Implementation of ACTS for STCF track reconstruction

With an electron-positron collider operating at center-of-mass-energy 2-7 GeV and a peak luminosity above $0.5\times10^{35} cm^{-2} s^{-1}$, the STCF physics program will provide an unique platform for in-depth studies of hadron structure and non-perturbative strong interaction as well as probing new physics beyond the Standard Model in the $\tau$-Charm sector, succeeding the present Beijing Electron-Positron Collider. To fulfill the physics targets and further maximize the physics potential at STCF, the STCF tracking software should have capability to reconstruct charged particles with high efficiency and excellent momentum resolution, especially for the charged particles with low transverse momentum down to 50 MeV. A Common Tracking Software (ACTS) providing a set of detector-independent tracking algorithms is adopted for reconstructing charged tracks with the information of two sub-detectors, a $\mu$RWELL-based inner tracker and a drift chamber, at STCF. This is the first demonstration of ACTS for a drift chamber. The implementation details and performance of track reconstruction are presented.Comment: 14 pages, 7 figure

Pion/Kaon Identification at STCF DTOF Based on Classical/Quantum Convolutional Neural Network

Particle identification (PID) is one of the most fundamental tools in various physics research conducted in collider experiments. In recent years, machine learning methods have gradually become one of the mainstream methods in the PID field of high-energy physics experiments, often providing superior performance. The emergence of quantum machine learning may potential arm a powerful new toolbox for machine learning. In this work, targeting at the π±/K± discrimination problem at the STCF experiment, a convolutional neural network (CNN) in the endcap PID system is developed. By combining the hit position and arrival time of each Cherenkov photon at the sensors, a two-dimensional pixel map is constructed as the CNN input. The preliminary results show that the CNN model has a promising performance. In addition, based on the classical CNN, a quantum convolution neural network (QCNN) is developed as well, exploring possible quantum advantages provided by quantum machine learning methods

Performance of Track Reconstruction at STCF Using ACTS

The STCF physics program will provide an unique platform for studies of hadron physics, strong interactions and searches for new physics beyond the Standard Model in the τ-charm region. To deliver those physics programs, the charged particles at STCF are required to be reconstructed with high efficiency and excellent momentum resolution. In particular, charged particles with transverse momentum down to 50 MeV are required to be reconstructed. The tracking performance at STCF is studied using A Common Tracking Software (ACTS) based on the information of the STCF tracking system, a µRWELL-based inner tracker and a drift chamber. We demonstrated the first application of ACTS for a drift chamber. The implementation and tracking performance are presented

Muon and Pion Identification at BESIII Based on Machine Learning Algorithm

BESIII is designed to study physics in the τ-charm energy region utilizing the high luminosity BEPCII. For collision physics experiments like the BESIII experiment, particle identification (PID) is one of the most important and commonly used tools for physics analysis. The effective µ/π identification performance is of great significance for most of BESIII physics analysis. However, due to the close masses of these two particles, as well as the intrinsic correlation between multiple detector information, traditional methods at BESIII is facing challenges in µ/π identification. In recent decades, machine learning (ML) techniques have been rapidly developed and have shown successful applications in HEP experiments. The PID based on ML provides powerful capability of combining more detection information from all sub-detectors with the data-driven approach. In this article, targeting at the µ/π identification problem at the BESIII experiment, we have developed a new PID algorithm based on the gradient boosted decision tree (BDT) model. Preliminary results show that the XGBoost classifier provides obviously higher discrimination power than traditional methods. In addition, based on the substantial amount of high-quality data taken by the BESIII detector, a method of evaluating and suppressing the systematical error of the ML model is also introduced, which is critical for applying the model to physics studies

Novel approach to investigate η\eta decays via η′→ππη\eta'\rightarrow\pi\pi\eta

To avoid the impact from the background events directly from $e^+e^-$ annihilations or $J/\psi$ decays, we propose a novel approach to investigate $\eta$ decays, in particular for its rare or forbidden decays, by using $\eta^\prime\rightarrow\pi\pi\eta$ produced in $J/\psi$ decays at the $\tau-$charm factories. Based on the MC studies of a few typical decays, $\eta\rightarrow \pi\pi$, $\gamma l^+l^- (l= e, \mu)$, $l^+l^-$, as well as $l^+l^-\pi^0$, the sensitivities could be obviously improved by taking advantage of the extra constraint of $\eta^\prime$. Using one trillion $J/\psi$ events accumulated at the Super $\tau$-Charm facility, the precision on the investigation of $\eta$ decays could be improved significantly and the observation of the rare decay $\eta\rightarrow e^+e^-$ is even accessable.Comment: 7 pages, 6 figure

Offline Data Processing Software for the Super Tau Charm Facility

The Super Tau Charm Facility (STCF) proposed in China is a newgeneration electron–positron collider with center-of-mass energies covering 2-7 GeV and a peak luminosity of 0.5 1035 cm−2 s−1. The offline software of STCF (OSCAR) is developed to support the offline data processing, including detector simulation, reconstruction, calibration as well as physics analysis. To meet STCF’s specific requirements, OSCAR is designed and developed based on the SNiPER framework, a lightweight common software for HEP experiments. Besides the commonly used software such as Geant4 and ROOT, several state-ofthe-art software packages and tools in the HEP community are incorporated as well, such as the Detector Description Toolkit (DD4hep), the plain-old-data I/O (podio) and Intel Thread Building Blocks (TBB) etc. This paper will present the overall design as well as some implementation details of OSCAR, including the event data management, paralleled data processing based on SNiPER and TBB as well as the geometry management system based on DD4hep. Currently, OSCAR is fully functioning to facilitate the conceptual design of the STCF detector and the study of its physics potential

Methylation-mediated silencing of PTPRD induces pulmonary hypertension by promoting pulmonary arterial smooth muscle cell migration via the PDGFRB/PLCγ1 axis

OBJECTIVE: Pulmonary hypertension is a lethal disease characterized by pulmonary vascular remodeling and is mediated by abnormal proliferation and migration of pulmonary arterial smooth muscle cells (PASMCs). Platelet-derived growth factor BB (PDGF-BB) is the most potent mitogen for PASMCs and is involved in vascular remodeling in pulmonary hypertension development. Therefore, the objective of our study is to identify novel mechanisms underlying vascular remodeling in pulmonary hypertension. METHODS: We explored the effects and mechanisms of PTPRD downregulation in PASMCs and PTPRD knockdown rats in pulmonary hypertension induced by hypoxia. RESULTS: We demonstrated that PTPRD is dramatically downregulated in PDGF-BB-treated PASMCs, pulmonary arteries from pulmonary hypertension rats, and blood and pulmonary arteries from lung specimens of patients with hypoxic pulmonary arterial hypertension (HPAH) and idiopathic PAH (iPAH). Subsequently, we found that PTPRD was downregulated by promoter methylation via DNMT1. Moreover, we found that PTPRD knockdown altered cell morphology and migration in PASMCs via modulating focal adhesion and cell cytoskeleton. We have demonstrated that the increase in cell migration is mediated by the PDGFRB/PLCγ1 pathway. Furthermore, under hypoxic condition, we observed significant pulmonary arterial remodeling and exacerbation of pulmonary hypertension in heterozygous PTPRD knock-out rats compared with the wild-type group. We also demonstrated that HET group treated with chronic hypoxia have higher expression and activity of PLCγ1 in the pulmonary arteries compared with wild-type group. CONCLUSION: We propose that PTPRD likely plays an important role in the process of pulmonary vascular remodeling and development of pulmonary hypertension in vivo