组态空间网络拓扑的发现

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摘要翻译：
动态系统的组态空间网络(CSN)是表示仿真过程中采样的组态集合及其动态连通性的有效方法。为了阐明CSN拓扑结构与支配系统动力学和热力学的自由能景观之间的联系，给出了解释度分布、邻区协同性和聚类系数的重尾的解析解。这一推导允许理解从简单的二次阱到beta3s肽和2D晶格杂聚合物的天然状态的系统中观察到的通用CSN网络拓扑。此外，CSN也属于一般的复杂网络类，用适应度模型描述d。
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英文标题：
《Uncovering the topology of configuration space networks》
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作者：
David Gfeller (1), Paolo De Los Rios (1), David Morton de Lachapelle
  (1), Guido Caldarelli (2,3), Francesco Rao (3) ((1) EPFL Lausanne
  Switzerland, (2) SMC CNR-INFM Rome Italy, (3) Centro Fermi Rome Italy)
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最新提交年份：
2007
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分类信息：

一级分类：Physics        物理学
二级分类：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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一级分类：Physics        物理学
二级分类：Disordered Systems and Neural Networks        无序系统与神经网络
分类描述：Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
眼镜和旋转眼镜；随机、非周期和准周期系统的性质；无序介质中的传输；本地化；由缺陷和无序介导的现象；神经网络
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英文摘要：
  The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underlying free-energy landscape governing the system dynamics and thermodynamics, an analytical soluti on is provided to explain the heavy tail of the degree distribution, neighbor co nnectivity and clustering coefficient. This derivation allows to understand the universal CSN network topology observed in systems ranging from a simple quadratic well to the native state of the beta3s peptide and a 2D lattice heteropolymer. Moreover CSN are shown to fall in the general class of complex networks describe d by the fitness model.
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PDF链接：
https://arxiv.org/pdf/704.2699

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关键词：connectivity distribution localization coefficient equilibrium configuration 聚类 协同 CSN 连通性