【时  间】 3月27日（周三） 上午 10:00

【地  点】 量子院320报告厅

【主  持】 张  江 （量子算法应用软件团队助理研究员）

【题  目】 QuanEstimation: An open-source toolkit for quantum parameter estimation

【摘  要】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.

【报告人简介】刘京：华中科技大学精密重力测量国家重大基础设施及物理学院副研究员。2015年博士毕业于浙江大学物理系。2015年至2017年在香港中文大学机械与自动化学院从事博士后研究。2018年1月加入华中科技大学引力中心任副研究员。2019年获得湖北省“楚天学子”称号。主要从事量子精密测量和量子参数估计理论、量子控制理论、量子信息理论、量子力学基本问题以及量子耗散相关问题等领域的研究。已发表论文三十余篇，谷歌学术总引用1700余次，单篇最高引用近五百次。曾获教育部2020年高等学校科学研究优秀成果奖（科学研究）二等奖，以及2022年IOP Publishing Top Cited Paper Award。