Electromagnetic counterparts of high-frequency gravitational waves having additional polarization states: distinguishing and probing tensor-mode, vector-mode and scalar-mode gravitons

GWs from extra dimensions, very early universe, and some high-energy astrophysical process, might have at most six polarizations: plus- and cross-type (tensor-mode gravitons), x-, y-type (vector-mode), and b-, l-type (scalar-mode). Peak or partial peak regions of some of such GWs are just distributed in GHz or higher frequency band, which would be optimal band for electromagnetic(EM) response. In this paper we investigate EM response to such high-frequency GWs(HFGWs) having additional polarizations. For the first time we address:(1)concrete forms of analytic solutions for perturbed EM fields caused by HFGWs having all six possible polarizations in background stable EM fields; (2)perturbed EM signals of HFGWs with additional polarizations in three-dimensional-synchro-resonance-system(3DSR system) and in galactic-extragalactic background EM fields. These perturbative EM fields are actually EM counterparts of HFGWs, and such results provide a novel way to simultaneously distinguish and display all possible six polarizations. It is also shown: (i)In EM response, pure cross-, x-type and pure y-type polarizations can independently generate perturbative photon fluxes(PPFs, signals), while plus-, b- and l-type polarizations produce PPFs in different combination states. (ii) All such six polarizations have separability and detectability. (iii)In EM response to HFGWs from extra-dimensions, distinguishing and displaying different polarizations would be quite possible due to their very high frequencies, large energy densities and special properties of spectrum. (iv)Detection band(10^8 to 10^12 Hz or higher) of PPFs by 3DSR and observation range(7*10^7 to 3*10^9 Hz) of PPFs by FAST (Five-hundred-meter-Aperture-Spherical Telescope, China), have a certain overlapping property, so their coincidence experiments will have high complementarity.Comment: 27 pages, 16 figure

Quasi-two-body decays B→DK∗(892)→DKπB \to D K^*(892) \to D K \pi in the perturbative QCD approach

We study the quasi-two-body decays $B\to D K^*(892) \to D K\pi$ by employing the perturbative QCD approach. The two-meson distribution amplitudes \Phi_{K\pi}^{\text{P-wave}} are adopted to describe the final state interactions of the kaon-pion pair in the resonance region. The resonance line shape for the $P$-wave $K\pi$ component $K^*(892)$ in the time-like form factor $F_{K\pi}(s)$ is parameterized by the relativistic Breit-Wigner function. For most considered decay modes, the theoretical predictions for their branching ratios are consistent with currently available experimental measurements within errors. We also disscuss some ratios of the branching fractions of the concerned decay processes. More precise data from LHCb and Belle-II are expected to test our predictions.Comment: 10 pages, 3 figures and 2 tables.To be published in EPJ

Single-Shot Refinement Neural Network for Object Detection

For object detection, the two-stage approach (e.g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e.g., SSD) has the advantage of high efficiency. To inherit the merits of both while overcoming their disadvantages, in this paper, we propose a novel single-shot based detector, called RefineDet, that achieves better accuracy than two-stage methods and maintains comparable efficiency of one-stage methods. RefineDet consists of two inter-connected modules, namely, the anchor refinement module and the object detection module. Specifically, the former aims to (1) filter out negative anchors to reduce search space for the classifier, and (2) coarsely adjust the locations and sizes of anchors to provide better initialization for the subsequent regressor. The latter module takes the refined anchors as the input from the former to further improve the regression and predict multi-class label. Meanwhile, we design a transfer connection block to transfer the features in the anchor refinement module to predict locations, sizes and class labels of objects in the object detection module. The multi-task loss function enables us to train the whole network in an end-to-end way. Extensive experiments on PASCAL VOC 2007, PASCAL VOC 2012, and MS COCO demonstrate that RefineDet achieves state-of-the-art detection accuracy with high efficiency. Code is available at https://github.com/sfzhang15/RefineDetComment: 14 pages, 7 figures, 7 table

Nearly Optimal Stochastic Approximation for Online Principal Subspace Estimation

Processing streaming data as they arrive is often necessary for high dimensional data analysis. In this paper, we analyse the convergence of a subspace online PCA iteration, as a followup of the recent work of Li, Wang, Liu, and Zhang [Math. Program., Ser. B, DOI 10.1007/s10107-017-1182-z] who considered the case for the most significant principal component only, i.e., a single vector. Under the sub-Gaussian assumption, we obtain a finite-sample error bound that closely matches the minimax information lower bound of Vu and Lei [Ann. Statist. 41:6 (2013), 2905-2947].Comment: 37 page