姓名: 杨晓东
电子邮箱: yangxd@szu.edu.cn
谷歌学术: [URL]
研究方向
量子控制;
量子精密测量;
量子计算与量子模拟;
教育经历
2010 - 2014 物理学学士学位
中国科学技术大学 近代物理系
2014 - 2020 物理学博士学位
中国科学技术大学 近代物理系
指导老师: 彭新华教授
工作经历
2020 - 2022 博士后
南方科技大学 量子科学与工程研究院
2022 - 2023 研究助理教授
南方科技大学 量子科学与工程研究院
2023 - 今 助理教授
深圳大学 物理与光电工程学院
科研成果
1. X. Yang, J. Li†, and X. Peng†, An improved differential evolution algorithm for learning high-fidelity quantum controls, Sci. Bull. 64, 1402 (2019). [URL]
2. X. Yang, R. Liu, J. Li†, and X. Peng†, Optimizing adiabatic quantum pathways via a learning algorithm, Phys. Rev. A 102, 012614 (2020). [URL]
3. X. Yang, J. Thompson, Z. Wu, M. Gu†, X. Peng†, and J. Du, Probe optimization for quantum metrology via closed-loop learning control, npj Quantum Inf. 6, 62 (2020). [URL]
4. X. Yang, C. Arenz, I. Pelczer, Q.-M. Chen, R.-B. Wu†, X. Peng†, and H. Rabitz†, Assessing three closed-loop learning algorithms by searching for high-quality quantum control pulses, Phys. Rev. A 102, 062605 (2020). [URL]
5. X. Yang*, X. Chen*, J. Li†, X. Peng†, and R. Laflamme, Hybrid quantum-classical approach to enhanced quantum metrology, Sci. Rep. 11, 1 (2021). [URL]
6. X. Yang, Y. Ge, B. Zhang†, and J. Li†, Robust Dynamical Decoupling for the Manipulation of a Spin Network Via a Single Spin, Phys. Rev. Appl. 18, 054075 (2022). [URL]
7. X. Yang, X. Nie, Y. Ji, T. Xin, D. Lu†, and J. Li†, Improved quantum computing with higher- order Trotter decomposition, Phys. Rev. A 106, 042401 (2022). [URL]
8. Y. Zhai, X. Yang†, K. Tang, X. Long, X. Nie, T. Xin, D. Lu, and J. Li†, Control-enhanced quantum metrology under Markovian noise, Phys. Rev. A 107, 022602 (2023). [URL]
9. Y. Zhang∗, H. Wu∗, X. Yang∗, T. Xie, Y.-X. Wang, C. Liu, Q. Zhao, J. Ma†, J. Li†, and B. Zhang†, Robust Quantum Control for the Manipulation of Solid-State Spins, Phys. Rev. Appl. 19, 034068 (2023). [URL]
10. H. Liu, X. Yang†, K. Tang, L. Che, X. Nie, T. Xin, J. Li, and D. Lu†, Practical quantum simulation of small-scale non-Hermitian dynamics, Phys. Rev. A 107, 062608 (2023). [URL]