Prediction and real-time compensation of qubit decoherence via machine learning
Control engineering techniques are promising for realizing stable quantum systems to counter their extreme fragility. Here the authors use techniques from machine learning to enable real-time feedback suppression of decoherence in a trapped ion qubit by predicting its future stochastic evolution.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2017-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/ncomms14106 |
| Summary: | Control engineering techniques are promising for realizing stable quantum systems to counter their extreme fragility. Here the authors use techniques from machine learning to enable real-time feedback suppression of decoherence in a trapped ion qubit by predicting its future stochastic evolution. |
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| ISSN: | 2041-1723 |