The Architecture of Coherence: A Unified Scalar-Field Framework from Fluid Dynamics to Astrophysical and Bioelectric Systems
Abstract
The Architecture of Coherence is a unified scientific framework proposing that a wide range of physical and biological systems can be consistently analyzed through the concept of scalar-field coherence. The framework integrates results from fluid dynamics, astrophysics, and coherence-based signal engineering, suggesting that stability, force emergence, and large-scale structure formation arise from coherent behavior of effective scalar potential fields rather than from domain-specific mechanisms alone. At the mathematical level, the framework incorporates dyadic decomposition and stability analysis of the three-dimensional incompressible Navier–Stokes equations, providing computational evidence for bounded nonlinear energy transfer under coherence-preserving conditions. At cosmological scales, it introduces a phenomenological scalar-potential interpretation of galaxy rotation curves and normalized gravitational lensing without invoking non-baryonic dark matter, using effective vacuum parameters within the Quantum Inertial Field Hypothesis (QIFH) and Zero Dark Energy (ZDE) formalism. At mesoscopic and biological scales, the framework is realized through coherence-sensitive engineering systems—such as Q-Vital Pulse and Q-Cancer Map—that detect weak bioelectric fields via phase coherence, gradient distortion, and relative baseline analysis. These implementations demonstrate that coherence-based field analysis can function as a general engineering principle independent of specific biological or astrophysical interpretations. The Architecture of Coherence is presented as a phenomenological and computationally grounded framework rather than a finalized fundamental theory. It is designed to be testable, reproducible, and open to independent verification, with potential relevance to physics, applied mathematics, signal engineering, and experimental systems science.
Publication details
- Journal / source
- Open Science Framework
- Publication date
- 1 January 2026