740 citations · 897 across the 7 of their papers we have counts for
7 papers
Adaptive Real-Time Magnetic Field Tracking beyond Prior Waveform Constraints
Yihan Wang, Xiaofeng Jin, Yuchuan Ming +4
The extraction of weak signals plays a crucial role in quantum precision measurement, where the estimation results are often limited by low signal-to-noise ratios. Here, we demonst…
Phase-coding quantum-key-distribution system based on Sagnac-Mach-Zehnder interferometers
Xiao-Tian Song, Dong Wang, Xiao-Ming Lu +6
Stability and robustness are important criteria to evaluate the performance of a quantum-key-distribution (QKD) system in real-life applications. However, the inherent birefringenc…
Generalized-mean Cramér-Rao Bounds for Multiparameter Quantum Metrology
Xiao-Ming Lu, Zhihao Ma, Chengjie Zhang
In multiparameter quantum metrology, the weighted-arithmetic-mean error of estimation is often used as a scalar cost function to be minimized during design optimization. However, o…
Quantum Fisher information matrix and multiparameter estimation
Jing Liu, Haidong Yuan, Xiao-Ming Lu +1
Quantum Fisher information matrix (QFIM) is a core concept in theoretical quantum metrology due to the significant importance of quantum Cramér-Rao bound in quantum parameter estim…
Quantum Weiss-Weinstein bounds for quantum metrology
Xiao-Ming Lu, Mankei Tsang
Sensing and imaging are among the most important applications of quantum information science. To investigate their fundamental limits and the possibility of quantum enhancements, r…
Robust quantum metrological schemes based on protection of quantum Fisher information
Xiao-Ming Lu, Sixia Yu, C. H. Oh
Fragile quantum features such as entanglement are employed to improve the precision of parameter estimation and as a consequence the quantum gain becomes vulnerable to noise. As an…
Improved Error-Tradeoff and Error-Disturbance Relations
Xiao-Ming Lu, Sixia Yu, Kazuo Fujikawa +1
Heisenberg's uncertainty principle is quantified by error-disturbance tradeoff relations, which have been tested experimentally in various scenarios. Here we shall report improved…