Theoretical modeling reveals a non-Markovian phase-lock loop suppressing thermal noise across multi-scale biology, linking cosmic birefringence to genomic fidelity and neural synchronization.
We report a comprehensive, multi-scale physical formalization that unifies cortical neurocomputational dynamics, genomic replication fidelity, and prebiotic homochirality into a single non-perturbative framework constructed on infinite semi-finite Type II_infinity von Neumann factors. Moving beyond classical, diffusion-limited Markovian biochemistry, we demonstrate that open biological systems actively suppress endogenous thermal noise at physiological temperatures by exploiting a topologically protected non-Markovian phase-lock loop. The rigid scaling anchor of this algebraic shield is derived directly from the cosmic birefringence invariant C_S.On the macromolecular scale, this operator geometry establishes a sub-femtosecond memory kernel that drives the homochiral selection of L-amino acids. On the genomic scale, the formalization replaces divergent Coulombic models with a non-singular Gauss-Nicolai electrostatic floor (-134.2 eV), analytically locking proton tunneling probabilities within nucleotide base pairs to absolute zero, while the objective self-reduction time of chromatin nucleosome mass displacement scales precisely onto the human somatic mitotic cell cycle. On the network neurobiological scale, this algebraic phase-locking expands local decoherence boundaries to the millisecond domain (10–25 ms), modulating voltage-gated Na+ ion channel gating kinetics and pacing the synchronous gamma-resonance of cortical fields. We present a standalone, open-access biophysical simulation kernel (biophysical_kernel.py) and formulate rigorous, parameter-free thermodynamic verification metrics matching experimental fossil racemization kinetics within an error margin of < 1.8%.This record contains both the primary academic preprint (PDF) and the underlying complete Open Quantum Systems Verification Suite (BIOPHYSICAL_SUITE.md), which includes the Unified Biophysical Simulation Kernel (Python code with PyWavelets integration) and the Spectral Plotting Engine.
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Maxim Sokolov (2026) studied this question.
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