About
I am Yubing Qian, and my ID on GitHub is AllanChain.
Currently, I am a PhD student at Institute of Condensed Matter and Material Physics, School of Physics, Peking University. I am working on computational physics in Ji Chen's group, mainly interested in quantum Monte Carlo (QMC) with neural networks. I am also a intern at ByteDance Seed AI for Science, focusing on the same topic.
I'm a programming hobbyist and open source lover. My primary programming languages are Python and JavaScript. You can read more on my blog and my GitHub profile.
The page was last updated at September, 2025.
Education
Experience
Publications
- Y. Qian, T. Zhao, J. Zhang, T. Xiang, X. Li, and J. Chen, “Describing Landau Level Mixing in Fractional Quantum Hall States with Deep Learning,” Phys. Rev. Lett. 134, 176503 (2025).
- Y. Qian, X. Li, Z. Li, W. Ren, and J. Chen, “Deep Learning Quantum Monte Carlo for Solids,” WIREs Comput Mol Sci 15, e70015 (2025).
- Y. Qian, X. Li, and J. Chen, “Force and stress calculation with neural network wavefunction for solids,” Faraday Discuss. 254, 529 (2024).
- X. Li, Y. Qian, and J. Chen, “Electric Polarization from Many-Body Neural Network Ansatz,” Phys. Rev. Lett. 132, 176401 (2024).
- Y. Qian, W. Fu, W. Ren, and J. Chen, “Interatomic Force from Neural Network Based Variational Quantum Monte Carlo,” The Journal of Chemical Physics 157, 164104 (2022).