From the 1 of 6 linked papers with an AI index.
6 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…
Storage, Scrambling, and Loss of Information in the Quantum Reservoir Computing Paradigm
Nathan Keenan, Roberta Zambrini
The suitability of a quantum reservoir computing (QRC) platform for a given time-series processing task is closely tied to the dynamical properties of its computational substrate a…
Dissipation in Periodically Driven Quantum Systems: Partial Secularization and Thermodynamic Consistency
LuÃsa T. Tude, Carlos Ortega-Taberner, Roberta Zambrini +1
Periodically driven open quantum systems are central to quantum thermodynamics and quantum control. These systems are typically described using Floquet-Born-Markov master equations…
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…