Jeffrey L. Carlin, Sebastien Lepine, Heidi Jo Newberg, Licai Deng, Timothy C. Beers, Yuqin Chen, Norbert Christlieb, Xiaoting Fu, Shuang Gao, Carl J. Grillmair, Puragra Guhathakurta, Zhanwen Han, Jinliang Hou, Hsu-Tai Lee, Jing Li, Chao Liu, Xiaowei Liu, Kaike Pan, J. A. Sellwood, Hongchi Wang, Fan Yang, Brian Yanny, Yueyang Zhang, Zheng Zheng, Zi Zhu
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.
View original:
http://arxiv.org/abs/1206.3577
No comments:
Post a Comment