An algorithmic complexity interpretation of Lin's third law of information theory

TL;DR

This paper proposes that Kolmogorov complexity better measures disorder in static structures than entropy, explaining how complexity influences stability and the inevitable evolution of structures towards universal randomness.

Contribution

It introduces an algorithmic complexity interpretation of Lin's third law, linking static structure stability to Kolmogorov complexity and randomness selection rules.

Findings

More complex structures are less stable.

Static structures evolve towards universal randomness.

Stability relates to the frequency of 1s in selected subsequences.

Abstract

Instead of static entropy we assert that the Kolmogorov complexity of a static structure such as a solid is the proper measure of disorder (or chaoticity). A static structure in a surrounding perfectly-random universe acts as an interfering entity which introduces local disruption in randomness. This is modeled by a selection rule $R$ which selects a subsequence of the random input sequence that hits the structure. Through the inequality that relates stochasticity and chaoticity of random binary sequences we maintain that Lin's notion of stability corresponds to the stability of the frequency of 1s in the selected subsequence. This explains why more complex static structures are less stable. Lin's third law is represented as the inevitable change that static structure undergo towards conforming to the universe's perfect randomness.