利用机器学习技术发现 118 颗新的超冷矮星候选体
太阳与恒星天体物理
2024-09-26 v2 地球与行星天体物理
星系天体物理
天体物理仪器与方法
摘要
我们报告了 118 颗新的超冷矮星候选体的发现，这些候选体是使用一种名为 \texttt{SMDET} 的新机器学习工具，应用于来自广域红外巡天探测者的时序图像而发现的。我们收集了测光和天体测量数据，以估计每个候选体的光谱型、距离和切向速度。该样本的光度估计光谱型分布为 28 颗 M 矮星、64 颗 L 矮星和 18 颗 T 矮星。我们还识别出一个 T 亚矮星候选体、两个极端 T 亚矮星候选体和两个候选年轻超冷矮星。有五个天体没有足够的测光数据来进行任何估计。为了验证我们估计的光谱型，我们收集了两个天体的光谱，确认其光谱型为 T5（估计为 T5）和 T3（估计为 T4）。这证明了机器学习工具作为一种新型大规模发现技术的有效性。
引用
@article{arxiv.2408.14447,
title = {Discovery of 118 New Ultracool Dwarf Candidates Using Machine Learning Techniques},
author = {Hunter Brooks and Dan Caselden and J. Davy Kirkpatrick and Yadukrishna Raghu and Charles Elachi and Jake Grigorian and Asa Trek and Andrew Washburn and Hiro Higashimura and Aaron Meisner and Adam Schneider and Jacqueline Faherty and Federico Marocco and Christopher Gelino and Jonathan Gagné and Thomas Bickle and Shih-yun Tang and Austin Rothermich and Adam Burgasser and Marc J. Kuchner and Paul Beaulieu and John Bell and Guillaume Colin and Giovanni Colombo and Alexandru Dereveanco and Deiby Flores and Konstantin Glebov and Leopold Gramaize and Les Hamlet and Ken Hinckley and Martin Kabatnik and Frank Kiwy and David Martin and Raul Palma and William Pendrill and Lizzeth Ruiz and John Sanchez and Arttu Sainio and JÖrg SchÜmann and Manfred Schonau and Christopher Tanner and Nikolaj Stevnbak Andersen and Andrés Stenner and Melina Thévenot and Vinod Thakur and Nikita Voloshin and Zbigniew Wedracki},
journal= {arXiv preprint arXiv:2408.14447},
year = {2024}
}
备注
14 pages, 8 figures, 2 tables, extended table 1, accepted to Astronomical Journal