Chaos最新文献

{"title":"Diffusing diffusivity model of a polymer moving on a spherical surface.","authors":"Xinyi Wu, Daxin Nie, Weihua Deng","doi":"10.1063/5.0251095","DOIUrl":"https://doi.org/10.1063/5.0251095","url":null,"abstract":"<p><p>The movement of a polymer is modeled by Brownian motion accompanied with a fluctuating diffusion coefficient when the polymer is in contact with a chemostatted monomer bath triggering the chain polymerization, which is called a diffusing diffusivity (DD) model. In this paper, we extend the DD model from three dimensional Euclidean space to a two dimensional spherical surface. The DD model on the spherical surface is described by a coupling Langevin system in the directions of longitude and latitude, while the diffusion coefficient is characterized by the birth and death chain. Then, the Fokker-Planck and Feynman-Kac equations for the DD model on the spherical surface, respectively, governing the probability density functions (PDFs) of the two statistical observables, position and functional, are derived. Finally, we use two ways to calculate the PDFs of some statistical observables, i.e., applying a Monte Carlo method to simulate the DD model and a spectral method to solve the Fokker-Planck and Feynman-Kac equations. In fact, the unification of the numerical results of the two ways also confirms the correctness of the built equations.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572021","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}

{"title":"Heterogeneous K-core percolation on hypergraphs.","authors":"Dandan Zhao, Wenjia Xi, Bo Zhang, Cheng Qian, Yifan Zhao, Shenhong Li, Hao Peng, Wei Wang","doi":"10.1063/5.0245871","DOIUrl":"10.1063/5.0245871","url":null,"abstract":"<p><p>In complex systems, there are pairwise and multiple interactions among elements, which can be described as hypergraphs. K-core percolation is widely utilized in the investigation of the robustness of systems subject to random or targeted attacks. However, the robustness of nodes usually correlates with their characteristics, such as degree, and exhibits heterogeneity while lacking a theoretical study on the K-core percolation on a hypergraph. To this end, we constructed a hyperedge K-core percolation model that introduces heterogeneity parameters to divide the active hyperedges into two parts, where hyperedges are inactive unless they have a certain number of active nodes. In the stage of pruning process, when the number of active nodes contained in a hyperedge is less than its set value, it will be pruned, which will result in the deletion of other hyperedges and ultimately trigger cascading failures. We studied the magnitude of the giant connected component and the percolation threshold of the model by mapping a random hypergraph to a factor graph. Subsequently, we conducted a large number of simulation experiments, and the theoretical values matched well with the simulated values. The heterogeneity parameters of the proposed model have a significant impact on the magnitude of the giant connected component and the type of phase transition in the network. We found that decreasing the value of heterogeneity parameters renders the network more fragile, while increasing the value of heterogeneity parameters makes it more resilient under random attacks. Meanwhile, as the heterogeneity parameter decreases to 0, it may cause a change in the nature of network phase transition, and the network shows a hybrid transition.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717801","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}

{"title":"Introduction to Focus Issue: Data-driven models and analysis of complex systems.","authors":"Johann H Martínez, Klaus Lehnertz, Nicolás Rubido","doi":"10.1063/5.0263794","DOIUrl":"https://doi.org/10.1063/5.0263794","url":null,"abstract":"<p><p>This Focus Issue highlights recent advances in the study of complex systems, with a particular emphasis on data-driven research. Our editorial explores a diverse array of topics, including financial markets, electricity pricing, power grids, lasers, the Earth's climate, hydrology, neuronal assemblies and the brain, biomedicine, complex networks, real-world hypergraphs, animal behavior, and social media. This diversity underscores the broad applicability of complex systems research. Here, we summarize the 47 published works under this Focus Issue, which employ state-of-the-art or novel methodologies in machine learning, higher-order correlations, control theory, embeddings, information theory, symmetry analysis, extreme event modeling, time series analysis, fractal techniques, Markov chains, and persistent homology, to name a few. These methods have substantially enhanced our understanding of the intricate dynamics of complex systems. Furthermore, the published works demonstrate the potential of data-driven approaches to revolutionize the study of complex systems, paving the way for future research directions and breakthroughs at the intersection of complexity science and the digital era of data.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630222","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}

{"title":"Negative public opinion and minority-driven social change in hypergraphs.","authors":"Lulu Gong, Changwei Huang, Luoluo Jiang","doi":"10.1063/5.0257900","DOIUrl":"https://doi.org/10.1063/5.0257900","url":null,"abstract":"<p><p>The phenomenon where a committed minority overturns established social norms, frequently witnessed in revolutions and elections, has drawn extensive attention as it powerfully showcases the profound influence of strong personal convictions. In order to unravel the underlying mechanisms of the crucial role of public opinion within the dynamic process where a committed minority can leverage negative public opinion to challenge the status and even overturn established norms when a critical threshold is reached, we investigated the effects of negative public opinion by integrating it into the well-established traditional naming game model. It was found that there exists an optimal range of negative public opinion influence, which facilitates the minority's ability to gain power and achieve social consensus. Notably, our results show that a smaller critical mass of committed individuals could trigger consensus behavior under this mechanism. The introduction of negative public influence into opinion propagation has yielded intriguing results, offering a new perspective on expanding consensus formation in opinion dynamics, particularly in diverse environments.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630224","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}

