DJpsiFDC: an event generator for the process gg→J/ψJ/ψgg\to J/\psi J/\psi at LHC

DJpsiFDC is an event generator package for the process $gg\to J/\psi J/\psi$. It generates events for primary leading-order $2\to 2$ processes. The package could generate a LHE document and this document could easily be embedded into detector simulation software frameworks. The package is produced in Fortran codes.Comment: 10 pages, 3 figure

Exploring Bosonic Mediator of Interaction at BESIII

We present a comprehensive investigation on the possibility of the search for new force mediator $X$ boson in $e^+e^-$ collision and $J/\psi$ decay at the BESIII experiment. The typical interactions of $X$ boson coupling to leptons and quarks are explored. The production and decay properties of this $X$ particle, the product/decay chains $e^+e^-\to X\gamma \to e^+e^-\gamma$ and $J/\psi \to X\gamma\to\mu^+\mu^-\gamma$, and exclusion limits on the reduced coupling strength parameters as functions of $X$ boson mass are presented. With the data set of tens of fb$^{-1}~e^+e^-$ or $10^{10}~J/\psi$, we find that the exclusion limits on the coupling strength parameters fall in the range of $10^{-3}\sim10^{-4}$, depending on $m_X$ assuming the decay width 10 eV$<\Gamma_X<$100 eV reasonably, for various hypotheses in the literature. According to our estimation, the search for new force mediator $X$ boson in both $e^+e^-$ collision and $J/\psi$ decay are accessible in nowadays BESIII experiment.Comment: To appear in EPJC; 26 pages, 13 figures; Fig.s (5, 6, 9, 11, 12, 13) are reploted and their discussion are updated; three paragraphs, two equations and 1 table are added; two errors are correcte

Increasing Compression Ratio of Low Complexity Compressive Sensing Video Encoder with Application-Aware Configurable Mechanism

With the development of embedded video acquisition nodes and wireless video surveillance systems, traditional video coding methods could not meet the needs of less computing complexity any more, as well as the urgent power consumption. So, a low-complexity compressive sensing video encoder framework with application-aware configurable mechanism is proposed in this paper, where novel encoding methods are exploited based on the practical purposes of the real applications to reduce the coding complexity effectively and improve the compression ratio (CR). Moreover, the group of processing (GOP) size and the measurement matrix size can be configured on the encoder side according to the post-analysis requirements of an application example of object tracking to increase the CR of encoder as best as possible. Simulations show the proposed framework of encoder could achieve 60X of CR when the tracking successful rate (SR) is still keeping above 90%.Comment: 5 pages with 6figures and 1 table,conferenc

BcB_c Exclusive Decays to Charmonium and a Light Meson at Next-to-Leading Order Accuracy

In this paper the next-to-leading order (NLO) corrections to $B_c$ meson exclusive decays to S-wave charmonia and light pseudoscalar or vector mesons, i.e. $\pi$, $K$, $\rho$, and $K^*$, are performed within non-relativistic (NR) QCD approach. The non-factorizable contribution is included, which is absent in traditional naive factorization (NF). And the theoretical uncertainties for their branching ratios are reduced compared with that of direct tree level calculation. Numerical results show that NLO QCD corrections markedly enhance the branching ratio with a K factor of 1.75 for $B_{c}^{\pm}\to \eta_{c} \pi^{\pm}$ and 1.31 for $B_{c}^{\pm}\to J/\psi \pi^{\pm}$. In order to investigate the asymptotic behavior, the analytic form is obtained in the heavy quark limit, i.e. $m_b \to \infty$. We note that annihilation topologies contribute trivia in this limit, and the corrections at leading order in $z= m_c/m_b$ expansion come from form factors and hard spectator interactions. At last, some related phenomenologies are also discussed.Comment: 20 pages, 7 figures and 5 table

Exploring Temporal Preservation Networks for Precise Temporal Action Localization

Temporal action localization is an important task of computer vision. Though a variety of methods have been proposed, it still remains an open question how to predict the temporal boundaries of action segments precisely. Most works use segment-level classifiers to select video segments pre-determined by action proposal or dense sliding windows. However, in order to achieve more precise action boundaries, a temporal localization system should make dense predictions at a fine granularity. A newly proposed work exploits Convolutional-Deconvolutional-Convolutional (CDC) filters to upsample the predictions of 3D ConvNets, making it possible to perform per-frame action predictions and achieving promising performance in terms of temporal action localization. However, CDC network loses temporal information partially due to the temporal downsampling operation. In this paper, we propose an elegant and powerful Temporal Preservation Convolutional (TPC) Network that equips 3D ConvNets with TPC filters. TPC network can fully preserve temporal resolution and downsample the spatial resolution simultaneously, enabling frame-level granularity action localization. TPC network can be trained in an end-to-end manner. Experiment results on public datasets show that TPC network achieves significant improvement on per-frame action prediction and competing results on segment-level temporal action localization