied over the past 30 years. We reproduce the original results and study the robustness of those results using the greater computing resources available today. Our analysis reveals several unanticipated features of the system, demonstrating a surprising mix of dynamical robustness and fragility. Specifically, we find that complex, stable organizations emerge more frequently than previously expected, that these organizations are robust against collapse into trivial fixed points, but that these stable organizations cannot be easily combined into higher order entities. We also study the role played by the random generators used in the model, characterizing the initial distribution of objects produced by two random expression generators, and their consequences on the results. Finally, we provide a constructive proof that shows how an extension of the model, based on the typed λ calculus, could simulate transitions between arbitrary states in any possible chemical reaction network, thus indicating a concrete connection between AlChemy and chemical reaction networks. We conclude with a discussion of possible applications of AlChemy to self-organization in modern programming languages and quantitative approaches to the origin of life.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142342586","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 heterogeneous multilayer networks. 基于动机的异构多层网络链接预测。

IF 2.7 2区数学

Chaos Pub Date : 2024-09-01 DOI: 10.1063/5.0218981

Yafang Liu, Jianlin Zhou, An Zeng, Ying Fan, Zengru Di

{"title":"Motifs-based link prediction for heterogeneous multilayer networks.","authors":"Yafang Liu, Jianlin Zhou, An Zeng, Ying Fan, Zengru Di","doi":"10.1063/5.0218981","DOIUrl":"https://doi.org/10.1063/5.0218981","url":null,"abstract":"Link prediction has a wide range of applications in the study of complex networks, and the current research on link prediction based on single-layer networks has achieved fruitful results, while link prediction methods for multilayer networks have to be further developed. Existing research on link prediction for multilayer networks mainly focuses on multiplexed networks with homogeneous nodes and heterogeneous edges, while there are relatively few studies on general multilayer networks with heterogeneous nodes and edges. In this context, this paper proposes a method for heterogeneous multilayer networks based on motifs for link prediction. The method considers not only the effect of heterogeneity of edges on network links but also the effect of heterogeneous and homogeneous nodes on the existence of links between nodes. In addition, we use the role function of nodes to measure the contribution of nodes to form the motifs with links in different layers of the network, thus enabling the prediction of intra- and inter-layer links on heterogeneous multilayer networks. Finally, we apply the method to several empirical networks and find that our method has better link prediction performance than several other link prediction methods on multilayer networks.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142139405","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

Chaos最新文献