Pub Date : 2026-02-03DOI: 10.1016/j.chaos.2026.118009
Tian Hao
{"title":"Universal correlations of the superconducting transition temperature, the superfluid density, the linear-in-T coefficient, and the slope of resistivity–temperature dependence with the fractal dimensions of electron structures","authors":"Tian Hao","doi":"10.1016/j.chaos.2026.118009","DOIUrl":"https://doi.org/10.1016/j.chaos.2026.118009","url":null,"abstract":"","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"90 1","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1016/j.chaos.2026.117920
Dan Zhou, Zhiqin Liang, Yixin Fu, Mingru Lu, Tao Wang, Qi Xu, Wenyong Li, Hu Yang
{"title":"Risk-aware model predictive control for autonomous vehicle platoons under uncertain cut-in scenarios based on Gaussian mixture models","authors":"Dan Zhou, Zhiqin Liang, Yixin Fu, Mingru Lu, Tao Wang, Qi Xu, Wenyong Li, Hu Yang","doi":"10.1016/j.chaos.2026.117920","DOIUrl":"https://doi.org/10.1016/j.chaos.2026.117920","url":null,"abstract":"","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"399 1","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-02DOI: 10.1016/j.chaos.2026.118008
K. Tamilselvan, Jun Liu, Jing Song He
In this work, we analytically investigate, for the first time, instability dynamics induced by pure-quartic dispersion in vector dissipative systems governed by vector complex Ginzburg–Landau equations (CGLEs) that incorporate pure-quartic dispersion, four-wave mixing, and gain–loss effects. The vector CGLEs describe pulse propagation and evolution in all-optical mode-locked fiber laser configurations with pure-quartic dispersion. A modified linear stability analysis is employed to examine modulation instability (MI) arising from small perturbations to continuous-wave steady states. Using the analytical results, we systematically explore how key physical parameters, including wave-number mismatch, pure-quartic dispersion, nonlinearity, gain bandwidth, and gain coefficient, affect the MI process and overall instability characteristics. The analysis is performed rigorously for both gain-free (a regime of the proposed model not previously reported) and dissipative systems. Notably, we uncover distinct instability signatures, including asymmetric MI sidebands, monotonically increasing sideband gain, rectangular spike-like spectra, and partially blown-out MI structures in dissipative systems.
{"title":"Instability dynamics in the vector pure-quartic dissipative systems","authors":"K. Tamilselvan, Jun Liu, Jing Song He","doi":"10.1016/j.chaos.2026.118008","DOIUrl":"https://doi.org/10.1016/j.chaos.2026.118008","url":null,"abstract":"In this work, we analytically investigate, for the first time, instability dynamics induced by pure-quartic dispersion in vector dissipative systems governed by vector complex Ginzburg–Landau equations (CGLEs) that incorporate pure-quartic dispersion, four-wave mixing, and gain–loss effects. The vector CGLEs describe pulse propagation and evolution in all-optical mode-locked fiber laser configurations with pure-quartic dispersion. A modified linear stability analysis is employed to examine modulation instability (MI) arising from small perturbations to continuous-wave steady states. Using the analytical results, we systematically explore how key physical parameters, including wave-number mismatch, pure-quartic dispersion, nonlinearity, gain bandwidth, and gain coefficient, affect the MI process and overall instability characteristics. The analysis is performed rigorously for both gain-free (a regime of the proposed model not previously reported) and dissipative systems. Notably, we uncover distinct instability signatures, including asymmetric MI sidebands, monotonically increasing sideband gain, rectangular spike-like spectra, and partially blown-out MI structures in dissipative systems.","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"80 1","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-02DOI: 10.1016/j.chaos.2026.118012
Izat B. Baybusinov, Enrico Maria Fenoaltea, Zhen Han, Yi-Cheng Zhang
We introduce a general framework to solve a class of combinatorial optimization problems, including the matching problem, the Traveling Salesman Problem, and also the minimum weight k-factor problem. By reformulating these problems as an arrangement model, we recast the optimization task into a grand-canonical ensemble, where chemical potentials are used to relax strict topological constraints. The analytical solution found can serve as a polynomial-time algorithm to compute an approximate minimum cost for arbitrary k and link-weight distributions. Our framework is complementary to existing approaches and reveals new connections between combinatorial optimization and the statistical physics of disordered systems.
