• Title
    Postdoctoral Researcher
  • Email
    fu9@llnl.gov
  • Phone
    (925) 424-5163
  • Organization
    Not Available

Yichen Fu is a theoretical and computational plasma physicist. He received his BS degree in physics from Zhejiang University (2017) and a PhD in plasma physics from Princeton University (2023). His PhD dissertation applied mathematical physics methods to study the topological and geometrical properties of waves in laboratory and space plasmas. He also worked on developing structure-preserving algorithms for collision operators and applying machine learning for fusion applications. He joined LLNL in 2023 as a postdoctoral researcher.

PhD, Plasma Physics, Princeton University, 2023

BS, Physics, Zhejiang University, 2017

Yichen Fu, I. Y. Dodin, and Hong Qin. Spin Hall effect of radiofrequency waves in magnetized plasmas. Physical Review E, 107(5):055210, 2023

Hong Qin and Yichen Fu. Topological Langmuir-cyclotron wave. Science Advances, 9(13): eadd8041, 2023

Yichen Fu and Hong Qin. The dispersion and propagation of topological Langmuir-cyclotron waves in cold magnetized plasmas. Journal of Plasma Physics, 88(4):835880401, 2022

Yichen Fu, Xin Zhang, and Hong Qin. An explicitly solvable energy-conserving algorithm for pitch-angle scattering in magnetized plasmas. Journal of Computational Physics, 449:110767, 2022

Hong Qin, Yichen Fu, Alexander S. Glasser, and Asher Yahalom. Spontaneous and explicit parity-time-symmetry breaking in drift-wave instabilities. Physical Review E, 104(1):015215, 2021

Yichen Fu and Hong Qin. Topological phases and bulk-edge correspondence of magnetized cold plasmas. Nature Communication, 12:3924, 2021

Xin Zhang, Yichen Fu, and Hong Qin. Simulating pitch angle scattering using an explicitly solvable energy-conserving algorithm. Physical Review E, 102(3):033302, 2020

Yichen Fu and Hong Qin. The physics of spontaneous parity-time symmetry breaking in the Kelvin–Helmholtz instability. New Journal of Physics, 22(8):083040, 2020

Yichen Fu, et. al., and Egemen Kolemen. Machine learning control for disruption and tearing mode avoidance. Physics of Plasmas, 27(2):022501, 2020