基本信息

姓名：杨晓东

职称：博士后

电 话（办公室）：18788836543

研究领域： 量子控制;自旋量子信息处理

教育背景

2010.09-2014.06 中国科学技术大学近代物理系粒子物理与原子核物理专业（本科）

2014.09-2020.07 中国科学技术大学近代物理系量子信息物理学专业（博士）

工作经历

2020.09—至今 深圳量子科学与工程研究院

论文及专利

(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.

(2) 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.

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

(4) 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.

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

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

(7) 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.