{"title":"A grand-canonical solution to a class of random optimization problems","authors":"Izat B. Baybusinov, Enrico Maria Fenoaltea, Zhen Han, Yi-Cheng Zhang","doi":"10.1016/j.chaos.2026.118012","DOIUrl":"https://doi.org/10.1016/j.chaos.2026.118012","url":null,"abstract":"We introduce a general framework to solve a class of combinatorial optimization problems, including the matching problem, the Traveling Salesman Problem, and also the minimum weight k-factor problem. By reformulating these problems as an arrangement model, we recast the optimization task into a grand-canonical ensemble, where chemical potentials are used to relax strict topological constraints. The analytical solution found can serve as a polynomial-time algorithm to compute an approximate minimum cost for arbitrary k and link-weight distributions. Our framework is complementary to existing approaches and reveals new connections between combinatorial optimization and the statistical physics of disordered systems.","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"8 1","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-31DOI: 10.1016/j.chaos.2026.117978
Xiaohua Hu , Xiang Zhu , Jia Shi , Zhaoxian Yan , Shuangshuang Qian , Hanlin Qi , Juan Du , He Yan , Changquan Ling
Modern multimodal learning often requires handling heterogeneous data types whose structures and information densities differ substantially. To address this challenge in the context of metabolic dysfunction-associated fatty liver disease (MAFLD) prediction, we propose an information-density-aware multimodal framework (NID-Net). Instead of relying on simple concatenation or shallow fusion, the model processes each modality using methods that align with its structural characteristics. Structured indicators with high information density are first processed by an XGBoost module optimized via Lagrange remainder correction, which enhances the nonlinearity of the loss landscape and improves robustness to data sparsity and imbalance. Meanwhile, tongue images with relatively low information density are encoded using a region-enhanced Swin Transformer, where adaptive regional biases guide the model toward informative local representations. The resulting modality-specific embeddings are fused within a Mixture-of-Experts (MoE) architecture, enabling selective specialization and nonlinear decision boundaries across modalities. Extensive experiments on real-world medical datasets demonstrate that NID-Net not only surpasses existing multimodal fusion approaches in predictive performance but also provides interpretable insights into cross-modal feature interactions. This work highlights the fundamental role of nonlinear design in achieving efficient, balanced, and explainable multimodal prediction systems.
{"title":"Modeling cross-modal interactions via a nonlinear information-density-aware network for MAFLD risk assessment","authors":"Xiaohua Hu , Xiang Zhu , Jia Shi , Zhaoxian Yan , Shuangshuang Qian , Hanlin Qi , Juan Du , He Yan , Changquan Ling","doi":"10.1016/j.chaos.2026.117978","DOIUrl":"10.1016/j.chaos.2026.117978","url":null,"abstract":"<div><div>Modern multimodal learning often requires handling heterogeneous data types whose structures and information densities differ substantially. To address this challenge in the context of metabolic dysfunction-associated fatty liver disease (MAFLD) prediction, we propose an information-density-aware multimodal framework (NID-Net). Instead of relying on simple concatenation or shallow fusion, the model processes each modality using methods that align with its structural characteristics. Structured indicators with high information density are first processed by an XGBoost module optimized via Lagrange remainder correction, which enhances the nonlinearity of the loss landscape and improves robustness to data sparsity and imbalance. Meanwhile, tongue images with relatively low information density are encoded using a region-enhanced Swin Transformer, where adaptive regional biases guide the model toward informative local representations. The resulting modality-specific embeddings are fused within a Mixture-of-Experts (MoE) architecture, enabling selective specialization and nonlinear decision boundaries across modalities. Extensive experiments on real-world medical datasets demonstrate that NID-Net not only surpasses existing multimodal fusion approaches in predictive performance but also provides interpretable insights into cross-modal feature interactions. This work highlights the fundamental role of nonlinear design in achieving efficient, balanced, and explainable multimodal prediction systems.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"207 ","pages":"Article 117978"},"PeriodicalIF":5.6,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：