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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.12066 |
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| _version_ | 1866908310442082304 |
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| author | Yu, Huai-Ming Liu, Jing |
| author_facet | Yu, Huai-Ming Liu, Jing |
| contents | As the main theoretical support of quantum metrology, quantum parameter estimation must follow the steps of quantum metrology towards the applied science and industry. Hence, optimal scheme design will soon be a crucial and core task for quantum parameter estimation. To efficiently accomplish this task, software packages aimed at computer-aided design are in high demand. In response to this need, we hereby introduce QuanEstimation.jl, an open-source Julia framework for scheme evaluation and design in quantum parameter estimation. It can be used either as an independent package or as the computational core of the recently developed hybrid-language (Python-Julia) package QuanEstimation [Phys. Rev. Res. 4 (4) (2022) 043057]. Utilizing this framework, the scheme evaluation and design in quantum parameter estimation can be readily performed, especially when quantum noises exist. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_12066 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | QuanEstimation.jl: An open-source Julia framework for quantum parameter estimation Yu, Huai-Ming Liu, Jing Quantum Physics High Energy Physics - Theory Computational Physics As the main theoretical support of quantum metrology, quantum parameter estimation must follow the steps of quantum metrology towards the applied science and industry. Hence, optimal scheme design will soon be a crucial and core task for quantum parameter estimation. To efficiently accomplish this task, software packages aimed at computer-aided design are in high demand. In response to this need, we hereby introduce QuanEstimation.jl, an open-source Julia framework for scheme evaluation and design in quantum parameter estimation. It can be used either as an independent package or as the computational core of the recently developed hybrid-language (Python-Julia) package QuanEstimation [Phys. Rev. Res. 4 (4) (2022) 043057]. Utilizing this framework, the scheme evaluation and design in quantum parameter estimation can be readily performed, especially when quantum noises exist. |
| title | QuanEstimation.jl: An open-source Julia framework for quantum parameter estimation |
| topic | Quantum Physics High Energy Physics - Theory Computational Physics |
| url | https://arxiv.org/abs/2405.12066 |