We propose a quantum reservoir computing framework based on a hybrid cavity magnomechanical system in the linearized Gaussian regime. The reservoir combines microwave-cavity, magnon, and mechanical degrees of freedom, and is extended by an auxiliary cavity acting as an input port, with time-dependent signals encoded in...
Quantum Reservoir Computing (QRC) exploits the rich dynamics of quantum many-body systems to process time-dependent information with high-dimensional state spaces. While neutral atom arrays offer a scalable platform for this paradigm, realizing intrinsic temporal memory without relying on external classical buffering r...
Luca Nigro, G. Giorgi, E. Prati et al.· 0 citations
A quantum machine-learning model implemented on a programmable superconducting quantum annealer that processes temporal data at large scale using up to 4,500 qubits is reported-the largest quantum machine-learning experiment performed to date.
Antonio Sannia, Roberto Menta, Pratik Sathe et al.· 1 citation
Metastability in open quantum systems is usually inferred from spectral separation in the Liouvillian, which governs unconditional, ensemble-averaged dynamics. We show that this diagnosis is incomplete at the level of individual quantum trajectories: conditioned realizations of the same unconditional dynamics can bypas...
Manali Malakar, Roberta Zambrini, G. Giorgi· 0 citations
A general theory of monitored quantum reservoir computing based on indirect quantum measurements is developed, which unifies projective, weak, partial, and dissipative monitoring protocols within a single operational framework and establishes quantum measurement engineering as a systematic approach for designing reserv...
Oriol Morguí-Sancho, Gonzalo Manzano, G. Giorgi et al.· 2 citations
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