{"title":"Exploration of soliton solutions and chaos analysis in thin-film ferroelectric materials.","authors":"Peng Guo, Guangyang Wang, Jianming Qi","doi":"10.1063/5.0258130","DOIUrl":"https://doi.org/10.1063/5.0258130","url":null,"abstract":"<p><p>This research comprehensively examines the Thin-Film Ferroelectric Material Equation (TFFEME). TFFEME is vital in ferroelectric materials, offering a theoretical means to understand and predict ferroelectric thin-film behavior. These films are applied in non-volatile memories, sensors, and actuators, and TFFEME aids in accurately depicting internal physical processes for device performance optimization. By applying the beta fractional derivative with the modified (G'G2)-expansion method, diverse soliton solutions were derived. This not only broadens our understanding of TFFEME's solution framework but also provides insights into polarization dynamics and chaos analysis in ferroelectric thin films, applicable for enhancing ferroelectric-based device performance, like faster switching and lower power in non-volatile memories. The study also explored how physical parameters and fractional derivative forms affect solutions, crucial for soliton propagation. This analysis serves as a basis for improving material properties and innovating device designs, such as enhancing sensor sensitivity. Moreover, TFFEME was transformed into a Hamiltonian structure to study its planar dynamics, which is essential for predicting the device long-term stability. Finally, the barycentric Lagrange interpolation method at Chebyshev nodes provided precise numerical solutions for TFFEME, validating models and guiding experiments for new ferroelectric thin-film applications.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143662967","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}

{"title":"Bifurcation and chaotic dynamics in a spatiotemporal epidemic model with delayed optimal control, stochastic process, and sensitivity analysis.","authors":"Arjun Kumar, Uma S Dubey, Balram Dubey","doi":"10.1063/5.0251992","DOIUrl":"10.1063/5.0251992","url":null,"abstract":"<p><p>This study introduces an epidemic model with a Beddington-DeAngelis-type incidence rate and Holling type II treatment rate. The Beddington-DeAngelis incidence rate is used to evaluate the effectiveness of inhibitory measures implemented by susceptible and infected individuals. Moreover, the choice of Holling type II treatment rate in our model aims to assess the impact of limited treatment facilities in the context of disease outbreaks. First, the well-posed nature of the model is analyzed, and then, we further investigated the local and global stability analysis along with bifurcation of co-dimensions 1 (transcritical, Hopf, saddle-node) and 2 (Bogdanov-Takens, generalized Hopf) for the system. Moreover, we incorporate a time-delayed model to investigate the effect of incubation delay on disease transmission. We provide a rigorous demonstration of the existence of chaos and establish the conditions that lead to chaotic dynamics and chaos control. Additionally, sensitivity analysis is performed using partial rank correlation coefficient and extended Fourier amplitude sensitivity test methods. Furthermore, we delve into optimal control strategies using Pontryagin's maximum principle and assess the influence of delays in state and control parameters on model dynamics. Again, a stochastic epidemic model is formulated and analyzed using a continuous-time Markov chain model for infectious propagation. Analytical estimation of the likelihood of disease extinction and the occurrence of an epidemic is conducted using the branching process approximation. The spatial system presents a comprehensive stability analysis and yielding criteria for Turing instability. Moreover, we have generated the noise-induced pattern to assess the effect of white noise in the populations. Additionally, a case study has been conducted to estimate the model parameters, utilizing COVID-19 data from Poland and HIV/AIDS data from India. Finally, all theoretical results are validated through numerical simulations. This article extensively explores various modeling techniques, like deterministic, stochastic, statistical, pattern formation(noise-induced), model fitting, and other modeling perspectives, highlighting the significance of the inhibitory effects exerted by susceptible and infected populations.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718191","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}

{"title":"Asynchronous hybrid event- and time-triggered control of heterogeneous networks with communication time delays.","authors":"Gaopeng Duan, Xuecheng Yu, Heung Wing Joseph Lee","doi":"10.1063/5.0239417","DOIUrl":"https://doi.org/10.1063/5.0239417","url":null,"abstract":"<p><p>This paper addresses the asynchronous leader-following consensus problem for networked double-integrator systems. In practical engineering contexts, there are three key factors that must be considered significantly: (1) asynchronous hybrid event- and time-triggered control, where asynchrony affects event detection, event-triggered processes, and controller updates; (2) heterogeneous networks, wherein position and velocity information are governed by distinct, independent graphs; and (3) communication time delays arising from limited bandwidth and long-distance transmission. Due to the independence of these heterogeneous networks, edge events related to position and velocity information are defined separately. When an event occurs on an edge, the connected agents sample the corresponding relative state information (position or velocity) and update their controllers accordingly. The paper proposes a control protocol based on these event rules and employs Lyapunov methods to address the leader-following consensus problem. Numerical simulations are provided to validate and illustrate the theoretical findings.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603846","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}

