• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

混沌映射中动力学对称性的普适性

Universality of Dynamical Symmetries in Chaotic Maps.

作者信息

Acero Marcos, Lyons Sean, Aragoneses Andrés, Pattanayak Arjendu K

机构信息

Department of Physics and Astronomy, Carleton College, Northfield, MN 55057, USA.

Department of Physics, Whitman College, Walla Walla, WA 99362, USA.

出版信息

Entropy (Basel). 2024 Nov 12;26(11):969. doi: 10.3390/e26110969.

DOI:10.3390/e26110969
PMID:39593913
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11593186/
Abstract

Identifying signs of regularity and uncovering dynamical symmetries in complex and chaotic systems is crucial both for practical applications and for enhancing our understanding of complex dynamics. Recent approaches have quantified temporal correlations in time series, revealing hidden, approximate dynamical symmetries that provide insight into the systems under study. In this paper, we explore universality patterns in the dynamics of chaotic maps using combinations of complexity quantifiers. We also apply a recently introduced technique that projects dynamical symmetries into a "symmetry space", providing an intuitive and visual depiction of these symmetries. Our approach unifies and extends previous results and, more importantly, offers a meaningful interpretation of universality by linking it with dynamical symmetries and their transitions.

摘要

识别复杂和混沌系统中的规律性迹象并揭示动力学对称性,对于实际应用以及增进我们对复杂动力学的理解都至关重要。最近的方法对时间序列中的时间相关性进行了量化,揭示了隐藏的、近似的动力学对称性,这些对称性为深入了解所研究的系统提供了线索。在本文中,我们使用复杂性量化指标的组合来探索混沌映射动力学中的普适模式。我们还应用了一种最近引入的技术,将动力学对称性投影到一个“对称空间”中,从而对这些对称性进行直观且可视化的描述。我们的方法统一并扩展了先前的结果,更重要的是,通过将普适性与动力学对称性及其转变联系起来,为普适性提供了有意义的解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/f8528c0bd337/entropy-26-00969-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/c3672d64423e/entropy-26-00969-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/7e5413034611/entropy-26-00969-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/634d9aa01a23/entropy-26-00969-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/1b4fa6e58cbd/entropy-26-00969-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/cb254e5e72dd/entropy-26-00969-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/f8528c0bd337/entropy-26-00969-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/c3672d64423e/entropy-26-00969-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/7e5413034611/entropy-26-00969-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/634d9aa01a23/entropy-26-00969-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/1b4fa6e58cbd/entropy-26-00969-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/cb254e5e72dd/entropy-26-00969-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097b/11593186/f8528c0bd337/entropy-26-00969-g006.jpg

相似文献

1
Universality of Dynamical Symmetries in Chaotic Maps.混沌映射中动力学对称性的普适性
Entropy (Basel). 2024 Nov 12;26(11):969. doi: 10.3390/e26110969.
2
A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis.一类二次多项式混沌映射及其不动点分析
Entropy (Basel). 2019 Jul 4;21(7):658. doi: 10.3390/e21070658.
3
Space-Group Symmetries Generate Chaotic Fluid Advection in Crystalline Granular Media.空间群对称性在晶体颗粒介质中产生混沌流体平流。
Phys Rev Lett. 2018 Jan 12;120(2):024501. doi: 10.1103/PhysRevLett.120.024501.
4
Contrasting chaotic with stochastic dynamics via ordinal transition networks.通过有序转移网络对比混沌动力学与随机动力学。
Chaos. 2020 Jun;30(6):063101. doi: 10.1063/1.5142500.
5
Unveiling the Connectivity of Complex Networks Using Ordinal Transition Methods.使用有序转移方法揭示复杂网络的连通性
Entropy (Basel). 2023 Jul 18;25(7):1079. doi: 10.3390/e25071079.
6
Evaluating Temporal Correlations in Time Series Using Permutation Entropy, Ordinal Probabilities and Machine Learning.使用排列熵、序数概率和机器学习评估时间序列中的时间相关性。
Entropy (Basel). 2021 Aug 9;23(8):1025. doi: 10.3390/e23081025.
7
Characterizing Complex Dynamics in the Classical and Semi-Classical Duffing Oscillator Using Ordinal Patterns Analysis.使用序数模式分析表征经典和半经典杜芬振荡器中的复杂动力学
Entropy (Basel). 2018 Jan 10;20(1):40. doi: 10.3390/e20010040.
8
Analysis of Chaotic Dynamics by the Extended Entropic Chaos Degree.基于扩展熵混沌度的混沌动力学分析
Entropy (Basel). 2022 Jun 14;24(6):827. doi: 10.3390/e24060827.
9
Three-dimensional chaotic flows with discrete symmetries.具有离散对称性的三维混沌流。
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Mar;69(3 Pt 2):036202. doi: 10.1103/PhysRevE.69.036202. Epub 2004 Mar 11.
10
Detection of chaotic patterns in dripping faucets through nonlinear dynamic system analysis based on observations using 2700 high-frequency frames.基于使用2700个高频帧的观测结果,通过非线性动力学系统分析检测滴水水龙头中的混沌模式。
MethodsX. 2025 Mar 31;14:103295. doi: 10.1016/j.mex.2025.103295. eCollection 2025 Jun.