Cosmic-ray muons are a type of natural radiation with high energy and a strong penetration ability. The flux distribution of such particles at sea level is a key problem in many areas, especially in the field of muon imaging and low background experiments. This paper summarizes the existing models to describe sea-level muon flux distributions. According to different means used, four parametric analytical models and one Monte Carlo model, which is referred to as CRY, are selected as typical sea-level muon flux distribution models. Then, the theoretical values of sea-level muon fluxes given by these models are compared with the experimental sea-level muon differential flux data with kinetic energy values in the range of 1–1,000 GeV in the directions of zenith angles 0° and 75°. The goodness of fit of these models to the experimental data was quantitatively calculated by Pearson’s chi-square test. The results of the comparison show that the commonly used Gaisser model overestimates the muon flux in the low-energy region, while the muon flux given by the Monte Carlo model CRY at the large zenith angle of 75° is significantly lower than that of the experimental data. The muon flux distribution given by the other three parametric analytical models is consistent with the experimental data. The results indicate that the original Gaisser model is invalid in the low energy range, and CRY apparently deviates at large zenith angles. These two models can be substituted with the muon flux models given by Gaisser/Tang, Bugaev/Reyna, and Smith and Duller/Chatzidakis according to actual experimental conditions.

宇宙射线缪子吸收成像技术是一种无损成像技术, 适用于对大尺度的成像目标进行无损探测. 考古学中现有的无损探测方法均存在一定的局限性, 若将μ子吸收成像技术应用于考古领域, 可以作为对传统无损探测方法的重要补充. 本文使用蒙特卡罗GEANT4程序, 对秦始皇陵地宫缪子吸收成像进行研究, 基于已有的秦始皇陵考古数据构建秦始皇陵地宫模型, 根据Reyna提出的海平面缪子能谱公式抽样产生缪子源的信息, 模拟了宇宙射线缪子在秦始皇陵地宫中的输运过程, 并利用图像重建算法实现墓室大小和位置的重构. 模拟结果表明, 利用单视角获得的缪子通量投影数据可以给出地宫中墓室边界的二维角坐标, 利用两个视角的投影数据可以重建墓室大小和三维位置, 重建得到的墓室边长和墓室中心位置相对于理论值的差异在7%左右.

Introduction: Identifying the technologies that will drive technological changes over the coming years is important for the optimal allocation of firms’ R&D resources and the deployment of innovation strategies. The citation frequency of a patent is widely recognized as representative of the patent’s value. Thus, identifying potential highly cited patents is an important goal. A number of studies have attempted to distinguish highly cited patents from others based on statistical models, but a more effective and applicable method needs to be further developed.Methods: This paper treats the prediction of later patent citations as a classification problem and proposes a novel framework based on machine learning methods. First, a indices system to identify highly cited patents is constructed using multiple factors that are believed to influence citation frequency. Second, various machine learning models are utilized to identify highly cited patents. The optimized model with the best generalization capability is selected to predict the future impacts of newly applied patents, which may be representative of emerging significant technologies. Finally, we select the electric vehicle (EV) domain as a case study to empirically test the validity of this framework.Results: The optimized support vector machine (SVM) model performs well in identifying highly cited EV patents. Technological frontiers in the EV domain are identified, which are related to the topics of information systems, batteries, stability control, wireless charging, and vehicle operation.Discussion: The good performance in prediction accuracy and generalization capability of the method proposed in this paper verifies its effectiveness and feasibility.

Muography is widely applied to detect the internal structures of large objects. To meet the demands for large-area and high-precision detection, muography detectors have high requirements for the accuracy and speed of the readout electronics. The μSight-1 muography detector developed by Beijing Normal University features an effective detection area of 1.3 m² and a position resolution of 1.9 mm. This paper presents the design of a multi-channel SiPM readout system for this detector, supporting flexible coupling methods between SiPMs and scintillators. The front-end electronics (FEE) in the system has a signal-to-noise ratio of 6.745, enabling single-photon detection when paired with SiPMs, and provides real-time temperature drift compensation for SiPMs. The time-of-flight (TOF) on the main control board offers a time resolution of 56 ps.

Rare event detection is a frontier subject in particle physics and nuclear physics. In particular, dark matter detection, neutrino-free double beta decay and neutrino-nucleon coherent elastic scattering are being planned and implemented gradually. Rare event detection requires not only the detectors to possess excellent performances but also extremely low environmental background, so the selection of detectors and related materials is an important issue in rare event detection. Liquid argon has become an important scintillator material for scintillator detectors because of its low cost, good scintillation performance and large volume. Liquid argon was first studied in the 1940s as a sensitive material for ionizing radiation detectors. The first measurements of high-energy beta particles were obtained by using a liquid argon ionization chamber in 1953. The ICARUS group put forward the idea of constructing liquid argon temporal projection chamber, and made attempt to construct liquid argon temporal projection chamber in 1977. The scintillation light signals were collected for the first time in a liquid argon temporal projection chamber in 1999. Thus, the drift time of the particle can be obtained to determine the particle track. After development, single-phase liquid argon scintillator detector and two-phase argon time projection chamber have become two common types of liquid argon detectors, and have been extensively used in rare event detection experiments in recent years. For dark matter detection, the DEAP group and DarkSide group have achieved good results with single-phase liquid argon scintillation detector and two-phase argon time projection chamber, respectively. For neutrino-free double beta decay experiments, the GERDA group has done a lot of researches of liquid argon anti-coincidence system and applied the said system to experiments. The LEGEND group, which is the combination of GERDA and MAJORANA experimental group, upgraded the liquid argon anti-coincidence system which was applied to the following LEGEND-200 project. For neutrino-nucleon elastic scattering experiments, COHERENT obtained the latest results by using the liquid argon detectors. The Taishan neutrino-nucleon coherent elastic scattering project of the High Energy Institute of Chinese Academy of Sciences has also begun to study the feasibility of liquid argon anti-coincidence system. Finally, this paper discusses the direction of optimizing the liquid argon detector, such as exposure, background level and optical readout scheme, and gives a good prospect of liquid argon detector applied to rare event detection in the future.