The Photon-induced Genesis of RNA and DNA: A Quantum-geometric CNP Model

Authors

  • Pavle Vesić Indepedent Researcher, Belgrade, Serbia

DOI:

https://doi.org/10.14738/ejas.1405.12519

Keywords:

CNP, STA, FEP, RNA, DNA, UV-C, Photon Fade

Abstract

The evolutionary transition from prebiotic chemistry to the first information-bearing macro-molecules remains one of the most significant paradoxes in modern science. This paper introduces a deterministic, quantum-geometric model for the origin of nucleic acids driven by the Charge Neutralization Process (CNP) under fluctuating environmental photon fluxes. Operating within Hestenes’ Spacetime Algebra (Cl1,3) and Friston’s Free Energy Principle (FEP), we reframe the genesis of RNA and DNA not as a stochastic chemical accident, but as a fundamental topological necessity of vacuum stress compensation. We demonstrate that high-energy, non-ionizing photon interactions (Case 3 geometry) distort localized electron-proton Zitterbewegung (zbw) rotors, imposing a geometric stress tensor on the boundary of macro-molecular systems (n-th Markov blankets). To preserve boundary integrity and minimize variational free energy, CNP forces the polymerization of free nucleotides into a single-stranded RNA chain, which acts as a dynamic geometric antenna that neutralizes the external electromagnetic flux. Crucially, when the external photon source fades, the asymmetric RNA strand becomes an internal source of vacuum deformation. To eliminate this residual internal stress, CNP executes an inversion of the topological gradient, drawing complementary bases into a stable, bivector phase-locked double helix. DNA is therefore revealed to be a stabilized, archetypal "null-surface" of the vacuum—a physical archive of past environmental stress. This framework seamlessly integrates the thermodynamic dissipation theories of life with the RNA World hypothesis under a singular cosmic algorithm.

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Published

2026-10-30

How to Cite

Vesić, P. (2026). The Photon-induced Genesis of RNA and DNA: A Quantum-geometric CNP Model. European Journal of Applied Sciences, 14(05), 508–520. https://doi.org/10.14738/ejas.1405.12519