The Group Theoretic Roots of Information: permutations, symmetry, and entropy
David J. Galas

TL;DR
This paper introduces a novel group-theoretic interpretation of information and entropy, defining an integer entropy that generalizes Shannon entropy through permutation groups and reveals deep connections between symmetry, combinatorics, and information theory.
Contribution
It proposes a new combinatorial measure called integer entropy, linking finite groups and permutations to information measures, and extends the understanding of entropy beyond Shannon's framework.
Findings
Integer entropy converges to Shannon entropy as group size increases.
Integer entropy has a clear combinatorial meaning related to permutation cycles.
Finite groups have associated information functionals analogous to Shannon entropy.
Abstract
We propose a new interpretation of measures of information and disorder by connecting these concepts to group theory in a new way. Entropy and group theory are connected here by their common relation to sets of permutations. A combinatorial measure of information and disorder is proposed, in terms of integers and discrete functions, that we call the integer entropy. The Shannon measure of information is the limiting case of a richer, more general conceptual structure that reveals relations among finite groups, information, and symmetries. It is shown that the integer entropy converges uniformly to the Shannon entropy when the group includes all permutations, the Symmetric group, and the number of objects increases without bound. The harmonic numbers have a well-known combinatorial meaning as the expected number of disjoint, non-empty cycles in permutations of n objects, and since…
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Taxonomy
TopicsNeural Networks and Applications · Statistical Mechanics and Entropy · Neural dynamics and brain function
