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Article

Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning in a Rigetti Quantum Computer

1
Department of Physical Chemistry, University of the Basque Country UPV/EHU, Apartado 644, 48080 Bilbao, Spain
2
IKERBASQUE, Basque Foundation for Science, Maria Diaz de Haro 3, 48013 Bilbao, Spain
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International Center of Quantum Artificial Intelligence for Science and Technology (QuArtist) and Physics Department, Shanghai University, Shanghai 200444, China
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IQM, 80336 Munich, Germany
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Departamento de Física Atómica, Molecular y Nuclear, Universidad de Sevilla, 41080 Sevilla, Spain
*
Author to whom correspondence should be addressed.
Quantum Rep. 2020, 2(2), 293-304; https://doi.org/10.3390/quantum2020019
Received: 31 March 2020 / Revised: 6 May 2020 / Accepted: 15 May 2020 / Published: 19 May 2020
(This article belongs to the Special Issue Exclusive Feature Papers of Quantum Reports)
We present an experimental realisation of a measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti cloud quantum computer. The experiment in this few-qubit superconducting chip faithfully reproduces the theoretical proposal, setting the first steps towards a semiautonomous quantum agent. This experiment paves the way towards quantum reinforcement learning with superconducting circuits. View Full-Text
Keywords: quantum artificial intelligence; quantum machine learning; quantum reinforcement learning; cloud quantum computer; rigetti quantum computer; state estimation quantum artificial intelligence; quantum machine learning; quantum reinforcement learning; cloud quantum computer; rigetti quantum computer; state estimation
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MDPI and ACS Style

Olivares-Sánchez, J.; Casanova, J.; Solano, E.; Lamata, L. Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning in a Rigetti Quantum Computer. Quantum Rep. 2020, 2, 293-304. https://doi.org/10.3390/quantum2020019

AMA Style

Olivares-Sánchez J, Casanova J, Solano E, Lamata L. Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning in a Rigetti Quantum Computer. Quantum Reports. 2020; 2(2):293-304. https://doi.org/10.3390/quantum2020019

Chicago/Turabian Style

Olivares-Sánchez, Julio, Jorge Casanova, Enrique Solano, and Lucas Lamata. 2020. "Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning in a Rigetti Quantum Computer" Quantum Reports 2, no. 2: 293-304. https://doi.org/10.3390/quantum2020019

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