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Quantum accelerated approach to the thermal state of classical all-to-all connected spin systems with applications to pattern retrieval in the Hopfield neural network

Fiorelli, Eliana; Rotondo, Pietro; Marcuzzi, Matteo; Garrahan, Juan P.; Lesanovsky, Igor

Authors

Eliana Fiorelli

Pietro Rotondo



Abstract

We explore the question as to whether quantum effects can yield a speedup of the nonequilibrium evolution of fully connected quadratic spin models towards a classical thermal state. In our approach we exploit the fact that the thermal state of a spin system can be mapped onto a node-free quantum state whose coefficients are given by thermal weights. This perspective permits the construction of a dissipative yet quantum dynamics which encodes in its stationary state the thermal state of the original problem. We show for the case of an all-to-all connected Ising spin model that an appropriate transformation of this dissipative dynamics allows us to interpolate between a regime in which the order parameter obeys the classical equations of motion under Glauber dynamics and a quantum regime with an accelerated transient timescale before approaching stationarity. We show that this effect enables, in principle, a speedup of pattern retrieval in a Hopfield neural network.

Citation

Fiorelli, E., Rotondo, P., Marcuzzi, M., Garrahan, J. P., & Lesanovsky, I. (2019). Quantum accelerated approach to the thermal state of classical all-to-all connected spin systems with applications to pattern retrieval in the Hopfield neural network. Physical Review A, 99(3), Article 032126. https://doi.org/10.1103/physreva.99.032126

Journal Article Type Article
Acceptance Date Mar 11, 2019
Online Publication Date Mar 29, 2019
Publication Date Mar 29, 2019
Deposit Date Apr 30, 2019
Publicly Available Date Apr 30, 2019
Journal Physical Review A
Print ISSN 2469-9926
Electronic ISSN 2469-9934
Publisher American Physical Society
Peer Reviewed Peer Reviewed
Volume 99
Issue 3
Article Number 032126
DOI https://doi.org/10.1103/physreva.99.032126
Public URL https://nottingham-repository.worktribe.com/output/1873704
Publisher URL https://journals.aps.org/pra/abstract/10.1103/PhysRevA.99.032126
Additional Information Quantum accelerated approach to the thermal state of classical all-to-all connected spin systems with applications to pattern retrieval in the Hopfield neural network, Eliana Fiorelli, Pietro Rotondo, Matteo Marcuzzi, Juan P. Garrahan, and Igor Lesanovsky, Phys. Rev. A 99, 032126.

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