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Quantum computing architectures with signaling and control mimicking biological processes

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 contro...

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Detalles Bibliográficos
Autores principales: Pau, L.-F., Borza, P.N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10413076/
https://www.ncbi.nlm.nih.gov/pubmed/37576268
http://dx.doi.org/10.1016/j.heliyon.2023.e18593
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author Pau, L.-F.
Borza, P.N.
author_facet Pau, L.-F.
Borza, P.N.
author_sort Pau, L.-F.
collection PubMed
description 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.
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spelling pubmed-104130762023-08-11 Quantum computing architectures with signaling and control mimicking biological processes Pau, L.-F. Borza, P.N. Heliyon Research Article 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. Elsevier 2023-07-22 /pmc/articles/PMC10413076/ /pubmed/37576268 http://dx.doi.org/10.1016/j.heliyon.2023.e18593 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Pau, L.-F.
Borza, P.N.
Quantum computing architectures with signaling and control mimicking biological processes
title Quantum computing architectures with signaling and control mimicking biological processes
title_full Quantum computing architectures with signaling and control mimicking biological processes
title_fullStr Quantum computing architectures with signaling and control mimicking biological processes
title_full_unstemmed Quantum computing architectures with signaling and control mimicking biological processes
title_short Quantum computing architectures with signaling and control mimicking biological processes
title_sort quantum computing architectures with signaling and control mimicking biological processes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10413076/
https://www.ncbi.nlm.nih.gov/pubmed/37576268
http://dx.doi.org/10.1016/j.heliyon.2023.e18593
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