IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0324154

Zehua Si, Takayuki Ito

{"title":"Adaptive conformity promotes cooperation within structured populations.","authors":"Zehua Si, Takayuki Ito","doi":"10.1063/5.0324154","DOIUrl":"https://doi.org/10.1063/5.0324154","url":null,"abstract":"From an evolutionary perspective, the pursuit of individual payoff maximization is a widespread behavioral tendency. However, human decision-making is not solely driven by payoffs. Under conditions of uncertainty, risk aversion, and social pressure, individuals often abandon short-term optimal choices and instead conform to locally prevailing behaviors. Along this line, previous studies have investigated how conformity-driven influences the evolution of cooperation in social dilemmas by shaping network reciprocity. Nevertheless, most of these studies treat conformity as a static individual trait, which limits their ability to capture the fact that individuals in real societies flexibly adjust their conformity tendency in response to changing environments. Motivated by this perspective, we propose an adaptive conformity model and examine its impact on the evolution of cooperation in social dilemmas. In this model, individuals dynamically update their conformity tendency based on comparisons between local and global payoffs, with the updating process further modulated by a satisfaction threshold factor and memory length. Through systematic simulations across multiple types of social dilemmas and network topologies, we find that, compared with static conformity models, the adaptive conformity mechanism significantly expands the parameter region in which cooperation can emerge and persist. Specifically, the satisfaction threshold factor exerts a pronounced nonlinear effect on cooperation, whereas longer memory lengths generally suppress the emergence of cooperation. Importantly, even under more severe social dilemma conditions and highly heterogeneous network structures, the proposed model maintains a robust cooperation-promoting effect. These results suggest that adaptive conformity may provide a viable pathway toward mitigating social dilemmas.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147431084","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

Expressed and private opinion dynamics in signed networks based on path-dependence framework. 基于路径依赖框架的签名网络中表达和私人意见动态。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0322595

Yutong Christina Wang, Yuzhi Kong, Hongfeng Hu, Zixi Wang, Xiaoqun Wu

{"title":"Expressed and private opinion dynamics in signed networks based on path-dependence framework.","authors":"Yutong Christina Wang, Yuzhi Kong, Hongfeng Hu, Zixi Wang, Xiaoqun Wu","doi":"10.1063/5.0322595","DOIUrl":"https://doi.org/10.1063/5.0322595","url":null,"abstract":"Opinion evolution in social networks represents a complex dynamical process, particularly when accounting for the interplay between expressed and private opinions-a dynamic that captures the tension between social conformity and individual authenticity. In this paper, we examine the evolution of these two opinion types in signed networks using the expressed and private opinion (EPO) model, in which each individual carries distinct expressed and private opinions. By applying the lifting technique to the EPO model, we rigorously address the influence of negative edges, while the path-dependence theory is employed to model transitions between consecutive topics. Through analytical study, we derive sufficient conditions to eliminate discrepancies between expressed and private opinions across a sequence of topics, ensuring convergence to zero consensus, bipartite consensus, or bounded opinion stability. Notably, iterative topic discussions lead to asymptotic alignment between private and expressed opinions, with all trajectories confined within a well-defined range. Furthermore, for structurally unbalanced networks, we establish a sufficient condition guaranteeing bipartite consensus. Numerical simulations validate all theoretical findings.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147455564","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

Kernel detrended fluctuation analysis: A nonlinear, multivariate method for detecting long-range persistence. 核去趋势波动分析：一种非线性、多变量的方法来检测长期持久性。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0316179

Tristan K E Williams, Homer Durand, Tobias Braun, Francesco Martinuzzi, David Montero, Miguel D Mahecha, Gustau Camps-Valls

