Quantum device fine-tuning using unsupervised embedding learning

Quantum devices with a large number of gate electrodes allow for precise control of device parameters. This capability is hard to fully exploit due to the complex dependence of these parameters on applied gate voltages. We experimentally demonstrate an algorithm capable of fine-tuning several device...

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書誌詳細

出版年:	New Journal of Physics
主要な著者:	N M van Esbroeck, D T Lennon, H Moon, V Nguyen, F Vigneau, L C Camenzind, L Yu, D M Zumbühl, G A D Briggs, D Sejdinovic, N Ares
フォーマット:	論文
言語:	英語
出版事項:	IOP Publishing 2020-01-01
主題:	quantum devices machine learning automatic tuning variational auto-encoder
オンライン･アクセス:	https://doi.org/10.1088/1367-2630/abb64c