Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design

Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design

Artificial intelligence (AI) technology leads to new insights into the manipulation of quantum systems in the Noisy Intermediate-Scale Quantum (NISQ) era. Classical agent-based artificial intelligence algorithms provide a framework for the design or control of quantum systems. Traditional reinforcem...

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Bibliographic Details
Main Authors: Tomah Sogabe, Tomoaki Kimura, Chih-Chieh Chen, Kodai Shiba, Nobuhiro Kasahara, Masaru Sogabe, Katsuyoshi Sakamoto
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Quantum Reports
Subjects:
quantum circuits
reinforcement learning
Q-learning
LSTM
Online Access:https://www.mdpi.com/2624-960X/4/4/27

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