Simulation of memristive synapses and neuromorphic computing on a quantum computer

One of the major approaches to spike-based neuromorphic computing is using memristors as analog synapses. We propose unitary quantum gates that exhibit memristive behaviors, including Ohm's law, pinched hysteresis loop and synaptic plasticity. Hysteresis depending on the quantum phase and long-...

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Main Author: Ying Li
Format: Article
Language:English
Published: American Physical Society 2021-05-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/PhysRevResearch.3.023146
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author Ying Li
author_facet Ying Li
author_sort Ying Li
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description One of the major approaches to spike-based neuromorphic computing is using memristors as analog synapses. We propose unitary quantum gates that exhibit memristive behaviors, 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. These results pave the way towards quantum spiking neural network built on unitary processes. We obtain these results in numerical simulations and experiments on the superconducting quantum computer ibmq_vigo.
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spelling doaj.art-dadede16ad654b8dadc245b05338d2612024-04-12T17:10:10ZengAmerican Physical SocietyPhysical Review Research2643-15642021-05-013202314610.1103/PhysRevResearch.3.023146Simulation of memristive synapses and neuromorphic computing on a quantum computerYing LiOne of the major approaches to spike-based neuromorphic computing is using memristors as analog synapses. We propose unitary quantum gates that exhibit memristive behaviors, 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. These results pave the way towards quantum spiking neural network built on unitary processes. We obtain these results in numerical simulations and experiments on the superconducting quantum computer ibmq_vigo.http://doi.org/10.1103/PhysRevResearch.3.023146
spellingShingle Ying Li
Simulation of memristive synapses and neuromorphic computing on a quantum computer
Physical Review Research
title Simulation of memristive synapses and neuromorphic computing on a quantum computer
title_full Simulation of memristive synapses and neuromorphic computing on a quantum computer
title_fullStr Simulation of memristive synapses and neuromorphic computing on a quantum computer
title_full_unstemmed Simulation of memristive synapses and neuromorphic computing on a quantum computer
title_short Simulation of memristive synapses and neuromorphic computing on a quantum computer
title_sort simulation of memristive synapses and neuromorphic computing on a quantum computer
url http://doi.org/10.1103/PhysRevResearch.3.023146
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