Learning symmetry-protected topological order from trapped-ion experiments
Classical machine learning has proven remarkably useful in post-processing quantum data, yet typical learning algorithms often require prior training to be effective. In this work, we employ a tensorial kernel support vector machine (TK-SVM) to analyze experimental data produced by trapped-ion quant...
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| Principais autores: | , , , , , , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2026-05-01
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| Serier: | Quantum |
| Online adgang: | https://quantum-journal.org/papers/q-2026-05-12-2100/pdf/ |
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