Machine learning enables completely automatic tuning of a quantum device faster than human experts
Device variability is a bottleneck for the scalability of semiconductor quantum devices. Increasing device control comes at the cost of a large parameter space that has to be explored in order to find the optimal operating conditions. We demonstrate a statistical tuning algorithm that navigates this...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2020
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