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Hilbert space as a computational resource in reservoir computing

2022; American Physical Society; Volume: 4; Issue: 3 Linguagem: Inglês

10.1103/physrevresearch.4.033007

2643-1564

William D. Kalfus, Guilhem Ribeill, Graham E. Rowlands, Hari Krovi, Thomas Ohki, Luke C. G. Govia,

Optical Network Technologies

Accelerating computation with quantum resources is limited by the challenges of high-fidelity control of quantum systems. Reservoir computing presents an attractive alternative, as precise control and full calibration of system dynamics are not required. Instead, complex internal trajectories in a large state space are leveraged as a computational resource. Quantum systems offer a unique venue for reservoir computing, given the presence of interactions unavailable in classical systems and a potentially exponentially-larger computational space. With a reservoir comprised of a single $d$-dimensional quantum system, we demonstrate clear performance improvement with Hilbert space dimension at two benchmark tasks and advantage over the physically analogous classical reservoir. Quantum reservoirs as realized by current-era quantum hardware offer immediate practical implementation and a promising outlook for increased performance in larger systems.