文章基本信息

标题：Fitting magnetic field gradient with Heisenberg-scaling accuracy
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作者：Yong-Liang Zhang ; Huan Wang ; Li Jing 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2014
卷号：4
DOI：10.1038/srep07390
出版社：Springer Nature
摘要：The linear function is possibly the simplest and the most used relation appearing in various areas of our world. A linear relation can be generally determined by the least square linear fitting (LSLF) method using several measured quantities depending on variables. This happens for such as detecting the gradient of a magnetic field. Here, we propose a quantum fitting scheme to estimate the magnetic field gradient with N-atom spins preparing in W state. Our scheme combines the quantum multi-parameter estimation and the least square linear fitting method to achieve the quantum Cramér-Rao bound (QCRB). We show that the estimated quantity achieves the Heisenberg-scaling accuracy. Our scheme of quantum metrology combined with data fitting provides a new method in fast high precision measurements.