arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2001.09348astro-ph.IMastro-ph.GA
收藏

多目标光谱探测中的概率光纤-目标分配算法

Probabilistic fibre-to-target assignment algorithm for multi-object spectroscopic surveys

E. Tempel, P. Norberg, T. Tuvikene, T. Bensby, C. Chiappini, N. Christlieb, M. -R. L. Cioni, J. Comparat, L. J. M. Davies, G. Guiglion, A. Koch, G. Kordopatis, … 展开作者

E. Tempel, P. Norberg, T. Tuvikene, T. Bensby, C. Chiappini, N. Christlieb, M. -R. L. Cioni, J. Comparat, L. J. M. Davies, G. Guiglion, A. Koch, G. Kordopatis, M. Krumpe, J. Loveday, A. Merloni, G. Micheva, I. Minchev, B. F. Roukema, J. G. Sorce, E. Starkenburg, J. Storm, E. Swann, W. F. Thi, G. Traven, R. S. de Jong

摘要:

上下文目前正在计划或正在建造几台新的多物体摄谱仪,它们能够同时观测数千个银河系和河外物体。目的。在本文中,我们提出了一种概率光纤到目标分配算法,考虑到光谱仪的目标约束,并能够处理多个并发的调查。我们提出了这种算法使用4米多目标光谱望远镜(4 MOST)作为一个例子。方法.该算法的核心思想是分配概率的纤维目标对。概率的分配考虑了光纤定位器的能力和约束。此外,这些概率包括调查的要求,并考虑到所需的曝光时间,数量密度变化,以及每个调查中目标的角度聚类。概率方法的主要优点是,它可以准确和容易地计算不同调查的目标选择函数,这涉及到确定观察目标的概率,给定的输入目录。结果概率光纤到目标的分配,使我们能够在一个单一的视野内实现最大限度的统一完整性。所提出的算法最大限度地成功观察到的目标的分数,同时最大限度地减少作为曝光时间的函数的选择偏差。在几个同时进行的调查的情况下,该算法最大限度地满足每个调查的科学要求,并且没有特定的调查被惩罚或优先考虑。结论.提出的算法是一个建议的解决方案的4 MOST项目,允许一个无偏的目标,许多同时进行的调查。经过适当的改进,该算法也可应用于其他多目标光谱测量。

英文摘要:

Context. Several new multi-object spectrographs are currently planned or under construction that are capable of observing thousands of Galactic and extragalactic objects simultaneously. Aims. In this paper we present a probabilistic fibre-to-target assignment algorithm that takes spectrograph targeting constraints into account and is capable of dealing with multiple concurrent surveys. We present this algorithm using the 4-metre Multi-Object Spectroscopic Telescope (4MOST) as an example. Methods. The key idea of the proposed algorithm is to assign probabilities to fibre-target pairs. The assignment of probabilities takes the fibre positioner's capabilities and constraints into account. Additionally, these probabilities include requirements from surveys and take the required exposure time, number density variation, and angular clustering of targets across each survey into account. The main advantage of a probabilistic approach is that it allows for accurate and easy computation of the target selection function for the different surveys, which involves determining the probability of observing a target, given an input catalogue. Results. The probabilistic fibre-to-target assignment allows us to achieve maximally uniform completeness within a single field of view. The proposed algorithm maximises the fraction of successfully observed targets whilst minimising the selection bias as a function of exposure time. In the case of several concurrent surveys, the algorithm maximally satisfies the scientific requirements of each survey and no specific survey is penalised or prioritised. Conclusions. The algorithm presented is a proposed solution for the 4MOST project that allows for an unbiased targeting of many simultaneous surveys. With some modifications, the algorithm may also be applied to other multi-object spectroscopic surveys.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