Upper Entropy Axioms and Lower Entropy Axioms

TL;DR

This paper introduces new axiomatic frameworks for upper and lower entropy, unifying various entropy measures and extending the theoretical foundations of information theory beyond traditional axioms.

Contribution

It proposes novel upper and lower entropy axioms, weaker than classical axioms, and unifies different entropy forms under a common axiomatic system.

Findings

Entropy axioms ensure expansibility, subadditivity, and strong subadditivity.

Tsallis entropy is a special case within the proposed axiomatic framework.

Different information measures can be unified under the new axiomatic system.

Abstract

The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak upper entropy axioms and weak lower entropy axioms. Their conditions are weaker than those of Shannon-Khinchin axioms and Tsallis axioms, while these conditions are stronger than those of the axiomatics based on the first three Shannon-Khinchin axioms for superstatiscs. The expansibility, subadditivity and strong subadditivity of entropy are obtained in the new axiomatics. Tsallis statistics is a special case of the superstatistics which satisfies our axioms. Moreover, different forms of information measures, such as Shannon entropy, Daroczy entropy, Tsallis entropy and other entropies, can be unified under the same axiomatic framework.