Disorder effect of resonant spin Hall effect in a tilted magnetic field

We study the disorder effect of resonant spin Hall effect in a two-dimension electron system with Rashba coupling in the presence of a tilted magnetic field. The competition between the Rashba coupling and the Zeeman coupling leads to the energy crossing of the Landau levels, which gives rise to the resonant spin Hall effect. Utilizing the Streda's formula within the self-consistent Born approximation, we find that the impurity scattering broadens the energy levels, and the resonant spin Hall conductance exhibits a double peak around the resonant point, which is recovered in an applied titled magnetic field.Comment: 6 pages, 4 figure

Electric field modulation of topological order in thin film semiconductors

We propose a method that can consecutively modulate the topological orders or the number of helical edge states in ultrathin film semiconductors without a magnetic field. By applying a staggered periodic potential, the system undergoes a transition from a topological trivial insulating state into a non-trivial one with helical edge states emerging in the band gap. Further study demonstrates that the number of helical edge state can be modulated by the amplitude and the geometry of the electric potential in a step-wise fashion, which is analogous to tuning the integer quantum Hall conductance by a megntic field. We address the feasibility of experimental measurement of this topological transition.Comment: 4 pages, 4 figure

Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications

Networked video applications, e.g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth. In this paper, we have developed a Quality Enhancement Network (QENet) to reduce the video compression artifacts, leveraging the spatial and temporal priors generated by respective multi-scale convolutions spatially and warped temporal predictions in a recurrent fashion temporally. We have integrated this QENet as a standard-alone post-processing subsystem to the High Efficiency Video Coding (HEVC) compliant decoder. Experimental results show that our QENet demonstrates the state-of-the-art performance against default in-loop filters in HEVC and other deep learning based methods with noticeable objective gains in Peak-Signal-to-Noise Ratio (PSNR) and subjective gains visually