Quanta Fluid Dynamical Binary Neural Code (QFD-BNC) Model
Year: 2025
Type: article
Abstract: This paper introduces the Quanta Fluid Dynamical Binary Neural Code (QFD-BNC) Model, which proposes that thought exists in a fluid binary state (1/0) before recursion collapses it into either consciousness (1) or unconsciousness (0). Unlike conventional quantum superposition, this model treats thought evolution as a fluid dynamical process, where pre-consciousness and pre-unconsciousness interact recursively before emergent cognition. The framework is mathematically formalized using fluid dynamics, Gödelian incompleteness recursion, and a probabilistic Markov model. Computational validation, including Lattice Boltzmann simulations, recursive Markov collapse tests, and fractal chaos analysis, confirms the stability and predictability of recursive thought emergence. The results suggest a structured yet undecidable framework for cognition, supporting the existence of Gödelian limbo states in thought recursion.
Author: Rabbani, Hassan Rabbani
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6930696938
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