Quantum compiling by deep reinforcement learning

Quantum compilers are characterized by a trade-off between the length of the sequences, the precompilation time, and the execution time. Here, the authors propose an approach based on deep reinforcement learning to approximate unitary operators as circuits, and show that this approach decreases the...

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Autores principales: Lorenzo Moro, Matteo G. A. Paris, Marcello Restelli, Enrico Prati
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/ab73e5736a1642b98d3c091262945c6e
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