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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...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua: H. Moon, D. T. Lennon, J. Kirkpatrick, N. M. van Esbroeck, L. C. Camenzind, Liuqi Yu, F. Vigneau, D. M. Zumbühl, G. A. D. Briggs, M. A. Osborne, D. Sejdinovic, E. A. Laird, N. Ares
Hōputu: Artigo
Reo:Inglês
I whakaputaina: Nature Portfolio 2020-08-01
Rangatū:Nature Communications
Urunga tuihono:https://doi.org/10.1038/s41467-020-17835-9
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