Active Learning for Quantum Mechanical Measurements
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2022
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| _version_ | 1866913380639440896 |
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| author | Zhu, Ruidi Pike-Burke, Ciara Mintert, Florian |
| author_facet | Zhu, Ruidi Pike-Burke, Ciara Mintert, Florian |
| contents | The experimental evaluation of many quantum mechanical quantities requires the estimation of several directly measurable observables, such as local observables. Due to the necessity to repeat experiments on individual quantum systems in order to estimate expectation values of observables, the question arises how many repetitions to allocate to a given directly measurable observable. We show that an active learning scheme can help to improve such allocations, and the resultant decrease in experimental repetitions required to evaluate a quantity with the desired accuracy increases with the size of the underlying quantum mechanical system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_07513 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Active Learning for Quantum Mechanical Measurements Zhu, Ruidi Pike-Burke, Ciara Mintert, Florian Quantum Physics The experimental evaluation of many quantum mechanical quantities requires the estimation of several directly measurable observables, such as local observables. Due to the necessity to repeat experiments on individual quantum systems in order to estimate expectation values of observables, the question arises how many repetitions to allocate to a given directly measurable observable. We show that an active learning scheme can help to improve such allocations, and the resultant decrease in experimental repetitions required to evaluate a quantity with the desired accuracy increases with the size of the underlying quantum mechanical system. |
| title | Active Learning for Quantum Mechanical Measurements |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2212.07513 |