Time-Series Quantum Reservoir Computing with Weak and Projective Measurements
Mujal, Pere; Martínez-Peña, Rodrigo; Giorgi, Gian Luca; Soriano, Miguel C.; Zambrini, Roberta
npj Quantum Information 9, 16 (2023)
npj Quantum Information 9, 16 (2023)
Time-series processing is a major challenge in machine learning with enormous progress in the last years in tasks such as speech recognition and chaotic series prediction. A promising avenue for sequential data analysis is quantum machine learning, with computational models like quantum neural networks and reservoir computing. An open question is how to efficiently include quantum measurement in realistic protocols while retaining the needed processing memory and preserving the quantum advantage offered by large Hilbert spaces. In this work, we propose different measurement protocols and assess their efficiency in terms of resources, through theoretical predictions and numerical analysis. We show that it is possible to exploit the quantumness of the reservoir and to obtain ideal performance both for memory and forecasting tasks with two successful measurement protocols. One repeats part of the experiment after each projective measurement while the other employs weak measurements operating online at the trade-off where information can be extracted accurately and without hindering the needed memory. Our work establishes the conditions for efficient time-series processing paving the way to its implementation in quantum devices.
Related research projects
QUAREC
Machine learning with quantum reservoir computing
I.P.: Roberta Zambrini
Project funded by the government of the Balearic Islands with the goal of extending Reservoir Computing into the quantum domain. The project is mainly theoretical/numerical, but also deals with the identification of …
QuaResC
Quantum machine learning using reservoir computing
I.P.: Miguel C. Soriano, Roberta Zambrini
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
QuaResC (CSIC)
Quantum machine learning using reservoir computing
I.P.: Roberta Zambrini
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
QuaResC (UIB)
Quantum machine learning using reservoir computing
I.P.: Miguel C. Soriano
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
Notícies relacionades
Investigadors de l’IFISC plantegen un nou protocol per al processament de dades amb Quantum Reservoir Computing
17 març de 2023
Investigadors de l’IFISC (UIB-CSIC) han proposat un nou protocol per processar dades seqüencials mitjançant l'aprenentatge automàtic quàntic.L'estudi proposa una manera d'incloure eficientment la mesura quàntica alhora que preserva l'avantatge quàntic que caracteritza aquests sistemes.Investigadors de l'Institut de Física Interdisciplinària i …
IFISC researchers propose a new protocol for data processing with Quantum Reservoir Computing
17 març de 2023
Researchers at IFISC (UIB-CSIC) propose a new protocol for processing sequential data using quantum machine learning.The study proposes a way to efficiently include quantum measurement while preserving the quantum advantage that characterises these systems. Researchers at the Institute for Cross-Disciplinary …
Investigadores del IFISC plantean un nuevo protocolo para el procesado de datos con Quantum Reservoir Computing
17 març de 2023
Investigadores del IFISC (UIB-CSIC) proponen un nuevo protocolo para procesar datos secuenciales mediante el aprendizaje automático cuántico.El estudio propone una manera de incluir eficientemente la medición cuántica a la vez que preserva la ventaja cuántica que caracteriza estos sistemas.Investigadores del …