Quanestimation.jl: An open-source Julia framework for quantum parameter estimation

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.

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Publication Details

Journal
Fundamental Research
Published
2025-03-01
DOI
https://doi.org/10.1016/j.fmre.2025.02.020
Citations
3
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
7.44

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article

Quanestimation.jl: An open-source Julia framework for quantum parameter estimation

Huai-Ming Yu, Jing Liu
3 citations
Fundamental Research
Quantum Information and Cryptography
7.44
article

Quanestimation.jl: An open-source Julia framework for quantum parameter estimation

Huai-Ming Yu, Jing Liu
article en
3 citations

Abstract

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.

Fundamental Research
Hainan University (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Quantum Information and Cryptography
7.44
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