Microwave signal processing using an analog quantum reservoir computer

A Senanian, S Prabhu, V Kremenetski, S Roy… - Nature …, 2024 - nature.com
Quantum reservoir computing (QRC) has been proposed as a paradigm for performing
machine learning with quantum processors where the training takes place in the classical …

Engineered dissipation to mitigate barren plateaus

A Sannia, F Tacchino, I Tavernelli, GL Giorgi… - npj Quantum …, 2024 - nature.com
Variational quantum algorithms represent a powerful approach for solving optimization
problems on noisy quantum computers, with a broad spectrum of potential applications …

Experimental optical simulator of reconfigurable and complex quantum environment

P Renault, J Nokkala, G Roeland, NY Joly, R Zambrini… - Prx quantum, 2023 - APS
No quantum system can be considered totally isolated from its environment. In most cases
the interaction between the system of interest and the external degrees of freedom deeply …

Role of coherence in many-body Quantum Reservoir Computing

A Palacios, R Martínez-Peña, MC Soriano… - Communications …, 2024 - nature.com
Abstract Quantum Reservoir Computing (QRC) offers potential advantages over classical
reservoir computing, including inherent processing of quantum inputs and a vast Hilbert …

Squeezing as a resource for time series processing in quantum reservoir computing

J García-Beni, G Luca Giorgi, MC Soriano… - Optics …, 2024 - opg.optica.org
Squeezing is known to be a quantum resource in many applications in metrology,
cryptography, and computing, being related to entanglement in multimode settings. In this …

Extending echo state property for quantum reservoir computing

S Kobayashi, QH Tran, K Nakajima - Physical Review E, 2024 - APS
The echo state property (ESP) represents a fundamental concept in the reservoir computing
(RC) framework that ensures output-only training of reservoir networks by being agnostic to …

[HTML][HTML] Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective

AH Abbas, H Abdel-Ghani, IS Maksymov - Dynamics, 2024 - mdpi.com
Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-
driving cars may consume up to 50% of the total power available onboard, thereby limiting …

Large-scale quantum reservoir learning with an analog quantum computer

M Kornjača, HY Hu, C Zhao, J Wurtz… - arXiv preprint arXiv …, 2024 - arxiv.org
Quantum machine learning has gained considerable attention as quantum technology
advances, presenting a promising approach for efficiently learning complex data patterns …

Quantum reservoir computing on random regular graphs

MN Ivaki, A Lazarides, T Ala-Nissila - arXiv preprint arXiv:2409.03665, 2024 - arxiv.org
Quantum reservoir computing (QRC) is a low-complexity learning paradigm that combines
the inherent dynamics of input-driven many-body quantum systems with classical learning …

Leveraging non-unital noise for gate-based quantum reservoir computing

F Monzani, E Ricci, L Nigro, E Prati - arXiv preprint arXiv:2409.07886, 2024 - arxiv.org
We identify a noise model that ensures the functioning of an echo state network employing a
gate-based quantum computer for reservoir computing applications. Energy dissipation …