{"title":"Kernel detrended fluctuation analysis: A nonlinear, multivariate method for detecting long-range persistence.","authors":"Tristan K E Williams, Homer Durand, Tobias Braun, Francesco Martinuzzi, David Montero, Miguel D Mahecha, Gustau Camps-Valls","doi":"10.1063/5.0316179","DOIUrl":"https://doi.org/10.1063/5.0316179","url":null,"abstract":"We introduce Kernel Detrended Fluctuation Analysis (kDFA), a multivariate, nonlinear generalization of detrended fluctuation analysis for quantifying long-range persistence in complex systems. We show that kDFA generalizes the traditional variance-based fluctuation functional by replacing it with a kernel cross-covariance-based measure. This formulation connects the estimator to the Hilbert-Schmidt norm of the covariance operator in the reproducing kernel Hilbert space. This allows persistence to be inferred from linear to strongly nonlinear regimes via kernel learning. We showcase kDFA in synthetic and real experiments. On synthetic data, kDFA accurately retrieves Hurst exponents and generalizes the standard DFA to nonlinear cases. Comparisons of the Lorenz systems (both L63 and L96) against iterated amplitude-adjusted Fourier transform surrogates reveal genuine nonlinear persistence beyond linear autocorrelation. Applied to ecosystems, kDFA uncovers robust, long-term coupling between vegetation activity and its drivers across European vegetation sites, and detects patterns in this coupling relative to the long-term vegetation trend. kDFA, thus, provides a scalable, theory-grounded tool to uncover hidden multivariate memory in natural and engineered systems.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147472722","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

Stable and efficient learning of degenerate stochastic differential equation in neural networks. 神经网络退化随机微分方程的稳定高效学习。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0301167

Zhiding Wang, Ming Yi, Ting Gao, Xiaoli Chen

{"title":"Stable and efficient learning of degenerate stochastic differential equation in neural networks.","authors":"Zhiding Wang, Ming Yi, Ting Gao, Xiaoli Chen","doi":"10.1063/5.0301167","DOIUrl":"https://doi.org/10.1063/5.0301167","url":null,"abstract":"Stochastic differential equations are fundamental for modeling complex dynamic systems subject to random noise. However, learning stochastic dynamics from empirical data remains challenging, particularly under degenerate noise conditions where the diffusion matrix is irreversible. Traditional approaches often suffer from numerical instability and prohibitive computational costs in such scenarios. To address these limitations, we propose three novel algorithms tailored for efficient and stable learning of SDEs with degenerate diffusion. Algorithm I integrates numerical techniques from second-order stochastic differential equation (SDE) solvers into a specialized learning framework, targeting the special case of a two-dimensional degenerate stochastic equation. This approach improves computational efficiency by taking advantage of the properties of the physical system. Algorithm II introduces a novel loss function that combines mean squared error and maximum likelihood estimation, specifically designed for systems with degenerate diffusion matrices, improving robustness by explicitly accounting for noise structure in the optimization process. Algorithm III incorporates a stabilizing auxiliary noise mechanism during training, which mitigates gradient instability without sacrificing convergence guarantees. Extensive numerical experiments demonstrate that the proposed methods significantly outperform conventional maximum likelihood estimation in terms of training stability, faster convergence, and higher accuracy. These advances enable reliable modeling of high-dimensional stochastic systems and offer promising tools for neural network learning tasks requiring robust noise adaptation.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147343446","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

Distinct roles of AMPA, NMDA, and GABA kinetics in shaping macroscopic cortical dynamics. AMPA， NMDA和GABA动力学在形成宏观皮质动力学中的不同作用。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0314661

