Machine learning enables completely automatic tuning of a quantum device faster than human experts
To optimize operating conditions of large scale semiconductor quantum devices, a large parameter space has to be explored. Here, the authors report a machine learning algorithm to navigate the entire parameter space of gate-defined quantum dot devices, showing about 180 times faster than a pure rand...
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| Auteurs principaux: | , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/dd86a9c2a00a4779a6625d51bea8a4a4 |
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