QuaResC
QUARESC QUANTUM MACHINE LEARNING USING RESERVOIR COMPUTING

  • I.P.: Miguel C. Soriano, Roberta Zambrini
  • Fecha de inicio: 1 de Junio de 2020
  • Fecha de final: 31 de Mayo de 2023

The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using reservoir computing. The PIs of QuaResC Roberta Zambrini (CSIC) and Miguel C. Soriano (UIB) recently have started to explore the possibility to join their efforts and experience in the new direction of quantum machine learning. The project aims at extending the reservoir computing paradigm into the quantum regime exploiting quantum networks as a specific realization of quantum machine learning. The goal of QuaResC is a systematic exploration of different implementations of quantum reservoir computing both with qubits and continuous variables to address their capability and to establish the possibility of a quantum advantage in the context of noisy intermediate-scale quantum computing (NISQ). The project is coordinated with two subprojects (1) Quantum reservoir computing and quantum complex systems and (2) Quantum reservoir computing and non-linear dynamical systems.
External collaborators include: Claudio Gallicchio (University of Pisa), Sabrina Maniscalco (University of Turku) and Valentina Parigi (Kastler–Brossel Laboratory).

Investigadores

  • Roberta Zambrini

    Roberta Zambrini

  • Stefano Longhi

    Stefano Longhi

  • Miguel C. Soriano

    Miguel C. Soriano

  • Gianluca Giorgi

    Gianluca Giorgi

  • Johannes Nokkala

    Johannes Nokkala

  • Albert Cabot

    Albert Cabot

  • Marco Cattaneo

    Marco Cattaneo

  • Rodrigo Martínez

    Rodrigo Martínez

Publicaciones recientes

Fluctuations and correlations in Kerr optical frequency combs with additive Gaussian noise

Chembo, Yanne K.; Coillet, Aurélien; Lin, Guoping; Colet, Pere; Gomila, Damià
Chaos 30, 083146 (1-6) (2020)

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