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April 8, 20260 citationsOpen Access

Phase-Model Paper 07: A Phase-Randomization Closure Model for Decoherence

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YYoshida

Key Points

  • The research aims to present a phase-randomization closure model that explains coherence decay in quantum systems.
  • Introduces a model framework linking phase variance to coherence decay.
  • Describes dynamics of phase diffusion and synchronization recovery.
  • Outlines falsifiable predictions and rejection criteria for testing the model.
  • Demonstrates how phase-variance dynamics correlate with observable coherence indicators.
  • Provides explicit predictions for experimental validation across multiple setups.

Abstract

Version note (v2.0, 2026-04-06): This release updates editorial consistency across the Phase-Model series (Papers 01–13), including reference formatting, author-name normalization, and removal of local-path citation strings. The core model claims and rejection logic are unchanged unless explicitly stated below. This preprint proposes a phase-randomization closure model for decoherence. The framework describes coherence decay as competition between phase diffusion and synchronization recovery, links phase-variance dynamics to observable coherence indicators, and provides explicit falsifiable predictions and rejection criteria across multiple experimental platforms.

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Cite This Study

Yoshida (2026) studied this question.

synapsesocial.com/papers/69d5f14b74eaea4b11a7ae5ahttps://doi.org/10.5281/zenodo.19439222
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Phase-Model Paper 06: A Phase-Selection Closure Model for the Quantum Measurement Problem2026
  2. 2Phase-Model Paper 04: A Phase-Synchronization Closure Model for High-Tc Superconductivity2026
  3. 3Phase-Model Paper 01: A Phase-Locking Closure Model for the L-H Transition2026
  4. 4Phase-Model Paper 10: A Hidden-Phase Closure Model for Dark-Matter-Like Effects2026
  5. 5Phase-Model Paper 12: A Phase Self-Organization Closure Model for Pattern Formation2026