Evolution Via EPR-Entanglement Algorithm

Journal Title: Journal of Biomedical Engineering and Medical Imaging - Year 2017, Vol 4, Issue 2

Abstract

By quantifying EPR-generated accumulations of entangled proton qubits populating duplex microsatellite base pairs, observed as G-C → G'-C', G-C → *G-C* and A-T → *A-*T, the potential to exhibit expansion or contraction over evolutionary times can be qualitatively specified. Bold italics identify base pair superpositions of entangled proton qubits. Metastable hydrogen bonding amino (−NH2) protons encounter quantum uncertainty limits, Δx Δpx ≥ ћ/2, which generate EPR arrangements, keto-amino ―(entanglement)→ enol−imine, yielding reduced energy entangled proton qubits shared between two indistinguishable sets of electron lone-pairs belonging to enol oxygen and imine nitrogen on opposite strands. When measured by Grover’s-type quantum processors, δt ≤ 10–13 s, microsatellites whose entangled proton qubits generate a preponderance of initiation codons ─ UUG, CUG, AUG, GUG ─ participate in the expansion mode of DNA synthesis, but if more stop codons ─ UAA, UGA, UAG ─ were introduced and/or the particular sequence consisted exclusively of A-T, such microsatellites would generally decrease in relative abundance over evolutionary times. This model is tested by evaluating the twenty-two most abundant microsatellites common to human and rat. From this list, predictions by “measurements of” entangled proton qubit states identify two ordered sets – eleven exhibiting expansion and eleven exhibiting contraction – of microsatellites, consistent with observation. These analyses imply Grover’s-type enzyme-processor measurements of EPR-generated entangled proton “qubit pairs” can simulate microsatellite evolution, and further, identify entangled proton “qubit pairs” as the smallest “measurable” genetic informational unit, specifying particular evolution instructions with “measured” quantum information. Classical pathways cannot simulate microsatellite evolution observables.

Authors and Affiliations

W. Grant Cooper

Keywords

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  • EP ID EP295949
  • DOI 10.14738/jbemi. 42.2795
  • Views 88
  • Downloads 0

How To Cite

W. Grant Cooper (2017). Evolution Via EPR-Entanglement Algorithm. Journal of Biomedical Engineering and Medical Imaging, 4(2), 43-95. https://europub.co.uk/articles/-A-295949