电子设计的物流地图网络中信息的非平凡生成和传输。

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-03-01 DOI:10.1063/5.0238711
Caracé Gutiérrez, Cecilia Cabeza, Nicolás Rubido
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引用次数: 0

摘要

在这项工作中,我们对扩散耦合逻辑图的电子实现中生成和传输的信息进行了批判性分析。我们的实现允许人们改变耦合配置(即网络)并微调耦合强度和映射参数,但具有最小的电子噪声和参数异质性,从而产生与数值模拟不同的集体行为。特别地,我们重点分析了两种动态状态及其对耦合构型的依赖:一种是产生和传输信息最大的状态,对应于混沌轨道的同步;另一种是产生信息但(实际上)没有传输的状态,对应于时空混沌。用香农熵来量化信息的产生,用互信息来量化信息的传递。为了描述这两种动态状态,我们引入了一个条件联合熵,它使用了两个量(熵和互信息),并分析了涉及6和12个耦合映射的60种不同耦合配置的值。我们发现90%的构型表现为混沌同步,92%的构型表现为时空混沌,时空混沌出现在需要强耦合强度的混沌同步之前。我们的结果还强调了在这些制度中最大化条件联合熵的耦合配置,而不需要密集耦合系统,这具有实际意义(因为在单元之间引入耦合可能是昂贵的)。总的来说,我们的工作有助于理解网络结构对复杂系统中信息的生成和传输的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-trivial generation and transmission of information in electronically designed logistic-map networks.

In this work, we carry out a critical analysis of the information generated and transmitted in an electronic implementation of diffusively coupled logistic maps. Our implementation allows one to change the coupling configuration (i.e., the network) and fine-tune the coupling strength and map parameters, but has minimal electronic noise and parameter heterogeneity, which generates collective behaviors that differ from numerical simulations. In particular, we focus on analyzing two dynamical regimes and their dependence on the coupling configuration: one where there is a maximum of information generated and transmitted-corresponding to synchronization of chaotic orbits-and another where information is generated but (practically) not transmitted-corresponding to spatiotemporal chaos. We use Shannon entropy to quantify information generation and mutual information to quantify information transmission. To characterize the two dynamical regimes, we introduce a conditional joint entropy that uses both quantities (entropy and mutual information) and analyze its values for 60 different coupling configurations involving 6 and 12 coupled maps. We find that 90% of the configurations exhibit chaotic synchronization and 92% spatiotemporal chaos, which emerges preceding the chaotic synchronous regime that requires strong coupling strengths. Our results also highlight the coupling configurations that maximize the conditional joint entropy in these regimes without requiring a densely coupled system, which has practical implications (since introducing couplings between units can be costly). Overall, our work contributes to understand the relevance that the network structure has on the generation and transmission of information in complex systems.

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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.
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