{"title":"Inference of couplings between variables of a given system using causal wavelets, causal information, equations reconstruction, and other techniques.","authors":"Sylvain Mangiarotti, Mathis Neuhauser, Ludovic Arnaud, Thao Bach Nguyen, Sébastien Verrier","doi":"10.1063/5.0272112","DOIUrl":"https://doi.org/10.1063/5.0272112","url":null,"abstract":"<p><p>To infer directional couplings from variables is a difficult problem in dynamical systems, especially when its variables are taken from the real world. Many approaches have been developed to infer such couplings directly from observational time series. The objective of the present study is to investigate the capabilities of a set of techniques in test situations where the dynamics are governed by either fully deterministic (ordinary differential) equations or partially deterministic equations (the same ones with a stochastic perturbation added, the deterministic part remaining dominant). The studied system is based on two three-dimensional chaotic subsystems with very different dynamics, but similar structure, considering various couplings between them (none, unidirectional, bidirectional). One system is dissipative, and the other one is conservative. The time evolution produced by their variables is clearly correlated with one system, almost totally decorrelated with the other one. The following techniques, some of which are introduced in this study, are considered: simple/causal correlation, mutual/causal information, Granger causality index, cross/causal wavelet coherence, bivariate global modeling, and equation reconstruction techniques. All the techniques are evaluated based on their ability to detect direct and indirect causal relationships. Most of them prove poorly capable of detecting direct couplings and are not really robust in the contexts with low variable correlation, external weak couplings, and stochastic perturbations. Applied to the current problems, the bivariate modeling and the equation reconstruction techniques, both based on a global modeling technique, appear to be the most effective approaches to infer causality. The detection of weak bidirectional couplings appears particularly challenging under noisy conditions. Causal detection is tested on a set of groundwater level observational time series, revealing deterministic but complex couplings between three sub-basins of the Se San River basin (Central Highlands, Vietnam).</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145307075","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}
Dianela Herrera, Nicolás Ángel, Diego González, Sergio Curilef
{"title":"Monte Carlo optimization for sampling selection in imbalanced data applied to student dropout prediction.","authors":"Dianela Herrera, Nicolás Ángel, Diego González, Sergio Curilef","doi":"10.1063/5.0278602","DOIUrl":"https://doi.org/10.1063/5.0278602","url":null,"abstract":"<p><p>University student completion rates vary among students who initially enroll in academic degrees and professional careers. Student dropout is a widespread global phenomenon that transcends both the type of degree pursued and the university attended. Traditionally, the greatest emphasis in corrective measures has been placed on improving academic performance and, to a lesser extent, on other variables that are overshadowed by the former but are equally impactful. Therefore, the current motivation is to develop an effective machine learning-based tool to identify students at a higher risk of dropping out early after 1-3 years of study. We use a large dataset from the Universidad Católica del Norte to test the methodology. Machine learning specific tools are tested to verify their predictive capability, and their results are discussed to remark on their precise utility. Moreover, we address the class imbalance in the first-year data by implementing an innovative adjustment using the Monte Carlo methodology, improving model performance under imbalanced conditions. Indeed, the technique is mainly relevant to first-year dropout, where the dataset is more anomalous. Nevertheless, a level of improvement is observed in all cases studied. The ultimate goal is to identify at-risk students early to support the timely, effective, and proper implementation of preventive interventions.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145307078","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":"A data-driven framework for Koopman semigroup estimation in stochastic dynamical systems.","authors":"Yuanchao Xu, Kaidi Shao, Isao Ishikawa, Yuka Hashimoto, Nikos Logothetis, Zhongwei Shen","doi":"10.1063/5.0283640","DOIUrl":"https://doi.org/10.1063/5.0283640","url":null,"abstract":"<p><p>We present Stochastic Dynamic Mode Decomposition (SDMD), a novel data-driven framework for approximating the Koopman semigroup in stochastic dynamical systems. Unlike existing approaches, SDMD explicitly incorporates sampling time into its formulation to ensure numerical stability and precision in the presence of noise. By directly approximating the Koopman semigroup rather than its generator, SDMD avoids computationally expensive matrix exponential calculation, providing a more practically efficient pathway for analyzing stochastic dynamics. The framework also leverages neural networks for automated basis selection, minimizing manual effort while preserving computational efficiency. We establish SDMD's theoretical foundations through rigorous convergence guarantees across three critical limits in order: large data, infinitesimal sampling time, and increasing dictionary size. Numerical experiments on canonical stochastic systems including oscillatory system, mean-reverting processes, metastable system, and a neural mass model demonstrate SDMD's effectiveness in capturing the spectral properties of the Koopman semigroup, even in systems with complex random behavior.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299012","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}
