QuaResC
QUARESC QUANTUM MACHINE LEARNING USING RESERVOIR COMPUTING

  • I.P.: Miguel C. Soriano, Roberta Zambrini
  • Data d'inici: 1 de juny de 2020
  • Data de finalització: 31 de desembre 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).

Investigadors

  • Miguel C. Soriano

    Miguel C. Soriano

  • Roberta Zambrini

    Roberta Zambrini

  • Gian Luca Giorgi

    Gian Luca Giorgi

  • Stefano Longhi

    Stefano Longhi

  • Marco Cattaneo

    Marco Cattaneo

  • Rodrigo Martínez

    Rodrigo Martínez

Publicacions recents

Dissipation as a resource for Quantum Reservoir Computing

Antonio Sannia, Rodrigo Martínez-Peña, Miguel C. Soriano, Gian Luca Giorgi, Roberta Zambrini
Submitted (2024)

Nonequilibrium transition between a continuous and a discrete time-crystal

Cabot, Albert; Giorgi, Gian Luca; Zambrini, Roberta
Submitted (2024)

Quantifying the diversity of multiple time series with an ordinal symbolic approach

Zunino, Luciano; Soriano, Miguel C.
Physical Review E 108, 065302 (2023)

Engineered dissipation to mitigate barren plateaus

Antonio Sannia, Francesco Tacchino, Ivano Tavernelli, Gian Luca Giorgi, Roberta Zambrini
Submitted (2023)

Experimental Optical Simulator of Reconfigurable and Complex Quantum Environment

Renault, P.; Nokkala, J.; Roeland, G.; Joly, N.Y.; Zambrini, R.; Maniscalco, S.; Piilo, Y.; Treps; N.; Parigi.P
Physical Review X Quantum 4, 040310 (2023)

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