Dynamic Synaptic Modulation of LMG Qubits populations in a Bio-Inspired Quantum Brain

Abstract:We present a biologically inspired quantum neural network that encodes neuronal populations as fully connected qubits governed by the Lipkin-Meshkov-Glick (LMG) quantum Hamiltonian and modulated by a synaptic-efficacy feedback implementing activity-dependent changes in the collective time scale. The framework links collective quantum many-body modes and collective-state structure to population homeostasis and rhythmogenesis, outlining scalable computational primitives long-lived operating regimes, activity-dependent oscillation periods, and size-dependent robustness that position LMG-based architectures as promising blueprints for bio-inspired quantum brains on future quantum hardware.

Quantum Physics (quant-ph); Computational Physics (physics.comp-ph)

arXiv:2602.16003 [quant-ph]

(or arXiv:2602.16003v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2602.16003 Focus to learn more arXiv-issued DOI via DataCite

Quantum Sci. Technol. 11 035048 (2026)

https://doi.org/10.1088/2058-9565/ae8a7b Focus to learn more DOI(s) linking to related resources

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