Spin transverse force and intrinsic quantum transverse transport

The spin-orbit coupling may generate spin transverse force on moving electron spin, which gives a heuristic picture for the quantum transverse transport of electron. A relation between the spin and anomalous Hall conductance and spin force was established, and applied to several systems. It was predicted that the sign change of anomalous Hall conductance can occur in diluted magnetic semiconductors of narrow band and can be applied to identify intrinsic mechanism experimentally

Magnetic Janus Particles and Their Applications

Magnetic properties are important since they enable the manipulation of particle behavior remotely and therefore provide the means to direct a particle’s orientation and translation. Magnetic Janus particles combine magnetic properties with anisotropy and thus are potential building blocks for complex structures that can be assembled from a particle suspension and can be directed through external fields. In this thesis, a method for the fabrication of three types of magnetic Janus particles with distinct magnetic properties is introduced, the assembly behavior of magnetic Janus particles in external magnetic and electric fields is systematically studied, and two potential applications of magnetic Janus particles are successfully tested. Janus particles with different magnetic properties are fabricated by varying the deposition rate of iron in an Ar/O2 atmosphere using physical vapor deposition (PVD). The extent of oxidation for each type of iron oxide is precisely controlled by the time it is exposed to the Ar/O2 atmosphere during deposition. Two of the three magnetic Janus particles produced show distinct assembly behavior into staggered and double chain structures, whereas the third shows no assembly behavior under an external magnetic field. The effect of the iron oxide cap thickness (≤ 50 nm) on the Janus particle assembly behavior is studied resulting in a deposition rate diagram that shows the relationship between the assembly behavior and the deposition rate. The cap materials for staggered chain, double chain, and no assembly behavior are assigned as Fe1-xO, Fe3O4, and Fe2O3, respectively, based on optical appearance and physical properties. The assignment is further confirmed by in-depth material characterization with scanning and transmission electron microscopy, atomic force microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The magnetic hardness of the iron oxides is tested using the magneto-optic Kerr effect. The assembly behavior of Fe3O4-capped Janus particles is studied in overlapping parallel and perpendicular AC electric and magnetic fields. The chains formed by Fe3O4-capped magnetic Janus particles show contraction behavior of ~30%, which suggests their application as an in situ viscometer. The chain contraction rate is found to depend on the viscosity of the liquid as well as the size of Janus particles and an in situ microviscometer is realized. Further, the magnetic dipole-dipole interactions of Fe1-xO and Fe3O4-capped Janus particles are studied by analyzing the particle-particle interaction force and energy during the process of Janus particle doublet formation. Using the magnetic particle interaction energy, the magnetization of each iron oxide cap is determined and found to be in excellent agreement with magnetization values obtained using standard SQUID measurements suggesting the application of magnetic Janus particles as a micro-magnetometer. In summary, three types of magnetic Janus particles with distinct magnetic properties have been fabricated and show versatile assembly behaviors that make them useful basic building blocks for complex structures and applications. For example, magnetic Janus particles can be used to measure the viscosity of a fluid or the magnetic property of a thin film cap material. It is likely that other interesting applications will emerge, when Janus particles of various sizes and/or patchy particles with magnetic properties are combined and explored

SBNet: Sparse Blocks Network for Fast Inference

Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications. For many problems such as object detection and semantic segmentation, we are able to obtain a low-cost computation mask, either from a priori problem knowledge, or from a low-resolution segmentation network. We show that such computation masks can be used to reduce computation in the high-resolution main network. Variants of sparse activation CNNs have previously been explored on small-scale tasks and showed no degradation in terms of object classification accuracy, but often measured gains in terms of theoretical FLOPs without realizing a practical speed-up when compared to highly optimized dense convolution implementations. In this work, we leverage the sparsity structure of computation masks and propose a novel tiling-based sparse convolution algorithm. We verified the effectiveness of our sparse CNN on LiDAR-based 3D object detection, and we report significant wall-clock speed-ups compared to dense convolution without noticeable loss of accuracy.Comment: 10 pages, CVPR 201