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arXiv 0902.1235cond-mat.stat-mech
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物理学中的广义信息与熵测度

Generalized information and entropy measures in physics

Christian Beck

摘要:

统计力学的形式主义可以通过从比香农熵更一般的信息度量开始,并在适当的约束下最大化这些度量来推广。我们讨论了一些最重要的例子,信息措施,是有用的描述复杂系统。处理的例子是Renyi熵,Tsallis熵,阿部熵,Kaniadakis熵,Sharma-Mittal熵,和一些更多。对信息测度的公理化基础、可组合性和Lesche稳定性等重要概念进行了简要的讨论。在物理学中的潜在应用包括具有长程相互作用和亚稳态的复杂系统、粒子物理中的散射过程、流体动力学湍流、缺陷湍流、光晶格以及具有温度波动的相当普遍的驱动非平衡系统。

英文摘要:

The formalism of statistical mechanics can be generalized by starting from more general measures of information than the Shannon entropy and maximizing those subject to suitable constraints. We discuss some of the most important examples of information measures that are useful for the description of complex systems. Examples treated are the Renyi entropy, Tsallis entropy, Abe entropy, Kaniadakis entropy, Sharma-Mittal entropies, and a few more. Important concepts such as the axiomatic foundations, composability and Lesche stability of information measures are briefly discussed. Potential applications in physics include complex systems with long-range interactions and metastable states, scattering processes in particle physics, hydrodynamic turbulence, defect turbulence, optical lattices, and quite generally driven nonequilibrium systems with fluctuations of temperature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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