Basis for a neuronal version of Grover’s quantum algorithm

Frontiers in Molecular Neuroscience

Kevin Bradley Clark¹ 

[1] Complex Biological Systems Alliance;Greater Los Angeles VA Healthcare System;

关键词: Biotechnology;    Inositol 1,4,5-Trisphosphate Receptors;    Neuronal Plasticity;    cellular decision making;    intracellular calcium;    natural computing;   

DOI  :  10.3389/fnmol.2014.00029

来源: DOAJ

【 摘 要 】

Grover’s quantum (search) algorithm exploits principles of quantum information theory and computation to surpass the strong Church-Turing limit governing classical computers. The algorithm initializes a search field into superposed N (eigen)states to later execute nonclassical subroutines involving unitary phase shifts of measured states and to produce root-rate or quadratic gain in the algorithmic time (O(N^1/2)) needed to find some target solution m. Akin to this fast technological search algorithm, single eukaryotic cells, such as differentiated neurons, perform natural quadratic speed-up in the search for appropriate store-operated Ca2+ response regulation of, among other processes, protein and lipid biosynthesis, cell energetics, stress responses, cell fate and death, synaptic plasticity, and immunoprotection. Such speed-up in cellular decision making results from spatiotemporal dynamics of networked intracellular Ca2+-induced Ca2+ release and the search (or signaling) velocity of Ca2+ wave propagation. As chemical processes, such as the duration of Ca2+ mobilization, become rate-limiting over interstore distances, Ca2+ waves quadratically decrease interstore-travel time from slow saltatory to fast continuous gradients proportional to the square-root of the classical Ca2+ diffusion coefficient, D^1/2, matching the computing efficiency of Grover’s quantum algorithm. In this Hypothesis and Theory article, I elaborate on these traits using a fire-diffuse-fire model of store-operated cytosolic Ca2+ signaling valid for glutaminergic neurons. Salient model features corresponding to Grover’s quantum algorithm are parameterized to meet requirements for the Oracle Hadamard transform and Grover’s iteration. A neuronal version of Grover’s quantum algorithm figures to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional response regulation choices

【 授权许可】

Unknown