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Canonical quantization of a memristive leaky integrate-and-fire neuron circuit

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Authors: Dean Brand, Domenica Dibenedetto, Francesco Petruccione

Year

2026

Paper ID

28253

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

119

Citations

0

Abstract

We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems. Starting from a classical memristive LIF circuit, we apply canonical quantization techniques to derive a quantum model grounded in circuit quantum electrodynamics. Numerical simulations demonstrate key dynamical features of the quantized memristor and LIF neuron in the weak-coupling and adiabatic regime, including memory effects and spiking behavior. Applications of this model to a sound localization benchmark show that it outperforms a phenomenological quantum LIF model as well as a classical LIF. This work establishes a foundational model for quantum neuromorphic computing, offering a pathway toward biologically inspired quantum spiking neural networks and paradigms in quantum machine learning.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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  • We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems.

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