Hidden persistent spin texture in bulk crystals

Exploring hidden effects that have been overlooked given the nominal global crystal symmetry but are indeed visible in solid-state materials has been a fascinating subject of research recently. Here, we introduce a novel type of hidden persistent spin texture (HPST) in nonmagnetic bulk crystals consisting of a pair of real-space sectors. In these crystals, the doubly degenerate bands formed in the momentum space can exhibit a uniform spin configuration with opposite spin orientations, which are spatially separated in the paired sectors. Interestingly, we find that such a type of spin texture can be hidden in both centrosymmetric and non-centrosymmetric materials. We further demonstrate the important role of nonsymmorphic twofold screw-rotational symmetry played in the formation of HPST. Moreover, two representative material examples, i.e., centrosymmetric WSe$_2$ and noncentrosymmetric BaBi$_4$O$_7$, are identified to show HPST via first-principles calculations. Our finding thus not only opens new perspectives for hidden spin polarization research but also significantly broadens the range of materials towards spintronics applications.Comment: 5 pages, 3 figure

(Bis{2-[3-(2,4,6-trimethyl­benz­yl)imid­azolin-2-yliden-1-yl-κC 2]-4-methyl­phenyl}amido-κN)chloridopalladium(II)

The coordination geometry about the Pd centre in the title compound, [Pd(C40H42N5)Cl], is approximately square-planar. The CNC pincer-type N-heterocyclic carbene ligand binds to the Pd atom in a tridentate fashion by the amido N atom and the two carbene atoms and generates two six-membered chelate rings, completing the coordination

Reconfigurable Intelligent Surfaces Aided mmWave NOMA: Joint Power Allocation,Phase Shifts, and Hybrid Beamforming Optimization

In this paper, an reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) non-orthogonal multiple access (NOMA) system is considered. In particular, we consider an RIS-aided mmWave-NOMA downlink system with a hybrid beamforming structure. To maximize the achievable sum-rate under a minimum rate constraint for the users and a minimum transmit power constraint, a joint RIS phase shifts, hybrid beamforming, and power allocation problem is formulated. To solve this non-convex optimization problem, we develop an alternating optimization algorithm. Specifically, first, the non-convex problem is transformed into three subproblems, i.e., power allocation, joint phase shifts and analog beamforming optimization, and digital beamforming design. Then, we solve the power allocation problem under fixed phase shifts of the RIS and hybrid beamforming. Finally, given the power allocation matrix, an alternating manifold optimization (AMO)-based method and a successive convex approximation (SCA)-based method are utilized to design the phase shifts, analog beamforming, and transmit beamforming, respectively. Numerical results reveal that the proposed alternating optimization algorithm outperforms state-of-the-art schemes in terms of sum-rate. Moreover, compared to a conventional mmWave-NOMA system without RIS, the proposed RIS-aided mmWave-NOMA system is capable of improving the achievable sum-rate of the system

Towards Real-Time Neural Video Codec for Cross-Platform Application Using Calibration Information

The state-of-the-art neural video codecs have outperformed the most sophisticated traditional codecs in terms of RD performance in certain cases. However, utilizing them for practical applications is still challenging for two major reasons. 1) Cross-platform computational errors resulting from floating point operations can lead to inaccurate decoding of the bitstream. 2) The high computational complexity of the encoding and decoding process poses a challenge in achieving real-time performance. In this paper, we propose a real-time cross-platform neural video codec, which is capable of efficiently decoding of 720P video bitstream from other encoding platforms on a consumer-grade GPU. First, to solve the problem of inconsistency of codec caused by the uncertainty of floating point calculations across platforms, we design a calibration transmitting system to guarantee the consistent quantization of entropy parameters between the encoding and decoding stages. The parameters that may have transboundary quantization between encoding and decoding are identified in the encoding stage, and their coordinates will be delivered by auxiliary transmitted bitstream. By doing so, these inconsistent parameters can be processed properly in the decoding stage. Furthermore, to reduce the bitrate of the auxiliary bitstream, we rectify the distribution of entropy parameters using a piecewise Gaussian constraint. Second, to match the computational limitations on the decoding side for real-time video codec, we design a lightweight model. A series of efficiency techniques enable our model to achieve 25 FPS decoding speed on NVIDIA RTX 2080 GPU. Experimental results demonstrate that our model can achieve real-time decoding of 720P videos while encoding on another platform. Furthermore, the real-time model brings up to a maximum of 24.2\% BD-rate improvement from the perspective of PSNR with the anchor H.265.Comment: 14 page