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Dynamical Phase Transitions in Quantum Reservoir Computing

Rodrigo Martínez‐Peña, Gian Luca Giorgi, Johannes Nokkala, Miguel C. Soriano, Roberta Zambrini

2021Physical Review Letters112 citationsDOIOpen Access PDF

Abstract

Closed quantum systems exhibit different dynamical regimes, like many-body localization or thermalization, which determine the mechanisms of spread and processing of information. Here we address the impact of these dynamical phases in quantum reservoir computing, an unconventional computing paradigm recently extended into the quantum regime that exploits dynamical systems to solve nonlinear and temporal tasks. We establish that the thermal phase is naturally adapted to the requirements of quantum reservoir computing and report an increased performance at the thermalization transition for the studied tasks. Uncovering the underlying physical mechanisms behind optimal information processing capabilities of spin networks is essential for future experimental implementations and provides a new perspective on dynamical phases.

Topics & Concepts

ExploitQuantumComputer scienceDynamical systems theoryThermalisationReservoir computingQuantum computerStatistical physicsPhase transitionPhysicsQuantum informationNonlinear systemTheoretical computer scienceQuantum mechanicsArtificial intelligenceArtificial neural networkRecurrent neural networkComputer securityNeural Networks and Reservoir ComputingQuantum many-body systemsQuantum Information and Cryptography
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