Isospin and a possible interpretation of the newly observed X(1576)

Recently, the BES collaboration observed a broad resonant structure X(1576) with a large width being around 800 MeV and assigned its $J^{PC}$ number to $1^{--}$. We show that the isospin of this resonant structure should be assigned to 1. This state might be a molecule state or a tetraquark state. We study the consequences of a possible $K^*(892)$-${\bar \kappa}$ molecular interpretation. In this scenario, the broad width can easily be understood. By using the data of $B(J/\psi\to X\pi^0)\cdot B(X\to K^+K^-)$, the branching ratios $B(J/\psi\to X\pi^0)\cdot B(X\to \pi^+\pi^-)$ and $B(J/\psi\to X\pi^0)\cdot B(X\to K^+K^-\pi^+\pi^-)$ are further estimated in this molecular state scenario. It is shown that the $X\to \pi^+\pi^-$ decay mode should have a much larger branching ratio than the $X\to K^+K^-$ decay mode has. As a consequence, this resonant structure should also be seen in the $J/\psi\to \pi^+\pi^-\pi^0$ and $J/\psi\to K^+K^-\pi^+\pi^-\pi^0$ processes, especially in the former process. Carefully searching this resonant structure in the $J/\psi\to \pi^+\pi^-\pi^0$ and $J/\psi\to K^+K^-\pi^+\pi^-\pi^0$ decays should be important for understanding the structure of X(1567).Comment: 5 pages, ReVTeX4, 3 figures. Version accepted for publication as a brief report in Phys. Rev.

Enhanced breaking of heavy quark spin symmetry

Heavy quark spin symmetry is useful to make predictions on ratios of decay or production rates of systems involving heavy quarks. The breaking of spin symmetry is generally of the order of $O({\Lambda_{\rm QCD}/m_Q})$, with $\Lambda_{\rm QCD}$ the scale of QCD and $m_Q$ the heavy quark mass. In this paper, we will show that a small $S$- and $D$-wave mixing in the wave function of the heavy quarkonium could induce a large breaking in the ratios of partial decay widths. As an example, we consider the decays of the $\Upsilon(10860)$ into the $\chi_{bJ}\omega\, (J=0,1,2)$, which were recently measured by the Belle Collaboration. These decays exhibit a huge breaking of the spin symmetry relation were the $\Upsilon(10860)$ a pure $5S$ bottomonium state. We propose that this could be a consequence of a mixing of the $S$-wave and $D$-wave components in the $\Upsilon(10860)$. Prediction on the ratio $\Gamma(\Upsilon(10860)\to\chi_{b0}\omega)/\Gamma(\Upsilon(10860)\to\chi_{b2}\omega)$ is presented assuming that the decay of the $D$-wave component is dominated by the coupled-channel effects.Comment: 13 pages, 5 figures. Discussion extended, version to appear in Phys.Lett.

Automatic Objects Removal for Scene Completion

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure based image completion algorithm for object removal that produces visually plausible content with consistent structure and scene texture. We use an edge matching technique to infer the potential structure of the unknown region. Driven by the estimated structure, texture synthesis is performed automatically along the estimated curves. We evaluate the proposed method on different types of images: from highly structured indoor environment to the natural scenes. Our experimental results demonstrate satisfactory performance that can be potentially used for subsequent big data processing: 3D scene reconstruction and location recognition.Comment: 6 pages, IEEE International Conference on Computer Communications (INFOCOM 14), Workshop on Security and Privacy in Big Data, Toronto, Canada, 201

A Global Context Mechanism for Sequence Labeling

Sequential labeling tasks necessitate the computation of sentence representations for each word within a given sentence. With the advent of advanced pretrained language models; one common approach involves incorporating a BiLSTM layer to bolster the sequence structure information at the output level. Nevertheless, it has been empirically demonstrated (P.-H. Li et al., 2020) that the potential of BiLSTM for generating sentence representations for sequence labeling tasks is constrained, primarily due to the amalgamation of fragments form past and future sentence representations to form a complete sentence representation. In this study, we discovered that strategically integrating the whole sentence representation, which existing in the first cell and last cell of BiLSTM, into sentence representation of ecah cell, could markedly enhance the F1 score and accuracy. Using BERT embedded within BiLSTM as illustration, we conducted exhaustive experiments on nine datasets for sequence labeling tasks, encompassing named entity recognition (NER), part of speech (POS) tagging and End-to-End Aspect-Based sentiment analysis (E2E-ABSA). We noted significant improvements in F1 scores and accuracy across all examined datasets