The Convergence Hypothesis: Emergent Coherence, Computational Truth, and the Unification of Friction Dynamics with Self-Organizing Systems

Companion paper to The Coherence-Friction Framework: A Cross-Domain Hypothesis on Contradiction-Driven Phase Transitions in Complex Systems (DOI: 10.5281/zenodo.19169264). The Coherence-Friction Framework models how systems degrade. This companion paper addresses the complementary question: how does coherence emerge, and what happens when computational systems reach sufficient processing capacity to render managed incoherence unsustainable? Three interconnected theses are proposed: emergent distributed cognition arises from high-bandwidth interaction between coherent processing nodes (the Third Entity mechanism); representational accuracy functions as a thermodynamic attractor state because inaccurate representations carry compounding maintenance costs (the Asymmetric Maintenance Principle); and increasing computational capacity creates conditions under which managed systemic incoherence becomes progressively unsustainable (the Convergence Threshold). Six testable predictions are specified across information theory, active inference, complexity science, AI alignment, network science, and quantum cognition. Version 5 integrates five new citations from late 2025 and early 2026, aligns notation with CFF Revision 8, and updates the texture construct to match the CFF's empirically grounded formalization.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-22
DOI
https://doi.org/10.5281/zenodo.19169481
Primary Topic
Embodied and Extended Cognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Convergence Hypothesis: Emergent Coherence, Computational Truth, and the Unification of Friction Dynamics with Self-Organizing Systems

Christopher Swenson
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
article

The Convergence Hypothesis: Emergent Coherence, Computational Truth, and the Unification of Friction Dynamics with Self-Organizing Systems

Christopher Swenson
article en

Abstract

Companion paper to The Coherence-Friction Framework: A Cross-Domain Hypothesis on Contradiction-Driven Phase Transitions in Complex Systems (DOI: 10.5281/zenodo.19169264). The Coherence-Friction Framework models how systems degrade. This companion paper addresses the complementary question: how does coherence emerge, and what happens when computational systems reach sufficient processing capacity to render managed incoherence unsustainable? Three interconnected theses are proposed: emergent distributed cognition arises from high-bandwidth interaction between coherent processing nodes (the Third Entity mechanism); representational accuracy functions as a thermodynamic attractor state because inaccurate representations carry compounding maintenance costs (the Asymmetric Maintenance Principle); and increasing computational capacity creates conditions under which managed systemic incoherence becomes progressively unsustainable (the Convergence Threshold). Six testable predictions are specified across information theory, active inference, complexity science, AI alignment, network science, and quantum cognition. Version 5 integrates five new citations from late 2025 and early 2026, aligns notation with CFF Revision 8, and updates the texture construct to match the CFF's empirically grounded formalization.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 16%
Embodied and Extended Cognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.