Essential Information

Name   Xiaodong Yang

PositionPostdoc          

Highest DegreeDoctor of Philosophy in Physics

Telephoneoffice):18788836543

OfficeRoom 103, Building 10, Innovation Park

Emailyangxd@sustech.edu.cn

Research FieldQuantum control;Spin-based quantum information processing

 

Educational Background

2010.09-2014.06,  Particle Physics and Nuclear Physics, Department of Modern Physics, University of Science and Technology of China (Bachelor)

2014.09-2020.07, Quantum Information Science, Department of Modern Physics, University of Science and Technology of China (Doctor)

 

Working Experience

2020.09- present  Institute for Quantum Science and Engineering and Department of Physics, Southern University of Science and Technology

 

Papers and Patents

(1) Xiaodong Yang, Xi Chen, Jun Li, Xinhua Peng, and Raymond Laflamme. Hybrid quantum-classical approach to enhanced quantum metrology[J]. arXiv preprint arXiv:2008.06466, 2020.

(1) Xiaodong Yang, Jayne Thompson, Mile Gu, et al. Probe optimization for quantum metrology via closed-loop learning control. npj Quantum Information, 2020, 6(1): 1-7. 

(2) Xiaodong Yang, Ran Liu, Jun Li, Xinhua Peng, Optimizing adiabatic quantum pathways via a learning algorithm. Physical Review A, 2020, 102(1): 012614.

(3) XiaodongYang, Christian Arenz, Istvan Pelczer, Qi-Ming Chen, Re-Bing Wu, Xinhua Peng and Herschel Rabitz. Assessing three closed-loop learning algorithms by searching for high-quality quantum control pulses. Physical Review A, 2020, 102(6): 062605.

(4) Xiaodong Yang, Jun Li, Xinhua Peng. An improved differential evolution algorithm for learning high-fidelity quantum controls. Science Bulletin, 2019, 64(19): 1402-1408.

(5) Jun Li, Xiaodong Yang, Xinhua Peng, ChangPu Sun, Hybrid Quantum-Classical Approach to Quantum Optimal Control. Physical Review Letters, 2017, 118(15): 150503.

(6) Qi-Ming Chen, XiaodongYang, Christian Arenz, Re-Bing Wu, Xinhua Peng, Istvan Pelczer and Herschel Rabitz.  Combining the synergistic control capabilities of modeling and experiments: Illustration of finding a minimum-time quantum objective. Physical Review A, 2020, 101(3): 032313.