Quantum anomalous vortex and Majorana zero mode in iron-based superconductor Fe(Te,Se)

In topological insulators doped with magnetic ions, spin-orbit coupling and ferromagnetism give rise to the quantum anomalous Hall effect. Here we show that in s-wave superconductors with strong spin-orbit coupling, magnetic impurity ions can generate topological vortices in the absence of external magnetic fields. Such vortices, dubbed quantum anomalous vortices, support robust Majorana zero-energy modes when superconductivity is induced in the topological surface states. We demonstrate that the zero-energy bound states observed in Fe(Te,Se) superconductors are possible realizations of the Majorana zero modes in quantum anomalous vortices produced by the interstitial magnetic Fe. The quantum anomalous vortex matter not only advances fundamental understandings of topological defect excitations of Cooper pairing, but also provides new and advantageous platforms for manipulating Majorana zero modes in quantum computing.Comment: final version, 8 pages, 3 figures + supplemental materia

YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection

Designing a real-time framework for the spatio-temporal action detection task is still a challenge. In this paper, we propose a novel real-time action detection framework, YOWOv2. In this new framework, YOWOv2 takes advantage of both the 3D backbone and 2D backbone for accurate action detection. A multi-level detection pipeline is designed to detect action instances of different scales. To achieve this goal, we carefully build a simple and efficient 2D backbone with a feature pyramid network to extract different levels of classification features and regression features. For the 3D backbone, we adopt the existing efficient 3D CNN to save development time. By combining 3D backbones and 2D backbones of different sizes, we design a YOWOv2 family including YOWOv2-Tiny, YOWOv2-Medium, and YOWOv2-Large. We also introduce the popular dynamic label assignment strategy and anchor-free mechanism to make the YOWOv2 consistent with the advanced model architecture design. With our improvement, YOWOv2 is significantly superior to YOWO, and can still keep real-time detection. Without any bells and whistles, YOWOv2 achieves 87.0 % frame mAP and 52.8 % video mAP with over 20 FPS on the UCF101-24. On the AVA, YOWOv2 achieves 21.7 % frame mAP with over 20 FPS. Our code is available on https://github.com/yjh0410/YOWOv2

EXPERIMENTAL AND NUMERICAL INVESTIGATION ON MANEUVERING PERFORMANCE OF SMALL WATERPLANE AREA TWIN HULL

Free running model tests and a system-based method are employed to evaluate maneuvering performance for a Small Waterplane Area Twin Hull (SWATH) ship in this paper. A 3 degrees of freedom Maneuvering Modeling Group (MMG) model is implemented to numerically simulate the maneuvering motions in calm water. Virtual captive model tests are performed by using a Reynolds-averaged Navier-Stokes (RANS) method to acquire hydrodynamic derivatives, after a convergence study to check the numerical accuracy. The turning and zigzag maneuvers are simulated by solving the maneuvering motion model and the predicted results agree well with the experimental data. Moreover, free running model tests are carried out for three lateral separations and the influence of the lateral separations on maneuvering performance is investigated. The research results of this paper will be helpful for the maneuvering prediction of the small waterplane area twin hull ship

Pre-merger electromagnetic counterparts of binary compact stars

We investigate emission signatures of binary compact star gravitational wave sources consisting of strongly magnetized neutron stars (NSs) and/or white dwarfs (WDs) in their late-time inspiral phase. Because of electromagnetic interactions between the magnetospheres of the two compact stars, a substantial amount of energy will be extracted, and the resultant power is expected to be $\sim 10^{38} - 10^{44}$ erg/s in the last few seconds before the two stars merge, when the binary system contains a NS with a surface magnetic field $10^{12}$ G. The induced electric field in the process can accelerate charged particles up to the EeV energy range. Synchrotron radiation is emitted from energetic electrons, with radiative energies reaching the GeV energy for binary NSs and the MeV energy for NS - WD or double WD binaries. In addition, a blackbody component is also presented and it peaks at several to hundreds keV for binary NSs and at several keV for NS - WD or double WD binaries. The strong angular dependence of the synchrotron radiation and the isotropic nature of the blackbody radiation lead to distinguishable modulation patterns between the two emission components. If coherent curvature radiation is presented, fast radio bursts could be produced. These components provide unique simultaneous electromagnetic signatures as precursors of gravitational wave events associated with magnetized compact star mergers and short gamma ray bursts (e.g., GRB 100717).Comment: 16 pages, 8 figures, 1 table. Minor corrections to match the version on Ap

PoNA: Pose-guided non-local attention for human pose transfer

Human pose transfer, which aims at transferring the appearance of a given person to a target pose, is very challenging and important in many applications. Previous work ignores the guidance of pose features or only uses local attention mechanism, leading to implausible and blurry results. We propose a new human pose transfer method using a generative adversarial network (GAN) with simplified cascaded blocks. In each block, we propose a pose-guided non-local attention (PoNA) mechanism with a long-range dependency scheme to select more important regions of image features to transfer. We also design pre-posed image-guided pose feature update and post-posed pose-guided image feature update to better utilize the pose and image features. Our network is simple, stable, and easy to train. Quantitative and qualitative results on Market-1501 and DeepFashion datasets show the efficacy and efficiency of our model. Compared with state-of-the-art methods, our model generates sharper and more realistic images with rich details, while having fewer parameters and faster speed. Furthermore, our generated images can help to alleviate data insufficiency for person re-identification