From the 1 of 16 linked papers with an AI index.
16 papers
Energetic Cost of Temporal Information Processing in Quantum Reservoirs
Gabriele Cenedese, Gonzalo Manzano, Gian Luca Giorgi +1
Quantum reservoir computing offers a promising route toward energy-efficient machine learning by processing temporal information with minimal training overhead. Yet, the physical p…
General theory of monitored Quantum Reservoir Computing
Oriol MorguÃ-Sancho, Gian Luca Giorgi, Gonzalo Manzano +1
The paper develops a unified theoretical framework for quantum reservoir computing that incorporates various types of measurements, showing how measurement back‑action can be harne…
Temporal processing of quantum states with hybrid quantum-classical reservoirs
Mateu Coll-Comas, Gian Luca Giorgi, Roberta Zambrini
A distinctive feature of Quantum Reservoir Computing (QRC) is the ability to directly embed quantum input states into the reservoir dynamics. However, the resulting output is funda…
Benchmarking Quantum Extreme Learning based on Gaussian Boson Sampling
Daniel Montesinos, Gian Luca Giorgi, Roberta Zambrini
Reservoir models offer a hardware-efficient learning paradigm for noisy intermediate-scale quantum devices by exploiting untrained quantum dynamics as a fixed feature map and restr…
Quantum reservoir computing in Jaynes-Cummings models: Nonlinear memory and time-series prediction
Sreetama Das, Gian Luca Giorgi, Roberta Zambrini
We investigate quantum reservoir computing (QRC) using a hybrid qubit-boson system described by the Jaynes-Cummings (JC) Hamiltonian and its dispersive limit (DJC). These models pr…
Memory-enhanced quantum extreme learning machines for characterizing non-Markovian dynamics
Hajar Assil, Abderrahim El Allati, Gian Luca Giorgi
We use a Quantum Extreme Learning Machine for characterizing and estimating parameters of quantum dynamics generated by a tunable collision model. The input to the learning protoco…