LEGUE中光谱目标优先选择算法
An Algorithm for Preferential Selection of Spectroscopic Targets in LEGUE
摘要：
我们描述了一个通用的目标选择算法，适用于任何调查，其中可用的候选人的数量远远大于要观察的对象的数量。该例程旨在实现平滑变化、易于理解的选择函数与优先选择某些类型的目标的愿望之间的平衡。一些目标选择的例子示出了不同的可能性的强调功能。尽管该算法普遍适用，但它是专门为将使用中国郭守敬望远镜进行的LAMOST银河系理解与探索实验（LEGUE）调查而开发的。特别是，该算法是专为部分的LEGUE目标的星系晕，在其中，我们试图平衡各种科学目标，需要在微弱的恒星的星等比可以完全采样LAMOST。该算法已在2011年10月开始的LAMOST试点调查的晕轮部分实施。
英文摘要：
We describe a general target selection algorithm that is applicable to any survey in which the number of available candidates is much larger than the number of objects to be observed. This routine aims to achieve a balance between a smoothly-varying, well-understood selection function and the desire to preferentially select certain types of targets. Some target-selection examples are shown that illustrate different possibilities of emphasis functions. Although it is generally applicable, the algorithm was developed specifically for the LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) survey that will be carried out using the Chinese Guo Shou Jing Telescope. In particular, this algorithm was designed for the portion of LEGUE targeting the Galactic halo, in which we attempt to balance a variety of science goals that require stars at fainter magnitudes than can be completely sampled by LAMOST. This algorithm has been implemented for the halo portion of the LAMOST pilot survey, which began in October 2011.
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