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May 15, 20260 citationsOpen Access

The Expansion Hypothesis: Dynamical Regimes of Reflexive Coherence

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AMAldo G. Malasomma

Key Points

  • The aim is to refine the Expansion Hypothesis and enhance the understanding of how reflexive coherence behaves across varying dynamical regimes.
  • Introduced version 1.2 of The Expansion Hypothesis (TEH) as an extension of the Reflexive Coherence Model (RCM).
  • Clarified the role of contextual and systemic temporal stability within the framework.
  • Distinguished between necessary dynamical conditions and subjective experience.
  • Refined operational framing of reflexive coherence and its dynamical aspects.
  • Strengthened distinction among gain, dissonance, and dissipation in reflexive coherence.
  • Established a clearer understanding of the temporal viability of reflexive coherence.

Abstract

This work presents version 1.2 of The Expansion Hypothesis (TEH), a dynamical extension of the Reflexive Coherence Model (RCM). Rather than redefining consciousness or treating expansion as a metaphysical process, TEH models the temporal viability of reflexive coherence across changing dynamical regimes. The framework distinguishes the Reflexive Coherence Index (RCI), understood as a local operational observable, from the reflexive expansion construct Ξ(t), which represents the evolving capacity of a system to sustain, regulate, or reorganize reflexive coherence over time. Version 1.2 refines the hypothesis by aligning it with the revised operational framing of RCM v1.2, clarifying the role of contextual and systemic temporal stability, strengthening the distinction between necessary dynamical conditions and sufficient proof of subjective experience, and introducing a more explicit separation between gain, dissonance, and dissipation. TEH should be read as the dynamical layer of the broader framework trilogy: RCM defines the foundational architecture of reflexive coherence, TEH models its temporal dynamics, and Proto-Reflexive States in Artificial Systems develops the interpretive and applied layer for artificial systems.

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Cite This Study

Aldo G. Malasomma (2026) studied this question.

synapsesocial.com/papers/6a06b81ce7dec685947aab09https://doi.org/10.5281/zenodo.20157592
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