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Heliyon

Quantum computing architectures with signaling and control mimicking biological processes

L. F. Pau, Paul Nicolae Borza

Published Jul 21, 2023• 5 citations
Publisher

Abstract

Earlier reports have described a quantum computing architecture, in which key elements are derived from control functions in biology. In this further continuing research, focus is on the signaling and control of a flow of qubits in that architecture, mimicking synapse signals and neurological controls. After a short description of that architecture, and of quantum sensing elements, it is first shown how the coloring of quantum particle flows, implemented as in mathematical colored algebras, can reduce decoherence and enhance the decidability of quantum processing elements. Next, after reviewing specific human biology functions, and exploiting experimental results on excitation modes in live animals, it is shown how to achieve separation of the quantum control & signaling signals. Technologies and designs from particle physics are discussed as well as open research issues towards a realization of a quantum computing architecture with decidable signaling.

DOI
10.1016/j.heliyon.2023.e18593

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Earlier reports have described a quantum computing architecture, in which key elements are derived from control functions in biology. In this further continuing research, focus is on the signaling and control of a flow of qubits in that architecture, mimicking synapse signals and neurological controls. After a short description of that architecture, and of quantum sensing elements, it is first shown how the coloring of quantum particle flows, implemented as in mathematical colored algebras, can reduce decoherence and enhance the decidability of quantum processing elements. Next, after reviewing specific human biology functions, and exploiting experimental results on excitation modes in live animals, it is shown how to achieve separation of the quantum control & signaling signals. Technologies and designs from particle physics are discussed as well as open research issues towards a realization of a quantum computing architecture with decidable signaling.
This paper reports about progress in two areas towards quantum computing architectures with elements inspired from biological controls, as proposed in an earlier paper.The first area is about exploiting mathematical results in coloured algebras, which, combined with the colouring of particle flows, would reduce the decoherence and enhance the decidability in the quantum processing elements; definitions are being recalled, with the required assumptions and results.The second area is to provide experimental results, and a patented biological feedback process in synapse , about light and acoustic excitations in a live animal species to enhance reactivity; the experimental set-up is characterized , the measurement results provided, and the implications are explicated for quantum processing elements approximating a synapse.A paragraph on open issues explains how the results in the two areas will be combined and will help in the design a very early compiler version.
This paper proposes a novel quantum computer architecture design rooted in the principles of quantum biology. Traditional quantum computing architectures often struggle with decoherence and scalability, presenting significant hurdles to practical implementation. This work posits that quantum effects, previously observed and utilized within biological systems, offer a potentially more robust and efficient approach. Specifically, we explore how processes like quantum entanglement, quantum tunneling, and quantum coherence – frequently employed by biological organisms for tasks ranging from photosynthesis to bird navigation – can be harnessed within a computational framework. The core claim is that by directly mimicking and leveraging these biological mechanisms, we can design quantum computer architectures exhibiting improved fidelity, reduced error rates, and enhanced scalability. The architecture presented here incorporates several key elements, including a novel qubit design inspired by photosynthetic reaction centers and a control system modeled after biological feedback loops. Mathematical formulations are provided to illustrate the principles of operation and to quantify the potential improvements. The research presents a fundamental shift in perspective, transitioning from purely physics-based approaches to one that draws upon the remarkable efficiency and resilience found in nature's quantum systems.
As a step in the architectural design of a quantum processing or sensing system with control and signaling, an attempt is made at putting in parallel functional properties of the random flows between neurons through electrical synapses, and quantum particle flows inside a quantum processing system mimicking biological processes. Based on a simplified dynamic electrical synapse model, a quantum synapse circuit design is proposed. This is extended to the case of bidirectional flows through a synapse, highlighting the possible role of quantum synapse circuits as highly parallel controlled interfaces crucial in sensing and sensor fusion systems. A short status of the quantum simulation is provided.
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This paper proposes a novel quantum computing architecture inspired by the structure and function of biological neural networks. The core claim is to enhance quantum computing efficiency and fault tolerance by leveraging the inherent properties of biological systems. The mechanism involves modeling quantum bits (qubits) using biologically inspired neuron and synapse models, mimicking their interactions, and utilizing the self-organizing capabilities of neural networks for quantum computation. Unlike traditional quantum computing architectures rooted in classical physics, this approach aims to capitalize on the flexibility and adaptability found within biological systems. The architecture explores concepts such as quantum entanglement and superposition through simulated neural network dynamics, offering a potentially more robust and scalable solution for quantum processing. This work lays the foundation for a biologically-inspired quantum computing paradigm.
An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self- measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective.