Quantum-like states on complex synchronized networks

Recent work has exposed the idea that interesting quantum-like (QL) probability laws, including interference effects, can be manifest in classical systems. Here, we propose a model for QL states and QL bits. We suggest a way that huge, complex systems can host robust states that can process information in a QL fashion. Axioms that such states should satisfy are proposed. Specifically, it is shown that building blocks suited for QL states are networks, possibly very complex, that we defined based on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>k</mml:mi> </mml:math> -regular random graphs. These networks can dynamically encode a lot of information that is distilled into the emergent states we can use for QL processing. Although the emergent states are classical, they have properties analogous to quantum states. Concrete examples of how QL functions are possible are given. The possibility of a ‘QL advantage’ for computing-type operations and the potential relevance for new kinds of function in the brain are discussed and left as open questions.

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Publication Details

Journal
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2024-08-01
DOI
https://doi.org/10.1098/rspa.2024.0209
Citations
13
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
4.46

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article

Quantum-like states on complex synchronized networks

Gregory D. Scholes
13 citations
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Neural dynamics and brain function
4.46
article

Quantum-like states on complex synchronized networks

Gregory D. Scholes
article en
13 citations

Abstract

Recent work has exposed the idea that interesting quantum-like (QL) probability laws, including interference effects, can be manifest in classical systems. Here, we propose a model for QL states and QL bits. We suggest a way that huge, complex systems can host robust states that can process information in a QL fashion. Axioms that such states should satisfy are proposed. Specifically, it is shown that building blocks suited for QL states are networks, possibly very complex, that we defined based on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>k</mml:mi> </mml:math> -regular random graphs. These networks can dynamically encode a lot of information that is distilled into the emergent states we can use for QL processing. Although the emergent states are classical, they have properties analogous to quantum states. Concrete examples of how QL functions are possible are given. The possibility of a ‘QL advantage’ for computing-type operations and the potential relevance for new kinds of function in the brain are discussed and left as open questions.

Proceedings of the Royal Society A Mathematical Physical and Engineering SciencesVol. 480(2295)
Princeton University (US)
National Science Foundation, Gordon and Betty Moore Foundation
Openalex Percentile: Top 5%
Neural dynamics and brain function
4.46
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