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January 17, 20260 citationsOpen Access

Dynamics of Coherence Capacity: Transport, Concentration, and Exhaustion

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PNPeter Nero

Key Points

  • The aim is to develop a dynamical theory of coherence capacity to understand its predictive stability and transport phenomena.
  • Developed a dynamical theory of coherence capacity.
  • Identified coherence capacity as a conserved resource within admissible regimes.
  • Established a local transport law and divergence-free current in coherence basins.
  • Analyzed the effects of persistent strain on capacity flow and concentration dynamics.
  • Demonstrated that persistent strain induces focusing of the capacity flow.
  • Established the occurrence of bottlenecks and exhaustion on codimension-one surfaces.
  • Showed that irreversibility arises at admissibility barriers, affecting capacity conservation.
  • Provided insights into gravitational attraction, horizon formation, and thermalization without altering fundamental dynamics.

Abstract

We develop the dynamical theory of coherence capacity, the finite stability margin that allows a projection-based effective description to remain predictive. Building on the identification of coherence capacity as a conserved resource within admissible regimes, we show that it admits a local transport law and a divergence-free current inside coherence basins. We prove that persistent strain generically induces focusing of the capacity flow, leading to concentration, bottleneck formation, and exhaustion on codimension-one surfaces. At admissibility barriers, capacity is no longer conserved and effective evolution becomes noninvertible, yielding irreversibility as a structural necessity despite invertibility of the underlying dynamics. This transport-and-focusing picture provides the dynamical substrate for gravitational attraction, horizon formation, thermalization, and loss of memory, without modifying fundamental dynamics or introducing new degrees of freedom. The results are model-independent and follow solely from projection-based effective description with finite stability margins, completing the coherence-capacity framework by supplying its dynamics.

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Cite This Study

Peter Nero (2026) studied this question.

synapsesocial.com/papers/696b2672d2a12237a9349addhttps://doi.org/10.5281/zenodo.18256048
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