标题： 群论，信息论和爱因斯坦似然原理 显示英文标题

标题： Groups, Information Theory and Einstein's Likelihood Principle

摘要： 我们提出一个统一的图景，其中广义熵的概念通过群论方法与信息论相关联。 群结构来自于熵在独立系统组合背景下必须明确定义的要求，在最近提出的香农-金钦公理的一般化框架中。 我们将每个大类熵的一个广义信息度量联系起来，该度量在独立系统集合上满足可加性性质，这是由于底层群法则的结果。 同时，我们还表明， 爱因斯坦似然函数自然地作为我们对（通常不可加）熵的信息解释的副产品出现。 这些结果证实了可组合熵在物理和社会科学背景中的适用性。 显示英文摘要

摘要： We propose a unifying picture where the notion of generalized entropy is related to information theory by means of a group-theoretical approach. The group structure comes from the requirement that an entropy be well defined with respect to the composition of independent systems, in the context of a recently proposed generalization of the Shannon-Khinchin axioms. We associate to each member of a large class of entropies a generalized information measure, satisfying the additivity property on a set of independent systems as a consequence of the underlying group law. At the same time, we also show that Einstein's likelihood function naturally emerges as a byproduct of our informational interpretation of (generally nonadditive) entropies. These results confirm the adequacy of composable entropies both in physical and social science contexts.