2014/01/21 by Yong-Liang Zhang, Huan Wang, Li Jing +2
Computer Science · Physics and Astronomy · #Curve fitting #Field (mathematics) #Function (biology) #Magnetic field #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum and electron transport phenomena #Quantum metrology #Spins #Square (algebra) #quant-ph
paper · pdf · doi:10.1038/srep07390
published as Scientific Reports 4, 7390 (2014) · 7 pages, 2 figures
arxiv created 2014/01/21 · openalex publication_date 2014/12/09 · arxiv updated 2014/12/30 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06
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.