Implications on η\eta-η′\eta'-glueball mixing from Bd/s→J/Ψη(′)B_{d/s} \to J/\Psi \eta^{(')} Decays

We point out that the recent Belle measurements of the $B_{d/s} \to J/\Psi \eta^{(')}$ decays imply large pseudoscalar glueball contents in the $\eta^{(\prime)}$ meson. These decays are studied in the perturbative QCD (PQCD) approach, considering the $\eta$-$\eta'$-$G$ mixing, where $G$ represents the pseudoscalar glueball. It is shown that the PQCD predictions for the $B_{d/s} \to J/\Psi \eta^{(')}$ branching ratios agree well with the data for the mixing angle $\phi_G\approx 30^\circ$ between the flavor-singlet state and the pure pseudoscalar glueball. Extending the formalism to the $\eta$-$\eta'$-$G$-$\eta_c$ tetramixing, the abnormally large observed $B_d\to K\eta'$ branching ratios are also explained. The proposed mixing formalism is applicable to other heavy meson decays into $\eta^{(\prime)}$ mesons, and could be tested by future LHCb and Super-$B$ factory data.Comment: Improved version, references added, 7 pages, 1 figur

Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm combined with popular machine learning approaches which largely reduce the human effort to tune algorithm parameters. However, the commonly used supervised learning approaches require the labeled data (e.g., bounding boxes), which is expensive for videos. Also, the TBD framework is usually suboptimal since it is not end-to-end, i.e., it considers the task as detection and tracking, but not jointly. To achieve both label-free and end-to-end learning of MOT, we propose a Tracking-by-Animation framework, where a differentiable neural model first tracks objects from input frames and then animates these objects into reconstructed frames. Learning is then driven by the reconstruction error through backpropagation. We further propose a Reprioritized Attentive Tracking to improve the robustness of data association. Experiments conducted on both synthetic and real video datasets show the potential of the proposed model. Our project page is publicly available at: https://github.com/zhen-he/tracking-by-animationComment: CVPR 201

O(\alpha_s) QCD Corrections to Spin Correlations in e−e+→ttˉe^- e^+ \to t \bar t process at the NLC

Using a Generic spin basis, we present a general formalism of one-loop radiative corrections to the spin correlations in the top quark pair production at the Next Linear Collider, and calculate the O(\alpha_s) QCD corrections under the soft gluon approximation. We find that: (a) in Off-diagonal basis, the $O(\alpha_s)$ QCD corrections to $e_L^- e^+$ ($e_R^- e^+$) scattering process increase the differential cross sections of the dominant spin component $t_{\uparrow}\bar{t}_{\downarrow}$ ($t_{\downarrow}\bar{t}_{\uparrow}$) by $\sim 30$ and $\sim (0.1$ depending on the scattering angle for $\sqrt{s}=400 GeV$ and 1 TeV, respectively; (b) in {Off-diagonal basis} (Helicity basis), the dominant spin component makes up 99.8% ($\sim 53$) of the total cross section at both tree and one-loop level for $\sqrt{s}=400 GeV$, and the Off-diagonal basis therefore remains to be the optimal spin basis after the inclusion of $O(\alpha_s)$ QCD corrections.Comment: 12 pages, 4 figures, revised version (a few print mistakes are corrected, some numerical results are modified, and Fig.4 is added