4,661 research outputs found
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
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