Bioreaction Quantum Computing without Quantum Diffusion

Abstract

Debate exists over whether or not adherence to quantum statistical mechanics and emulation of quantum information properties are sufficient criteria for biocomputations to be classified as quantum processes. A noteworthy example at the scale of intact life forms making social decisions can be found in "lower" eukaryotes. Ciliates learn to group Ca 2+ -dependent behavioral strategies into heuristics which they then use to signal mating status after physical contacts from presumed suitors and rivals. The time taken by ciliates to find appropriate strategies stored within behavioral repertoires diminishes with experience. Improvements in strategy search speeds by experts resemble the root-rate performance of Grover's quantum search algorithm over classical processes. Ciliates putatively implement fast strategy search algorithms by learning to change the reaction kinetics of mechanically activated Ca 2+ -induced Ca 2+ waves that travel through different cellular compartments to preferentially trigger over-learned behavioral sequences. Fire-diffuse-fire models demonstrate wave-conduction velocities most suited for quadratic increases in strategy search speeds are sensitive to limitations imposed by Ca 2+ release times and distances between Ca 2+ storage sites. These reaction-diffusion computations provide an interesting contrast to physicochemical quantum events described by equations containing quantum diffusion terms, as a modifiable classical diffusion coefficient solely accounts for root-rate processing efficiency. Fast chemical events underlying quantum information processing schemes in live biological systems can thus counter-intuitively exert their effects via thermodynamically vulnerable reaction parameters. The ubiquity and biological importance of intracellular Ca 2+ -induced Ca 2+ cascades across taxa suggests bacteria to mammals might likewise learn to use quantum-level processing when planning and executing behavioral strategies.

Basis for a neuronal version of Grover's quantum algorithm

“…Continued advances in systems biology, synthetic biology, and micro- and nanobiotechnology increasingly drive states-of-knowledge and -art in computational cell biology toward trends in logic gate, circuit, and algorithm designs (e.g., Ehrenfeucht et al, 2003; Amos, 2006; Baumgardner et al, 2009; Friedland et al, 2009; Adamatzky, 2010; Clark, 2010a,b,c,d, 2011, 2012b, 2013a; Norris et al, 2011; Karafyllidis, 2012; Mehta and Schwab, 2012; Daniel et al, 2013; Goñi-Moreno et al, 2013; Ji et al, 2013), especially for “programmable” group and solitary cellular decisions mediated by genetic, epigenetic, and somatic regulatory networks. Unsurprisingly, given their preeminent status as computational units (cf.…”

Ciliates learn to diagnose and correct classical error syndromes in mating strategies

“…Future research will have to address the biological mechanisms underlying such phenomena. One possible mechanism involves learned modification of intracellular Ca 2+ entry, homeostasis, and feedback regulation, which can account for previously observed classical and quantum computational phases (Clark, 2010a,b,c,d,e, 2011a,b,c, 2012a,b). In ciliates, as well as bacteria, algae, and fungi, free intracellular Ca 2+ acts as a response regulator critical for sensing and reacting to environmental stimuli (cf.…”

“…Furthermore, signals of ideal prudent savings and conspicuous consumption have greater mating significance in terms of net reproductive payoffs when compared to alternative mating replies (Clark, 2010a). Because preparedness impacts the type of serial behavioral signals generated and executed by ciliates and, therefore, the degree of mating success (Clark, 2010a, 2012a,b), it seems likely that preparedness also should dictate the quality or quantity of errors incurred during signal production as well as how those errors are diagnosed and corrected before transmission of mating replies. Collapsed across learning trials and across modal and non-modal strategies, a 3 × 5 repeated-measures factorial analysis showed level of initial contraction responsiveness of microbes only produced weakly significant overall interaction effects with Szilárd-engine operational characteristics, including mean average work, efficiency, power, coefficient of performance, and fidelity associated with strategy planning-execution corrective cycles [ F (8, 855) = 1.908, p = 0.056].…”

“…These fire-diffuse-fire reactions are believed to underlie observed increases in ciliate strategy searches following strategy planning (Clark, 2010a,b,c,d,e, 2011b,c) and possibly function as digital information channels (Plieth, 2005). As the reaction kinetics of Ca 2+ waves become restricted by the duration of Ca 2+ mobilization, wave velocity quickens in quadratic proportion to the classical Ca 2+ diffusion coefficient (Ponce-Dawson et al, 1999), matching the improved efficiency of Grover's quantum search algorithm over classical processes without evoking use of quantum diffusion terms (Clark, 2011c, 2012b). Furthermore, distinctive spatiotemporal patterns of activated intracellular Ca 2+ stores crosstalk with other response regulator systems, such as pheromone transduction pathways (Miyake, 1981; Nielsen and Heitman, 2007) and cAMP pathways (Siso-Nadal et al, 2009), to likely integrate and “bind” salient information into coherent chemical states or associative memory circuits.…”

The Extended Brain: Cyclic Information Flow in a Quantum Physical Realm

“…In turn, local magnetic fields can influence neural firing patterns and induce regional convergent zones of brain activity that are produced through sub-threshold EPSP's and inhibitory inter-neuronal synaptic activity, being amplified by reentry and recurrent circuitry (Pereira and Furlan, 2007). The importance of Ca 2+ waves in fast strategic search algorithms in a sort of bioreaction quantum computing was stressed by Clark (2012). Total brain activity is determined by genetic and epigenetic information, neuroplasticity, as well as functional cycles of efferent and afferent signals (internal copies and external mirror information), that reflect the interaction with the whole body and its environment and dynamically produce our inner worldview, earlier referred to as "personal universe" (Figure 3).…”