论文标题
调查和应用拟合模型用于核心算法的天体统计算法
Investigation and Application of Fitting Models for Centering Algorithms in Astrometry
论文作者
论文摘要
为了确定恒星在CCD框架中的精确位置，已经提出了各种居中算法用于天体测量法。有效点扩散函数（EPSF）和高斯核心算法是两个代表性的核心算法。本文详细比较并研究了这两种中心算法在执行数据降低时。具体而言，生成并处理了不同条件下的合成星图像（即最大值，最大值的概况，通量，背景和全宽度）。我们发现两种算法之间的精度差异与星图像的轮廓有关。因此，使用理想的高斯元音图像的精确比较结果不能扩展到其他更具体的实验场景。基于仿真结果，可以根据观测值的图像特征选择最合适的算法，并且可以估算其他算法的精度丧失。使用云南天文台的1-M和2.4-M望远镜捕获的观测值对结论进行了验证。
To determine the precise positions of stars in CCD frames, various centering algorithms have been proposed for astrometry. The effective point spread function (ePSF) and the Gaussian centering algorithms are two representative centering algorithms. This paper compares in detail and investigates these two centering algorithms in performing data reduction. Specifically, synthetic star images in different conditions (i.e. profiles, fluxes, backgrounds and full width at half maximums) are generated and processed. We find that the difference in precision between the two algorithms is related to the profiles of the star images. Therefore, the precision comparison results using an ideal Gaussian-profile star image cannot be extended to other more specific experimental scenarios. Based on the simulation results, the most appropriate algorithm can be selected according to the image characteristics of observations, and the loss of precision of other algorithms can be estimated. The conclusions are verified using observations captured by the 1-m and 2.4-m telescopes at Yunnan Observatory.
