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.
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| Language: | English |
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Nature Publishing Group
2017-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/ncomms14106 |
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doaj-54fb8f67b9664aab884a9c4affc37390 |
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doaj-54fb8f67b9664aab884a9c4affc373902021-05-11T07:26:20ZengNature Publishing GroupNature Communications2041-17232017-01-01811610.1038/ncomms14106Prediction and real-time compensation of qubit decoherence via machine learningSandeep Mavadia0Virginia Frey1Jarrah Sastrawan2Stephen Dona3Michael J. Biercuk4ARC Centre for Engineered Quantum Systems, School of Physics, The University of SydneyARC Centre for Engineered Quantum Systems, School of Physics, The University of SydneyARC Centre for Engineered Quantum Systems, School of Physics, The University of SydneyARC Centre for Engineered Quantum Systems, School of Physics, The University of SydneyARC Centre for Engineered Quantum Systems, School of Physics, The University of SydneyControl 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.https://doi.org/10.1038/ncomms14106 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Sandeep Mavadia Virginia Frey Jarrah Sastrawan Stephen Dona Michael J. Biercuk |
| spellingShingle |
Sandeep Mavadia Virginia Frey Jarrah Sastrawan Stephen Dona Michael J. Biercuk Prediction and real-time compensation of qubit decoherence via machine learning Nature Communications |
| author_facet |
Sandeep Mavadia Virginia Frey Jarrah Sastrawan Stephen Dona Michael J. Biercuk |
| author_sort |
Sandeep Mavadia |
| title |
Prediction and real-time compensation of qubit decoherence via machine learning |
| title_short |
Prediction and real-time compensation of qubit decoherence via machine learning |
| title_full |
Prediction and real-time compensation of qubit decoherence via machine learning |
| title_fullStr |
Prediction and real-time compensation of qubit decoherence via machine learning |
| title_full_unstemmed |
Prediction and real-time compensation of qubit decoherence via machine learning |
| title_sort |
prediction and real-time compensation of qubit decoherence via machine learning |
| publisher |
Nature Publishing Group |
| series |
Nature Communications |
| issn |
2041-1723 |
| publishDate |
2017-01-01 |
| description |
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. |
| url |
https://doi.org/10.1038/ncomms14106 |
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