Krzysztof Gdawiec, Yan G S Dos Santos, Ricardo Fariello
{"title":"Quaternion Julia sets reimagined: The Garodia-Uddin iteration approach.","authors":"Krzysztof Gdawiec, Yan G S Dos Santos, Ricardo Fariello","doi":"10.1063/5.0271064","DOIUrl":"https://doi.org/10.1063/5.0271064","url":null,"abstract":"<p><p>In recent years, significant research has been conducted on using various iteration schemes derived from fixed-point theory to generate Mandelbrot and Julia sets in the complex space. Building on these advancements, this work explores the application of the Garodia-Uddin iteration scheme to construct Julia sets of q↦qk+c in the quaternion space. Specifically, we establish the escape criterion for the Garodia-Uddin orbit and analyze the symmetry of the Julia set for the even values of k. Additionally, we provide and discuss 2D and 3D graphical examples of sets generated from the Garodia-Uddin iteration scheme. Furthermore, we investigate the effect of a key parameter in the proposed approach on the average escape time, non-escaping area index, and fractal dimension for 2D cross sections of quaternion Julia sets of varying degrees. Finally, the Julia sets obtained are compared to the ones which come from the Picard-Mann iteration scheme.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273825","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}
Hang Yu, Lin Deng, Weicheng Fu, Yisen Wang, Liang Huang
{"title":"Thermal rectifiers based on asymmetric van der Waals heteronanotubes.","authors":"Hang Yu, Lin Deng, Weicheng Fu, Yisen Wang, Liang Huang","doi":"10.1063/5.0289192","DOIUrl":"https://doi.org/10.1063/5.0289192","url":null,"abstract":"<p><p>Efficient thermal management at the nanoscale is essential for advanced electronic applications. In this work, we explore the thermal rectification properties of asymmetric van der Waals heteronanotubes, e.g., a single-walled carbon nanotube (CNT) partially coated by a single-walled molybdenum disulfide nanotube (MoS2NT), which have been successfully synthesized in recent experiments. Through extensive molecular dynamics simulations, we demonstrate that these heteronanotubes can effectively function as thermal rectifiers, with rectification ratios surpassing 100% under substantial temperature gradients. The analyses based on the phonon density of states and the velocity autocorrelation function reveal key insights into the underlying mechanisms. In addition to the phonon-spectrum mismatch, the MoS2NT sheath suppresses radial vibrations on the covered CNT segment, leading to a prominent 13 THz standing wave mode at the exposed CNT end under reverse bias, which traps vibrational energy and impedes reverse heat flux. The thermal rectification remains robust across variations in the average temperature, device size, inter-tube spacing, diameter of heteronanotubes, and MoS2NT coverage fraction, underscoring the potential for scalable and fault-tolerant applications. These findings highlight the promise of heteronanotubes in nanoscale thermal management, offering a novel approach for controlling heat flow in advanced electronic devices, thermal diodes, and other nanoscale systems.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336533","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":"Intrinsic dimensionality of Fermi-Pasta-Ulam-Tsingou high-dimensional trajectories through manifold learning: A linear approach.","authors":"Gionni Marchetti","doi":"10.1063/5.0293702","DOIUrl":"https://doi.org/10.1063/5.0293702","url":null,"abstract":"<p><p>A data-driven approach based on unsupervised machine learning is proposed to infer the intrinsic dimensionality of high-dimensional trajectories in the Fermi-Pasta-Ulam-Tsingou (FPUT) model. Principal component analysis is applied to trajectory data accurately computed using a symplectic integrator, comprising ns=4000000 data points from the FPUT β model with N=32 coupled harmonic oscillators. By estimating the intrinsic dimension m∗ using multiple methods (participation ratio, Kaiser rule, and the Kneedle algorithm), it is found that m∗ increases with the model's nonlinearity. Interestingly, in the weakly nonlinear regime (β≲1.1), for trajectories initialized by exciting the first mode (k=1), the participation ratio estimates m∗=2,3, strongly suggesting that quasi-periodic motion on a low-dimensional Riemannian manifold underlies the characteristic energy recurrences observed in the FPUT model.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145285638","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":"From homogeneity to heterogeneity: Topologically reconfigurable multi-cavity attractors in memristive chaotic maps.","authors":"Jin Liu, Kehui Sun, Huihai Wang","doi":"10.1063/5.0283700","DOIUrl":"https://doi.org/10.1063/5.0283700","url":null,"abstract":"<p><p>In recent years, multi-cavity attractors have emerged as a focal point in chaotic dynamics research. However, previous studies have predominantly focused on homogeneous multi-cavity attractors, where all cavities share identical topological structures. While topologically interesting, this homogeneity leads to highly similar statistical characteristics across cavities, potentially posing a threat to its cryptographic applications. To address this limitation, this study proposes a concise chaotic map construction scheme based on discrete memristors. Mathematical analysis reveals that this map exhibits no fixed points and can stably generate hidden attractors. Crucially, by selecting periodic or aperiodic memristive functions, it is possible to construct both homogeneous and heterogeneous multistability or multi-cavity attractors. Furthermore, we demonstrate that the heterogeneous structure breaks the periodic redundancy inherent in its homogeneous counterpart, resulting in a significantly larger and scalable effective key space. This finding quantitatively validates the enhanced security potential of the proposed map in fields, such as information encryption. This research not only expands the conceptual boundaries of multi-cavity attractors in chaotic systems but also presents a promising novel framework for diverse engineering applications.