Anish's Universal Emergence Threshold Framework

This paper proposes a universal law describing the precise threshold at which any physical system transitions into a self-sustaining adaptive structure. The framework defines a critical balance between three measurable factors: the flow of usable energy, the capacity to store and process information, and the structural efficiency of the system. It hypothesizes that when the available energy flow, weighted by organizational quality, surpasses a critical ratio relative to both static and dynamic information capacities, a system achieves adaptive emergence. The hypothesis is designed to be empirically tested across diverse domains, including biology, quantum systems, artificial intelligence, and cosmology, using standardized measurements. This work aims to provide a quantifiable, cross-disciplinary foundation for understanding the origins of life, complex adaptive systems, and the efficiency of emerging technologies.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-02
DOI
https://doi.org/10.5281/zenodo.16728924
Primary Topic
Chaos, Complexity, and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Anish's Universal Emergence Threshold Framework

Zenodo (CERN European Organization for Nuclear Research)
Chaos, Complexity, and Education
article

Anish's Universal Emergence Threshold Framework

article en

Abstract

This paper proposes a universal law describing the precise threshold at which any physical system transitions into a self-sustaining adaptive structure. The framework defines a critical balance between three measurable factors: the flow of usable energy, the capacity to store and process information, and the structural efficiency of the system. It hypothesizes that when the available energy flow, weighted by organizational quality, surpasses a critical ratio relative to both static and dynamic information capacities, a system achieves adaptive emergence. The hypothesis is designed to be empirically tested across diverse domains, including biology, quantum systems, artificial intelligence, and cosmology, using standardized measurements. This work aims to provide a quantifiable, cross-disciplinary foundation for understanding the origins of life, complex adaptive systems, and the efficiency of emerging technologies.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 52%
Chaos, Complexity, and Education
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