标题： 基于可扩展的高级机器学习方法的恒星耀斑识别：应用于TESS短时间间隔数据并分析一个新的耀斑目录 显示英文标题

标题： Scalable, Advanced Machine Learning-based Approaches for Stellar Flare Identification: Application to TESS short-cadence Data and Analysis of a New Flare Catalogue

摘要： 我们应用多算法机器学习模型对TESS 2分钟调查数据从第1至第72象限的数据进行分析，以识别恒星耀斑。 分别使用深度神经网络、随机森林和XGBoost算法训练的模型，采用四个耀斑光曲线特征作为输入特征。 模型性能通过准确率、精确率、召回率和F1分数指标进行评估，所有指标均超过94%。 与之前报告的TESS M型矮星耀斑识别结果进行验证显示，我们的模型成功恢复了超过92%的耀斑，同时检测到$\sim2,000$更多的小事件，从而提高了先前工作的检测灵敏度。 在处理了130万条光曲线后，我们的模型识别出近18,000颗耀斑恒星和250,000次耀斑。 我们提供了一个详尽的目录，记录了耀斑和恒星属性。 我们发现总耀斑能量和耀斑振幅与颜色之间存在强相关性，这与之前的研究一致。 分析了耀斑频率分布，修正了耀斑行为的幂律斜率，并考虑了由于低振幅事件检测不完全导致的频率不确定性。 我们确定了$\sim120,000$颗恒星的自转周期，从而得出了自转周期与耀斑活动之间的关系。 我们发现，在耀斑能量中饱和和非饱和区域之间的自转周期过渡与在日冕X射线发射中饱和和非饱和水平之间分离的自转周期过渡相吻合。 我们发现，在早期类型和非饱和恒星中，X射线发射随耀斑光度增加得更快，表明这些天体的日冕加热效率更高。 此外，我们在白矮星和热亚矮星中检测到耀斑，这些耀斑可能来源于未解析的低质量伴星。 显示英文摘要

摘要： We apply multi-algorithm machine learning models to TESS 2-minute survey data from Sectors 1-72 to identify stellar flares. Models trained with Deep Neural Network, Random Forest, and XGBoost algorithms, respectively, utilized four flare light curve characteristics as input features. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics, all exceeding 94%. Validation against previously reported TESS M dwarf flare identifications showed that our models successfully recovered over 92% of the flares while detecting $\sim2,000$ more small events, thus extending the detection sensitivity of previous work. After processing 1.3 million light curves, our models identified nearly 18,000 flare stars and 250,000 flares. We present an extensive catalog documenting both flare and stellar properties. We find strong correlations in total flare energy and flare amplitude with color, in agreement with previous studies. Flare frequency distributions are analyzed, refining power-law slopes for flare behavior with the frequency uncertainties due to the detection incompleteness of low-amplitude events. We determine rotation periods for $\sim120,000$ stars thus yielding the relationship between rotation period and flare activity. We find that the transition in rotation period between the saturated and unsaturated regimes in flare energy coincides with the same transition in rotation period separating the saturated and unsaturated levels in coronal X-ray emission. We find that X-ray emission increases more rapidly with flare luminosity in earlier-type and unsaturated stars, indicating more efficient coronal heating in these objects. Additionally, we detect flares in white dwarfs and hot subdwarfs that are likely arising from unresolved low-mass companions.