Adaptive quantum state tomography via linear regression estimation: Theory and two-qubit experiment
Quantum tomography: Adaptivity improves precision Quantum state tomography is an essential task in the development of quantum technology. The key problem is to find a strategy that has a high level of estimation accuracy and is easy to experimentally implement. A group of international scientists fr...
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| Autores principales: | , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2017
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/cf74ecd82e854942a2f3282b5168091b |
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| Sumario: | Quantum tomography: Adaptivity improves precision Quantum state tomography is an essential task in the development of quantum technology. The key problem is to find a strategy that has a high level of estimation accuracy and is easy to experimentally implement. A group of international scientists from China and Australia presented, and experimentally tested, such a strategy, called recursively adaptive quantum state tomography (RAQST). In RAQST, no prior assumption on the state is made. Numerical results show that RAQST, even with the simplest product measurements, outperforms other proposed protocols wherein nonlocal measurements are involved. With error-compensation techniques, the authors experimentally demonstrated its superiority for two-qubit optical tomography. RAQST is particularly effective when reconstructing states with high purity, which are important resources in quantum information. Their method offers a new basis for designing effective approaches for determining a quantum state and can be widely used in quantum information experiments. |
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