标题： TESS万个星表：10,001个经统一验证和确认的通过机器学习从全帧图像数据中检测到并由公民科学家分析的食双星 显示英文标题

标题： The TESS Ten Thousand Catalog: 10,001 uniformly-vetted and -validated Eclipsing Binary Stars detected in Full-Frame Image data by machine learning and analyzed by citizen scientists

摘要： 凌日系外行星巡天卫星（TESS）以200秒到30分钟的时间分辨率和至少27天的时间基线，在全帧图像模式下几乎完整地扫描了整个天空。 除了发现新系外行星的主要目标外，TESS在探测变星方面也非常出色，特别是短周期食双星，它们相对常见，占所有恒星的百分之几，并且代表了强大的天体物理实验室，可用于深入研究恒星形成和演化。 我们梳理了TESS全帧图像数据的第1至82扇区，使用一种神经网络识别出约120万颗具有类似掩食特征的恒星。 在这之中，我们对大约60,000个目标进行了深入分析，采用自动化方法和公民科学家的手动检查。 这里我们提供了一份包含10001个统一验证和确认的掩食双星的目录，这些系统通过了我们的历元和光心测试，以及互补的视觉检查。 其中，7936个是新的掩食双星，而剩下的2065个是已知系统，我们更新了它们的发表历元。 我们概述了目标的检测和分析，讨论了样本的特性，并突出了可能有趣的系统。 最后，我们还提供了一份约900,000个未验证目标的列表，神经网络为这些目标找到了高于0.9分数的类似掩食特征，并且在TESS像素（约21弧秒）投影分离范围内没有已知的掩食双星。 显示英文摘要

摘要： The Transiting Exoplanet Survey Satellite (TESS) has surveyed nearly the entire sky in Full-Frame Image mode with a time resolution of 200 seconds to 30 minutes and a temporal baseline of at least 27 days. In addition to the primary goal of discovering new exoplanets, TESS is exceptionally capable at detecting variable stars, and in particular short-period eclipsing binaries which are relatively common, making up a few percent of all stars, and represent powerful astrophysical laboratories for deep investigations of stellar formation and evolution. We combed Sectors 1-82 of TESS Full-Frame Image data searching for eclipsing binary stars using a neural network that identified ~1.2 million stars with eclipse-like features. Of these, we have performed an in-depth analysis on ~60,000 targets using automated methods and manual inspection by citizen scientists. Here we present a catalog of 10001 uniformly-vetted and -validated eclipsing binary stars that passed all our ephemeris and photocenter tests, as well as complementary visual inspection. Of these, 7936 are new eclipsing binaries while the remaining 2065 are known systems for which we update the published ephemerides. We outline the detection and analysis of the targets, discuss the properties of the sample, and highlight potentially interesting systems. Finally, we also provide a list of ~900,000 unvetted and unvalidated targets for which the neural network found eclipse-like features with a score higher than 0.9, and for which there are no known eclipsing binaries within a sky-projected separation of a TESS pixel (~21 arcsec).