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Quantum phase detection generalization from marginal quantum neural network models
Quantum machine learning offers a promising advantage in extracting information about quantum states, e.g., phase diagram. However, access to training labels is a major bottleneck for any supervised approach, preventing getting insights about new physics. In this Letter, using quantum convolutional...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1103/PhysRevB.107.L081105 http://cds.cern.ch/record/2848944 |