More hidden heavy quarkonium molecules and their discovery decay modes

To validate the molecular description of the observed $Z_b(10610)/Z_b(10650)$ and $Z_c(3900)/Z_c(4025)$, it is valuable to investigate their counterparts, denoted as $Z_{QV}^{(\prime)}$ in this work, and the corresponding decay modes. In this work, we present an analysis of the $Z_{QV}^{(\prime)}$ using flavor symmetry. We also use the effective Lagrangian based on the heavy quark symmetry to explore the rescattering mechanism and calculate the partial widths for the isospin conserved channels $Z_{QV}^{(\prime)} \to \eta_Q V$. The predicted partial widths are of an order of MeV for $Z_{QV} \to \eta_Q V$, which correspond to branching ratios of the order of $10^{-2}\sim 10^{-1}$. For $Z_{QV}^\prime \to \eta_Q V$, the partial widths are a few hundreds of keV and the branching ratios are about $10^{-3}$. Future experimental measurements can test our predictions on the partial widths and thus examine the molecule description of heavy quarkoniumlike exotic states.Comment: 11 pages, 2 figures; accepted by Phys. Rev.

Building Footprint Generation Using Improved Generative Adversarial Networks

Building footprint information is an essential ingredient for 3-D reconstruction of urban models. The automatic generation of building footprints from satellite images presents a considerable challenge due to the complexity of building shapes. In this work, we have proposed improved generative adversarial networks (GANs) for the automatic generation of building footprints from satellite images. We used a conditional GAN with a cost function derived from the Wasserstein distance and added a gradient penalty term. The achieved results indicated that the proposed method can significantly improve the quality of building footprint generation compared to conditional generative adversarial networks, the U-Net, and other networks. In addition, our method nearly removes all hyperparameters tuning.Comment: 5 page