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Beam-induced backgrounds contribute to the trigger and data-acquisition rate at high-luminosity electron--positron colliders. Their dependence on beam and machine conditions motivates data-driven studies alongside simulation. A data-driven machine-learning method for trigger-level beam-background suppression is developed using experimental data recorded by BESIII.Compact neural-network classifiers are trained and evaluated for two trigger configurations: one based only on tracking and time-of-flight information, and one based only on electromagnetic-calorimeter information.Each classifier uses 48 binary Level-1 trigger conditions of the BESIII detector.The models distinguish hadron events from beam-background events and are evaluated against the established trigger selection at matched hadron-event efficiency. Relative to the established trigger selection, the beam-background false-positive rate is reduced by 19--60\% across the studied configurations and center-of-mass energies, with stable suppression performance as tested using random-trigger data.Hardware-oriented synthesis indicates that the compact network is suitable for low-latency FPGA implementation. The proposed method can reduce the fraction of beam-background events in the trigger stream in future BESIII trigger upgrades. It also provides a reference for trigger optimization at future high-luminosity electron--positron colliders.

Nuclear clocks operate on the basis of transitions in atomic nuclei, which offer superior resistance to external perturbations and make them crucial tools for fundamental physics research and precision metrology applications. The nuclide 229Th is currently the leading candidate for nuclear clocks due to its unique low-energy nuclear transition, while its scarcity and high cost present significant challenges. Here, we evaluate the production of 229Th through nuclear reactions induced by irradiating 232Th targets with γ-ray, proton and neutron particle sources. The interaction between the particle beams and the target was modeled using Geant4, where the relevant reaction channels were constructed and supplemented, and the reaction cross-sections were calculated using TALYS. Using beam parameters representative of existing facilities, the calculated one-year yields of 229Th are 43.001 mg for a 100 MeV, 1 mA electron beam generating bremsstrahlung photons, 73.728 mg for a 100 MeV, 520 μA proton beam, and 27.227 ng for the adopted PWR neutron spectrum at a flux of 1.21 × 1011 -2 s-1. Proton irradiation gives the highest yield among the three scenarios, while both proton irradiation and electron-beam-driven photonuclear production achieve milligram-scale yields. The radioactive decay accumulation of the products in the 229Th production chain was recorded, revealing the main contributors to 229Th.

System-generated electromagnetic pulse (SGEMP) induced in coaxial cables by X-ray irradiation can interfere with diagnostic signals in inertial confinement fusion and pulsed radiation experiments. In this paper, the nonuniform net charge distribution obtained from coupled photon-electron transport in MCNP5 is introduced into a twodimensional axisymmetric Maxwell finite-difference time-domain (FDTD) model to evaluate the cable SGEMP response. To assess the consistency of the numerical predictions, the calculated current responses of the coaxial cable under X-ray irradiation are compared with those obtained using the equivalent transmission-line method reported in a previous study. The current responses under uniform and nonuniform charge distribution conditions are compared, and the results show that the assumption of uniform charge deposition overestimates the peak response by more than an order of magnitude. A transverse electromagnetic mode analysis explains the underlying mechanism: the spatial weighting of dielectric charge and its cancellation with conductor charge jointly govern this discrepancy. This paper further examines the effects of irradiation conditions, cable length and materials, and termination conditions on the SGEMP current response of the cable. This study can provide theoretical guidance for the radiation hardening of cables.

为满足自动驾驶离线学习与仿真实验对高质量、多场景、可复现轨迹数据的需求，本文围绕CARLA仿真平台下的城市场景数据集构建开展研究。首先，选取Town10HD地图中的直线定速巡航、行人横穿马路和红绿灯路口通行三类典型驾驶场景，分别明确任务目标、失败条件和采集边界。其次，通过固定路线筛选、候选route预览、场景可重复化设计和规则专家控制器设计，生成包含成功、临界和失败三类质量层次的离线驾驶轨迹。针对行人横穿场景，本文在固定直线路线基础上参数化生成横穿事件，并记录让行、停车、安全距离和碰撞等行为信息；针对红绿灯路口场景，构建停止线推断、交通灯关联和红/黄/绿灯状态机，使数据覆盖红灯等待与绿灯通行两类典型路口行为。最后，对不同来源的episode级数据进行统一字段提取、标签归一化、索引组织和训练/验证/测试集划分，形成面向后续离线策略学习使用的标准化多场景离线驾驶数据集。结果表明，所构建的数据集在三类场景下均具有明确的任务语义、稳定的路线基础和可追踪的数据结构，能够为自动驾驶场景建模、轨迹分析以及后续算法训练与对比实验提供可靠的数据支撑。

低时间抖动光脉冲在精密测量、光电频率合成及低噪声微波产生等领域具有重要应用价值。针对自由运行脉冲激光器重复频率稳定度较低、低频相位波动明显的问题，提出并实验验证了一种基于双点光学分频的低时间抖动脉冲产生方法。该方法采用锁定至同一法布里-珀罗腔不同纵模的两路激光作为光学参考，通过双点光学分频将双频参考的相对稳定性传递至锁模激光器的重复频率，实现对输出脉冲序列的闭环锁定。实验结果表明，与自由运行状态相比，锁定后光电探测得到的1 GHz微波信号在1 Hz处改善36dB，1kHz处改善26dB；在10 Hz至100 kHz积分带宽内，累计均方根时间抖动由252.78 fs降低至8.39 fs。该方法能够有效抑制锁模脉冲序列的低频相位波动，为低时间抖动光脉冲的产生提供了一种有效方案。