{"title":"Rumor propagation in the framework of evolutionary game analysis.","authors":"Deliang Li, Yi Zhao, Yang Deng, Yifeng Wang","doi":"10.1063/5.0259050","DOIUrl":"https://doi.org/10.1063/5.0259050","url":null,"abstract":"<p><p>With the ubiquity of social networks, rumors spread easily, leading to increasing attention on their dissemination. In this context, the spread of rumors is influenced not only by the content of the information itself but also by the behavior of various actors over social networks. To model such a process, we propose a novel rumor propagation interaction model. This model, for the first time, combines a rumor-spreading model, characterizing the dual impact of media activities on rumor propagation, with a three-party evolutionary game model, exploring the interactions among netizens, media, and the government on social media platforms. To validate the model, we employ a physics-informed neural network to simulate real rumor-spread data from the U.S. Twitter platform. By integrating the estimated parameter set from the rumor-spreading model with the three-party evolutionary game model, we design a new tripartite evolutionary game matrix. This matrix effectively quantifies the government's regulatory efforts, the media's tendency to spread rumors, and the likelihood of netizens participating in rumor diffusion. The experimental results demonstrate that a higher probability of strict government control more effectively curbs the momentum of rumor spread, while a lower probability of media spreading rumors corresponds to an increase in the number of rumor debunkers. Reduced control costs lead to increased government intervention, less media-driven rumor propagation, and more frequent media refutations. In summary, this model demonstrates significant practical value for understanding rumor propagation dynamics.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630226","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}

{"title":"Self-organization of conducting pathways explains complex wave trajectories in procedurally interpolated fibrotic cardiac tissue: A virtual replica study.","authors":"V D Naumov, A P Sinitsyna, I S Semidetnov, S S Bakumenko, A K Berezhnoy, T O Sergeeva, M M Slotvitsky, V A Tsvelaya, K I Agladze","doi":"10.1063/5.0240140","DOIUrl":"https://doi.org/10.1063/5.0240140","url":null,"abstract":"<p><p>In precision cardiology, virtual replicas (VRs) hold promise for predicting arrhythmias by leveraging patient-specific data and biophysics knowledge. A crucial first step is creating VRs of cardiac tissue based on retrospective patient data. However, VRs aim to replicate biopotential conduction directly, whereas only non-invasive methods are feasible for clinical use on real organs and tissues. This discrepancy challenges our understanding of VR applicability limits. This study aims to enhance the mathematical template of VR by developing an in vitro validation complement. We performed a frame-by-frame comparison of in vitro optical mapping of biopotential conduction with VR predictions. Patient-specific self-organized tissue samples from human induced pluripotent stem cell-derived cardiomyocytes (CMs) with diffuse fibrosis were utilized as VR prototypes. High-resolution optical mapping recordings (Δx = 117 ± 4 μm, Δt = 7.69 ms) and immunostaining were used to reproduce fibrotic samples of linear size 7.5 mm. We applied data-driven Bayesian optimization of the Cellular Potts model (CPM) to study wave propagation at the subcellular level. The modified CPM accurately reflected the \"perinatal window\" until the 20th day of differentiation, affecting CMs' self-organization. The percolation threshold of virtual conductive pathways reached 0.26 (0.27 ± 0.03 of CMs in vitro), yielding a spatial correlation of amplitude maps with Pearson's coefficients of 0.83 ± 0.02. As a proof-of-concept, we demonstrated that CPM-enhanced VR could predict wavefront trajectories in optical mapping recordings, showing that approximating fibrosis distribution is crucial for improving VR prediction accuracy.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143662277","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}

{"title":"Training stiff neural ordinary differential equations with explicit exponential integration methods.","authors":"Colby Fronk, Linda Petzold","doi":"10.1063/5.0251475","DOIUrl":"https://doi.org/10.1063/5.0251475","url":null,"abstract":"<p><p>Stiff ordinary differential equations (ODEs) are common in many science and engineering fields, but standard neural ODE approaches struggle to accurately learn these stiff systems, posing a significant barrier to the widespread adoption of neural ODEs. In our earlier work, we addressed this challenge by utilizing single-step implicit methods for solving stiff neural ODEs. While effective, these implicit methods are computationally costly and can be complex to implement. This paper expands on our earlier work by exploring explicit exponential integration methods as a more efficient alternative. We evaluate the potential of these explicit methods to handle stiff dynamics in neural ODEs, aiming to enhance their applicability to a broader range of scientific and engineering problems. We found the integrating factor Euler (IF Euler) method to excel in stability and efficiency. While implicit schemes failed to train the stiff van der Pol oscillator, the IF Euler method succeeded, even with large step sizes. However, IF Euler's first-order accuracy limits its use, leaving the development of higher-order methods for stiff neural ODEs an open research problem.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143699858","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}