QuanEstimation: An open-source toolkit for quantum parameter estimation

Quantum parameter estimation promises a high-precision measurement in theory; however, how to design the optimal scheme in a specific scenario, especially under a practical condition, is still a serious problem that needs to be solved case by case due to the existence of multiple mathematical bounds...

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Main Authors: Mao Zhang, Huai-Ming Yu, Haidong Yuan, Xiaoguang Wang, Rafał Demkowicz-Dobrzański, Jing Liu
Format: Article
Language:English
Published: American Physical Society 2022-10-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/PhysRevResearch.4.043057
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author Mao Zhang
Huai-Ming Yu
Haidong Yuan
Xiaoguang Wang
Rafał Demkowicz-Dobrzański
Jing Liu
author_facet Mao Zhang
Huai-Ming Yu
Haidong Yuan
Xiaoguang Wang
Rafał Demkowicz-Dobrzański
Jing Liu
author_sort Mao Zhang
collection DOAJ
description Quantum parameter estimation promises a high-precision measurement in theory; however, how to design the optimal scheme in a specific scenario, especially under a practical condition, is still a serious problem that needs to be solved case by case due to the existence of multiple mathematical bounds and optimization methods. Depending on the scenario considered, different bounds may be more or less suitable, both in terms of computational complexity and the tightness of the bound itself. At the same time, the metrological schemes provided by different optimization methods need to be tested against realization complexity, robustness, etc. Hence, a comprehensive toolkit containing various bounds and optimization methods is essential for the scheme design in quantum metrology. To fill this vacancy, here we present a Python-Julia-based open-source toolkit for quantum parameter estimation, which includes many well-used mathematical bounds and optimization methods. Utilizing this toolkit, all procedures in the scheme design, such as the optimizations of the probe state, control and measurement, can be readily and efficiently performed.
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spelling doaj.art-a2afbf31531949deaa612f8ed8ca509b2024-04-12T17:25:34ZengAmerican Physical SocietyPhysical Review Research2643-15642022-10-014404305710.1103/PhysRevResearch.4.043057QuanEstimation: An open-source toolkit for quantum parameter estimationMao ZhangHuai-Ming YuHaidong YuanXiaoguang WangRafał Demkowicz-DobrzańskiJing LiuQuantum parameter estimation promises a high-precision measurement in theory; however, how to design the optimal scheme in a specific scenario, especially under a practical condition, is still a serious problem that needs to be solved case by case due to the existence of multiple mathematical bounds and optimization methods. Depending on the scenario considered, different bounds may be more or less suitable, both in terms of computational complexity and the tightness of the bound itself. At the same time, the metrological schemes provided by different optimization methods need to be tested against realization complexity, robustness, etc. Hence, a comprehensive toolkit containing various bounds and optimization methods is essential for the scheme design in quantum metrology. To fill this vacancy, here we present a Python-Julia-based open-source toolkit for quantum parameter estimation, which includes many well-used mathematical bounds and optimization methods. Utilizing this toolkit, all procedures in the scheme design, such as the optimizations of the probe state, control and measurement, can be readily and efficiently performed.http://doi.org/10.1103/PhysRevResearch.4.043057
spellingShingle Mao Zhang
Huai-Ming Yu
Haidong Yuan
Xiaoguang Wang
Rafał Demkowicz-Dobrzański
Jing Liu
QuanEstimation: An open-source toolkit for quantum parameter estimation
Physical Review Research
title QuanEstimation: An open-source toolkit for quantum parameter estimation
title_full QuanEstimation: An open-source toolkit for quantum parameter estimation
title_fullStr QuanEstimation: An open-source toolkit for quantum parameter estimation
title_full_unstemmed QuanEstimation: An open-source toolkit for quantum parameter estimation
title_short QuanEstimation: An open-source toolkit for quantum parameter estimation
title_sort quanestimation an open source toolkit for quantum parameter estimation
url http://doi.org/10.1103/PhysRevResearch.4.043057
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AT haidongyuan quanestimationanopensourcetoolkitforquantumparameterestimation
AT xiaoguangwang quanestimationanopensourcetoolkitforquantumparameterestimation
AT rafałdemkowiczdobrzanski quanestimationanopensourcetoolkitforquantumparameterestimation
AT jingliu quanestimationanopensourcetoolkitforquantumparameterestimation