Dynamical properties of the composed Logistic-Gauss map.

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED Chaos Pub Date : 2025-01-01 DOI:10.1063/5.0238591
Luam Silva de Paiva, Julia G S Rocha, Joelson D V Hermes, Matheus Hansen, Ricardo Luiz Viana, Iberê Luiz Caldas, Rene O Medrano-T, Diogo Ricardo da Costa
{"title":"Dynamical properties of the composed Logistic-Gauss map.","authors":"Luam Silva de Paiva, Julia G S Rocha, Joelson D V Hermes, Matheus Hansen, Ricardo Luiz Viana, Iberê Luiz Caldas, Rene O Medrano-T, Diogo Ricardo da Costa","doi":"10.1063/5.0238591","DOIUrl":null,"url":null,"abstract":"<p><p>This study focuses on the analysis of a unique composition between two well-established models, known as the Logistic-Gauss map. The investigation cohesively transitions to an exploration of parameter space, essential for unraveling the complexity of dissipative mappings and understanding the intricate relationships between periodic structures and chaotic regions. By manipulating control parameters, our approach reveals intriguing patterns, with findings enriched by extreme orbits, trajectories that connect local maximum and minimum values of one-dimensional maps. This theory enhances our perception of structural organization and offers valuable perceptions of the system behaviors, contributing to an expanded understanding of chaos and periodicity in dynamic systems. The analysis reveals Complex Sets of Periodicity (CSP) in the parameter space, characterized by superstable curves that traverse their main bodies. The exploration of different combinations of parameters shows cascades of CSP structures with added periods and are organized based on extreme curves. This investigation offers valuable discoveries of the dynamics of dissipative mappings, opening avenues for future explorations in chaotic systems.</p>","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1063/5.0238591","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

This study focuses on the analysis of a unique composition between two well-established models, known as the Logistic-Gauss map. The investigation cohesively transitions to an exploration of parameter space, essential for unraveling the complexity of dissipative mappings and understanding the intricate relationships between periodic structures and chaotic regions. By manipulating control parameters, our approach reveals intriguing patterns, with findings enriched by extreme orbits, trajectories that connect local maximum and minimum values of one-dimensional maps. This theory enhances our perception of structural organization and offers valuable perceptions of the system behaviors, contributing to an expanded understanding of chaos and periodicity in dynamic systems. The analysis reveals Complex Sets of Periodicity (CSP) in the parameter space, characterized by superstable curves that traverse their main bodies. The exploration of different combinations of parameters shows cascades of CSP structures with added periods and are organized based on extreme curves. This investigation offers valuable discoveries of the dynamics of dissipative mappings, opening avenues for future explorations in chaotic systems.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
合成logistic -高斯映射的动力学性质。
本研究的重点是分析两个成熟模型之间的独特组成,即Logistic-Gauss图。研究紧密地过渡到对参数空间的探索,这对于揭示耗散映射的复杂性和理解周期结构和混沌区域之间的复杂关系至关重要。通过操纵控制参数,我们的方法揭示了有趣的模式,并通过极端轨道(连接一维地图的局部最大值和最小值的轨迹)丰富了研究结果。该理论增强了我们对结构组织的感知,并提供了对系统行为的有价值的感知,有助于扩大对动态系统中的混沌和周期性的理解。分析揭示了参数空间中的复周期集(CSP),其特征是超稳定曲线穿越其主体。对不同参数组合的探索显示了具有附加周期的CSP结构级联,并基于极端曲线组织。这项研究提供了耗散映射动力学的有价值的发现,为混沌系统的未来探索开辟了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
期刊最新文献
Continuum limit of the adaptive Kuramoto model. Directed recurrence networks for the analysis of nonlinear and complex dynamical systems. Evolution modeling and control of networked dynamic games with event-triggering mechanism. Koopman learning with episodic memory. Symbolic dynamics of joint brain states during dyadic coordination.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1