Pair production of 125 GeV Higgs boson in the SM extension with color-octet scalars at the LHC

Although the Higgs boson mass and single production rate have been determined more or less precisely, its other properties may deviate significantly from its predictions in the standard model (SM) due to the uncertainty of Higgs data. In this work we study the Higgs pair production at the LHC in the Manohar-Wise model, which extends the SM by one family of color-octet and isospin-doublet scalars. We first scanned over the parameter space of the Manohar-Wise model considering exprimental constraints and performed fits in the model to the latest Higgs data by using the ATLAS and CMS data separately. Then we calculated the Higgs pair production rate and investigated the potential of its discovery at the LHC14. We conclude that: (i) Under current constrains including Higgs data after Run I of the LHC, the cross section of Higgs pair production in the Manohar-Wise model can be enhanced up to even $10^3$ times prediction in the SM. (ii) Moreover, the sizable enhancement comes from the contributions of the CP-odd color-octet scalar $S^A_I$. For lighter scalar $S^A_I$ and larger values of $|\lambda_I|$, the cross section of Higgs pair production can be much larger. (iii) After running again of LHC at 14 TeV, most of the parameter spaces in the Manohar-Wise model can be test. For an integrated luminosity of 100 fb$^{-1}$ at the LHC14, when the normalized ratio $R=10$, the process of Higgs pair production can be detected.Comment: 13 pages, 4 figure

Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. With the large amounts of molecular dynamics data generated everyday in nearly every aspect of materials design, this approach provides a broadly useful, automated tool to understand atomic scale dynamics in material systems.Comment: 25 + 7 pages, 5 + 3 figure

SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes

The SportsMOT dataset aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer. The dataset is challenging because of the unstable camera view, athletes' complex trajectory, and complicated background. Previous MOT methods can not match enough high-quality tracks of athletes. To pursue higher performance of MOT in sports scenes, we introduce an innovative tracker named SportsTrack, we utilize tracking by detection as our detection paradigm. Then we will introduce a three-stage matching process to solve the motion blur and body overlapping in sports scenes. Meanwhile, we present another innovation point: one-to-many correspondence between detection bboxes and crowded tracks to handle the overlap of athletes' bodies during sports competitions. Compared to other trackers such as BOT-SORT and ByteTrack, We carefully restored edge-lost tracks that were ignored by other trackers. Finally, we reached the SOTA result in the SportsMOT dataset.Comment: 7 pages,9 figure

Geochemistry of Late Triassic pelitic rocks in the NE part of Songpan-Ganzi Basin, western China: Implications for source weathering, provenance and tectonic setting

AbstractMajor, trace and rare earth element (REE) concentrations of Late Triassic sediments (fine-grained sandstones and mudstones) from Hongcan Well 1 in the NE part of the Songpan-Ganzi Basin, western China, are used to reveal weathering, provenance and tectonic setting of inferred source areas. The Chemical Index of Alteration (CIA) reflects a low to moderate degree of chemical weathering in a cool and somewhat dry climate, and an A-CN-K plot suggests an older upper continental crust provenance dominated by felsic to intermediate igneous rocks of average tonalite composition. Based on the various geochemical tectonic setting discrimination diagrams, the Late Triassic sediments are inferred to have been deposited in a back-arc basin situated between an active continental margin (the Kunlun-Qinling Fold Belt) and a continental island arc (the Yidun Island Arc). The Triassic sediments in the study area underwent a rapid erosion and burial in a proximal slope-basin environment by the petrographic data, while the published flow directions of Triassic turbidites in the Aba-Zoige region was not supported Yidun volcanic arc source. Therefore, we suggest that the Kunlun-Qinling terrane is most likely to have supplied source materials to the northeast part of the Songpan-Ganzi Basin during the Late Triassic