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Journal article

Efficiently measuring a quantum device using machine learning

Abstract:

Scalable quantum technologies such as quantum computers will require very large numbers of quantum devices to be characterised and tuned. As the number of devices on chip increases, this task becomes ever more time-consuming, and will be intractable on a large scale without efficient automation. We present measurements on a quantum dot device performed by a machine learning algorithm in real time. The algorithm selects the most informative measurements to perform next by combining information...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41534-019-0193-4

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Publisher:
Springer Nature Publisher's website
Journal:
npj Quantum Information Journal website
Volume:
5
Article number:
79
Publication date:
2019-09-26
Acceptance date:
2019-08-22
DOI:
EISSN:
2056-6387
Source identifiers:
935453
Keywords:
Pubs id:
pubs:935453
UUID:
uuid:3f48fa13-0f72-41d0-b42d-e2341dfa5176
Local pid:
pubs:935453
Deposit date:
2019-03-19

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