Bootstrapping quantum process tomography via a perturbative ansatz
Quantum process tomography represents one of the workhorses of quantum information processing, but suffers from exponential resource scaling. Here, the authors propose to efficiently infer general processes by approximating them through a sequence of two-qubit processes, and demonstrate it on a thre...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/04158d734a05489c9f7057b405121fd3 |
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| Sumario: | Quantum process tomography represents one of the workhorses of quantum information processing, but suffers from exponential resource scaling. Here, the authors propose to efficiently infer general processes by approximating them through a sequence of two-qubit processes, and demonstrate it on a three-qubit case. |
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