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145238244","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":"Analyzing the relationship between synchronization dynamics in hypernetworks and their single-interaction counterparts.","authors":"Sheida Ansarinasab, Farnaz Ghassemi, Fatemeh Parastesh, Sajad Jafari","doi":"10.1063/5.0301496","DOIUrl":"https://doi.org/10.1063/5.0301496","url":null,"abstract":"<p><p>Hypernetworks provide a proper framework for representing systems in which units interact simultaneously through multiple layers of interactions. Synchronization is a fundamental collective behavior in such systems, yet its stability analysis remains challenging. Studies have often assumed hypernetworks with commuting Laplacians or purely linear interactions, conditions that rarely hold in real-world systems. This paper addresses this gap by investigating hypernetworks with non-commuting Laplacians, where oscillators interact through both linear and nonlinear diffusive coupling functions on random and ring topologies. Because the Master Stability Function (MSF) cannot be decoupled in such systems, direct stability analysis is intractable. To overcome this limitation, we establish a connection between the synchronization dynamics in hypernetworks and those of their derived single-interaction counterparts, enabling qualitative predictions of the MSF structure. Numerical simulations with Lorenz oscillators demonstrate that hypernetworks exhibit intermediate synchronization regions shaped by the dominant coupling function. Additionally, nonlinear interactions enhance synchronizability but increase coupling energy demands. An inverse relationship between pre-synchronization coupling energy and required time to achieve synchronization is consistently observed. These findings provide a systematic framework and offer novel insights for interpreting and predicting the dynamics and stability of synchronization in real-world complex networks with multiple interaction modes.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145354052","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":"Weighted scheduled traffic process with asymptotic fractional dynamics.","authors":"Marcin Magdziarz, Wladyslaw Szczotka","doi":"10.1063/5.0294488","DOIUrl":"https://doi.org/10.1063/5.0294488","url":null,"abstract":"<p><p>This paper investigates the asymptotic behavior of a weighted scheduled traffic process, an extension of the traditional scheduled traffic model where events are subject to random perturbations and carry variable weights. Under the assumption that the perturbations follow a heavy-tailed distribution, we demonstrate that the appropriately rescaled process converges weakly to a fractional Brownian motion. Applications of this framework span diverse fields such as queueing theory, telecommunications, finance, and healthcare, where the model provides insights into workload accumulation, network traffic variability, and transaction flow dynamics.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145354093","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":"The negative information-epidemic coupling model based on individual emotional responses in multiplex network.","authors":"Liang'an Huo, Bingjie Liu","doi":"10.1063/5.0283393","DOIUrl":"https://doi.org/10.1063/5.0283393","url":null,"abstract":"<p><p>Individuals express diverse emotional responses to negative information and epidemics, which significantly influence both information diffusion and epidemic transmission. This study develops a coupling model based on individual emotional responses to analyze the interplay between negative information diffusion and epidemic transmission in a multiplex network. Emotional responses are classified as anxious and fair reactions. In the information layer, an individual's emotional response, determined by the threshold function, influences the strength of information diffusion. In the epidemic layer, the emotional responses of infected individuals are modeled using a linear function to describe their effect on recovery rates. A Markov chain approach is employed to analyze the epidemic outbreak threshold and estimate the final epidemic size. Extensive Monte Carlo simulations demonstrate that anxious individuals who are aware of the epidemic facilitate the diffusion of negative information. A higher proportion of anxious individuals accelerates epidemic transmission, lowers the outbreak threshold, and increases the final epidemic size. Furthermore, the effect of emotional responses on information diffusion is largely related to the neighborhood of the surrounding anxious response. In addition, infected individuals with anxious emotional responses are more sensitive to the effects of epidemic recovery rates. Reducing the anxiety of infected individuals and guiding the public to cope with the outbreak rationally will be beneficial for promoting the recovery of infected individuals and will also help to control the transmission of the epidemic.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336505","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}