Open quantum generalisation of Hopfield neural networks

We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we pr...

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Main Authors: Rotondo, Pietro, Marcuzzi, Matteo, Garrahan, Juan P., Lesanovsky, Igor, Müller, M.
Format: Article
Language:English
Published: IOP 2018
Subjects:
Online Access:https://eprints.nottingham.ac.uk/50332/
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author Rotondo, Pietro
Marcuzzi, Matteo
Garrahan, Juan P.
Lesanovsky, Igor
Müller, M.
author_facet Rotondo, Pietro
Marcuzzi, Matteo
Garrahan, Juan P.
Lesanovsky, Igor
Müller, M.
author_sort Rotondo, Pietro
building Nottingham Research Data Repository
collection Online Access
description We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain.
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spelling nottingham-503322019-02-14T04:30:17Z https://eprints.nottingham.ac.uk/50332/ Open quantum generalisation of Hopfield neural networks Rotondo, Pietro Marcuzzi, Matteo Garrahan, Juan P. Lesanovsky, Igor Müller, M. We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain. IOP 2018-03-16 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/50332/1/opQnet.pdf Rotondo, Pietro, Marcuzzi, Matteo, Garrahan, Juan P., Lesanovsky, Igor and Müller, M. (2018) Open quantum generalisation of Hopfield neural networks. Journal of Physics A: Mathematical and Theoretical, 51 (11). 115301/1-115301/11. ISSN 1751-8121 neural networks; statistical physics of disordered systems; open quantum systems http://iopscience.iop.org/article/10.1088/1751-8121/aaabcb/meta doi:10.1088/1751-8121/aaabcb doi:10.1088/1751-8121/aaabcb
spellingShingle neural networks; statistical physics of disordered systems; open quantum systems
Rotondo, Pietro
Marcuzzi, Matteo
Garrahan, Juan P.
Lesanovsky, Igor
Müller, M.
Open quantum generalisation of Hopfield neural networks
title Open quantum generalisation of Hopfield neural networks
title_full Open quantum generalisation of Hopfield neural networks
title_fullStr Open quantum generalisation of Hopfield neural networks
title_full_unstemmed Open quantum generalisation of Hopfield neural networks
title_short Open quantum generalisation of Hopfield neural networks
title_sort open quantum generalisation of hopfield neural networks
topic neural networks; statistical physics of disordered systems; open quantum systems
url https://eprints.nottingham.ac.uk/50332/
https://eprints.nottingham.ac.uk/50332/
https://eprints.nottingham.ac.uk/50332/