**SYSTEM HYPOTHESIS: A 3D BIOLOGICAL QUANTUM COMPUTER MODEL BASED ON CARBON CRYSTAL NETWORKS AND PROTON TRANSFER MECHANISMS**

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Authors: CÔNG LIỆT NGUYỄN
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Abstract

This work presents a system-level hypothesis proposing that Deoxyribonucleic Acid (DNA) functions as a complete three-dimensional biological quantum computing system rather than merely a chemical genetic storage molecule. In this model, nitrogenous bases act as multi-state information units (qudits), while codons function as three-dimensional quantum logic processors. The hypothesis is built on a quaternary information framework, where the four DNA bases correspond to distinct energy states of aromatic carbon structures. Grouping three bases into codons generates a sixty-four-state space, sufficient to encode twenty amino acids while naturally supporting quantum error correction through genetic code degeneracy. The three-dimensional geometry of codons is argued to enhance stability against thermal noise at physiological temperature. At the operational level, information processing is attributed to proton tunneling within hydrogen bonds between base pairs. Prior to observation during transcription or replication, protons may exist in superposition states within double-well potentials. Through conductive carbon networks and ionic salt environments, these quantum states may extend coherence and entanglement across gene sequences. Quantitative considerations indicate that DNA achieves extremely high information density and operates at energy scales approaching the Landauer limit. Salt ion concentrations, comparable to those of the primordial ocean, are proposed to act as a stabilizing dielectric environment that supports coherence in the carbon-based system. Finally, the work outlines experimentally testable predictions, including the possibility of detecting ultra-weak magnetic signatures generated by proton tunneling using high-sensitivity instruments such as SQUIDs or atomic magnetometers. This hypothesis offers a unified framework linking matter, energy, and information, and provides a conceptual foundation for future exploration of biological quantum computation and natural intelligence.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026