摘要
主要介绍SAGE巡天的恒星大气参数计算方法。首先回顾了前人利用恒星颜色确定恒星大气参数的工作;然后介绍了确定参数的多项式拟合和深度学习两种方法,并对每一种方法的原理、误差和特点进行了详细描述;最后对利用SAGE巡天恒星大气参数的前景进行展望。
The photometric system and data reduction of SAGE survey has been introduced before.This paper mainly focuses on the stellar parameter determination of stars from the SAGE survey.First,the previous work on stellar parameter estimation from photometric color is reviewed.Then,we illustrated two methods to derive the stellar parameters:polynomial tting and deep learning with MILES spectral library.For each method,the theory,accuracy and characteristic are presented in detail.Finally,the prospect of the stellar parameters of the SAGE survey are demonstrated.
作者
赵景昆
赵刚
范舟
谈克峰
宋轶晗
王奇勋
王炜
ZHAO Jing-kun;ZHAO Gang;FAN Zhou;TAN Ke-feng;SONG Yi-han;WANG Qi-xun;WANG Wei(Key Laboratory for Optical Astronomy,National Astronomical Observatory,Chinese Academy of Sciences,Beijing 100012,China;School of Astronomy and Space Science,University of Chinese Academy of Sciences,Beijing 100049,China;Chinese Academy of Sciences South America Center for Astronomy,China-Chile Joint Center for Astronomy,Santiago 7550000,Chile)
出处
《天文学进展》
CSCD
北大核心
2020年第1期60-68,共9页
Progress In Astronomy
基金
国家自然科学基金(11988101,11890694,11973048,11927804,11390371,11373003,11673030)
国家自然科学基金联合基金(U1631102)。
关键词
测光系统
恒星大气
深度学习
photometric system
stellar atmosphere
deep learning
作者简介
通讯作者:赵刚,gzhao@bao.ac.cn。
