The Origin of Shared Emergent Properties in Discrete Systems

Here, we propose that the shared emergent properties reproducibly observed in discrete systems can be explained by a theory that embeds the Conservation of Hartley-Shannon Information (CoHSI) in a statistical mechanics framework. Specific predictions of global properties that represent the most likely equilibrium state should be apparent in all qualifying systems, regardless of provenance. We demonstrate that these predictions of emergent global properties hold true in systems as disparate as collections of software written in the programming language C and collections of proteins. The implication is that the emergence of such shared properties is not driven by any specific local mechanism as the systems are so different. This raises the interesting prospect that important properties of biological systems (exemplified here by the length and multiplicity distributions of proteins) have little, if anything, to do with natural selection. Similarly, the size distribution of components and the frequency of tokens observed in computer software in C emerge as the most likely states, and are thus properties that are divorced from human agency, regardless of functionality.

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Publication Details

Journal
Entropy
Published
2025-05-26
DOI
https://doi.org/10.3390/e27060561
Citations
2
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
2.65
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article

The Origin of Shared Emergent Properties in Discrete Systems

Les Hatton, Greg Warr
2 citations
Entropy
Complex Network Analysis Techniques
2.65
article

The Origin of Shared Emergent Properties in Discrete Systems

Les Hatton, Greg Warr
article en
2 citations

Abstract

Here, we propose that the shared emergent properties reproducibly observed in discrete systems can be explained by a theory that embeds the Conservation of Hartley-Shannon Information (CoHSI) in a statistical mechanics framework. Specific predictions of global properties that represent the most likely equilibrium state should be apparent in all qualifying systems, regardless of provenance. We demonstrate that these predictions of emergent global properties hold true in systems as disparate as collections of software written in the programming language C and collections of proteins. The implication is that the emergence of such shared properties is not driven by any specific local mechanism as the systems are so different. This raises the interesting prospect that important properties of biological systems (exemplified here by the length and multiplicity distributions of proteins) have little, if anything, to do with natural selection. Similarly, the size distribution of components and the frequency of tokens observed in computer software in C emerge as the most likely states, and are thus properties that are divorced from human agency, regardless of functionality.

EntropyVol. 27(6)
Medical University of South Carolina (US), Kingston University London (GB)
Openalex Percentile: Top 11%
Complex Network Analysis Techniques
2.65
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The Origin of Shared Emergent Properties in Discrete Systems — Les Hatton, Greg Warr · Entropy (2025) | TGRS Research Map | TGRS