Simulation of memristive synapses and neuromorphic computing on a quantum computer

TL;DR

This paper introduces quantum gates that mimic memristive synapses, enabling neuromorphic computing on quantum hardware, demonstrated through simulations and experiments on a superconducting quantum computer.

Contribution

It proposes a novel quantum memristive model and a three-layer neural network capable of universal quantum computing, advancing brain-inspired quantum computing.

Findings

Quantum memristive behaviors observed, including hysteresis and plasticity.

Successful quantum state classification using the memristive neural network.

Experimental validation on ibmq_vigo quantum computer.

Abstract

One of the major approaches to neuromorphic computing is using memristors as analogue synapses. We propose unitary quantum gates that exhibit memristive behaviours, including Ohm's law, pinched hysteresis loop and synaptic plasticity. Hysteresis depending on the quantum phase and long-term plasticity that encodes the quantum state are observed. We also propose a three-layer neural network with the capability of universal quantum computing. Quantum state classification on the memristive neural network is demonstrated. Our results pave the way towards brain-inspired quantum computing. We obtain these results in numerical simulations and experiments on the superconducting quantum computer ibmq_vigo.