AI 中文总结
本研究分析290颗Ariel目标恒星的TESS光变曲线，定义归一化耀斑指数GF.01，发现近3%恒星耀斑活动增强，低光度恒星相对耀斑输出更高，AU Mic的凌星受耀斑污染概率高，为Ariel观测提供定量指导。
AI 中文摘要
恒星耀斑是磁能的突然释放，会扭曲系外行星凌星测光和透射光谱，从而对行星半径估算、凌星时刻及大气表征产生偏差。因此，了解Ariel目标恒星的耀斑活动，对识别耀斑可能破坏观测的恒星、表征影响大气逃逸和光化学的辐射环境至关重要。我们利用TESS光变曲线分析了290颗Ariel目标恒星，通过迭代高斯过程去趋势识别耀斑，并用两段幂律模型对其能量分布进行建模。我们开展了注入-恢复测试：向去趋势后的光变曲线中添加合成耀斑，运行完整流程以量化完备性和探测偏差。我们在1638个TESS天区中探测到15857个耀斑，每个天区的耀斑数量为2至86个。我们定义了归一化耀斑指数GF.01，用于比较不同恒星光度下的活动水平，近3%的样本表现出增强的耀斑活动（GF.01 > 1）。AU Mic和HD 28109在凌星观测期间存在较高的耀斑污染可能性。GF.01与恒星光热光度呈负相关，表明低光度恒星的相对耀斑输出更高。AU Mic是极端案例：观测到的AU Mic b的5次凌星中有4次受耀斑影响，与统计预期一致。我们通过将预测的耀斑污染概率与代表性凌星子集的观测耀斑发生情况进行比较来验证该框架，发现结果在不确定度范围内一致。这些结果证实，高能耀斑会显著影响凌星观测，并为Ariel的目标选择和分析策略提供定量指导。
英文摘要
Stellar flares are sudden releases of magnetic energy that can distort exoplanet transit photometry and transmission spectroscopy, biasing planet radius estimates, transit timings, and atmospheric characterization. Understanding flare activity in Ariel targets is therefore essential to identify stars where flares may compromise observations and to characterize the radiation environment affecting atmospheric escape and photochemistry. We analyzed 290 Ariel target stars using TESS light curves. Flares were identified via iterative Gaussian process detrending, and their energy distributions were modeled with two-segment power laws. We performed injection-recovery tests by adding synthetic flares to detrended light curves and running the full pipeline to quantify completeness and detection biases. We detected 15,857 flares across 1,638 TESS sectors, with 2-86 events per sector. We defined a normalized flare index GF.01 to compare activity across stellar luminosities. Near 3% of the sample exhibits enhanced flare activity (GF.01 > 1). AU Mic and HD 28109 show a high likelihood of flare contamination during transit observations. GF.01 correlates negatively with stellar bolometric luminosity, indicating higher relative flare output in lower-luminosity stars. AU Mic is an extreme case: four of five observed transits of AU Mic b are affected by flares, consistent with statistical expectations. We validate the framework by comparing predicted flare-contamination probabilities with observed flare occurrences in a representative subset of transits, finding agreement within uncertainties. These results confirm that energetic flares can significantly impact transit observations and provide quantitative guidance for Ariel target selection and analysis strategies.
CommentsArticle accepted by RASTI with official acceptance date 16/08/2026