Hongsheng Deng, Xinkun Zhang, Hongjie Bi, Xiyun Zhang

{"title":"Distinct roles of AMPA, NMDA, and GABA kinetics in shaping macroscopic cortical dynamics.","authors":"Hongsheng Deng, Xinkun Zhang, Hongjie Bi, Xiyun Zhang","doi":"10.1063/5.0314661","DOIUrl":"10.1063/5.0314661","url":null,"abstract":"The balance between excitation and inhibition (E-I balance) regulates transitions between asynchronous irregular firing and coherent oscillations in cortical networks; yet, the specific contributions of distinct synaptic timescales remain poorly understood. While excitatory transmission is mediated by both fast α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and slow N-methyl-D-aspartate (NMDA) receptors, most theoretical models lump these into a single effective conductance, obscuring their distinct roles in shaping network dynamics. Here, we investigate this problem using a sparsely connected network of quadratic integrate-and-fire neurons incorporating physiologically realistic AMPA, NMDA, and Gamma-aminobutyric acid (GABA) kinetics. By deriving an exact low-dimensional mean-field reduction, we systematically explore the bifurcation structure of the system. We find that shortening the NMDA decay time can lead to transitions between foci and limit cycles, and abrupt alpha-to-gamma frequency jumps reminiscent of epileptic transitions. Conversely, prolonging NMDA or AMPA decay times stabilizes low-rate asynchronous irregular firing activity through enhanced shunting effects, while GABAergic decay kinetics exert only marginal influence in the thermodynamic limit. Furthermore, increasing external drive suppresses oscillations, shifting the network toward the high-rate asynchronous regime associated with heightened arousal. These results demonstrate that glutamatergic receptor kinetics are critical control parameters for E-I balance, providing a mechanistic framework for understanding how synaptic anomalies drive pathological rhythmopathies, such as epilepsy and providing insights into the maintenance of cognitive states.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147364063","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

Time-delay induced oscillations in tumor-immune dynamics in physics laboratory: Theory and electronic experiment. 物理实验室肿瘤免疫动力学中的延时振荡：理论与电子实验。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0302264

Debabrata Biswas

{"title":"Time-delay induced oscillations in tumor-immune dynamics in physics laboratory: Theory and electronic experiment.","authors":"Debabrata Biswas","doi":"10.1063/5.0302264","DOIUrl":"10.1063/5.0302264","url":null,"abstract":"We present a comprehensive study of a tumor-immune interaction model with delayed immune activation, combining analytical, numerical, and experimental approaches. A central feature of our formulation is the use of a generalized Hill function for immune activation, where the exponent m introduces tunable cooperativity. This generalization extends beyond conventional Michaelis-Menten or fixed-saturation forms and captures a wider range of nonlinear immune responses. On the analytical side, we derive explicit conditions for transcritical and Hopf bifurcations, clarifying the roles of key biological parameters and the immune response delay in shaping tumor dynamics. Numerically, we investigate the time-series, phase-plane plots, and both single- and two-parameter bifurcation scenarios with respect to the delay and other system parameters that confirmed the observed transitions are in excellent agreement with the analytical predictions. Most importantly, we implement the delayed tumor-immune model in an analog electronic circuit by reformulating the Hill activation function in terms of hyperbolic tangents, enabling direct laboratory exploration of the system. Experimental investigations reveal steady-state and oscillatory behaviors, dependent on time delay, that closely match the numerical simulations, despite the unavoidable real-world effects such as parameter mismatch, noise, and fluctuations. To the best of our knowledge, this is the first realization of a time-delayed tumor-immune model in hardware in the physics laboratory. This provides a novel bridge between mathematical theory, numerical analysis, and experimental validation and opens new directions for probing tumor dormancy, immune oscillations, and relapse under controlled physical conditions.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"36 3","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147324941","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

The constructive role of random noise in sequential dynamics. 随机噪声在序列动力学中的建设性作用。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0320490

Irina Bashkirtseva, Lev Ryashko

引用次数: 0

Enhanced stability and root detection in a derivative-free Steffensen algorithm for nonlinear dynamical systems. 非线性动力系统的无导数Steffensen算法的增强稳定性和根检测。

IF 3.2 2区数学

Chaos Pub Date : 2026-03-01 DOI: 10.1063/5.0295235

Alexandre Wagemakers, Vipul Periwal

引用次数: 0

Noise-induced decoherence-free zones for anyons. 任意子的噪声诱导无退相干区。