斯巴鲁FMOS星系红移巡天（FastSound）。I.在$z \sim 1.4$进行的以H $α$排放者为对象的调查概述
The Subaru FMOS Galaxy Redshift Survey (FastSound). I. Overview of the Survey Targeting on H$α$ Emitters at $z \sim 1.4$
摘要：
FastSound是一项星系红移巡天计划，使用安装在斯巴鲁望远镜上的近红外光纤多目标摄谱仪（FMOS），瞄准$z \sim 1.18$ - $1.54$处的H $α$发射器，灵敏度低至H $α$通量$\sim 2 \times 10^{-16} \ \rm erg \ cm^{-2} s^{-1}$。巡天的主要目标是探测红移空间畸变（RSD），通过测量大尺度结构的增长率来检验广义相对论，并限制修正的引力模型来解释宇宙加速膨胀的起源。目标星系是根据测光红移和H $α$通量估计选择的，这些估计是通过将光谱能量分布（SED）模型拟合到加拿大-法国-夏威夷望远镜遗产巡天（CFHTLS）宽目录的五个光学星等来计算的。调查于2012年3月开始，所有观察于2014年7月完成。总之，我们通过以六边形图案平铺CFHTLS Wide的四个字段，实现了覆盖$20.6$ deg $^2$的FMOS的$121$点（每个点具有$30$弧分直径圆形覆盖区）。发射线检测$\sim 4,000$恒星形成星系的自动线检测算法应用到二维光谱图像。这是基于FastSound数据的一系列论文中的第一篇，我们描述了调查设计，目标选择，观测，数据减少和发射线检测的细节。
英文摘要：
FastSound is a galaxy redshift survey using the near-infrared Fiber Multi-Object Spectrograph (FMOS) mounted on the Subaru Telescope, targeting H$α$ emitters at $z \sim 1.18$--$1.54$ down to the sensitivity limit of H$α$ flux $\sim 2 \times 10^{-16} \ \rm erg \ cm^{-2} s^{-1}$. The primary goal of the survey is to detect redshift space distortions (RSD), to test General Relativity by measuring the growth rate of large scale structure and to constrain modified gravity models for the origin of the accelerated expansion of the universe. The target galaxies were selected based on photometric redshifts and H$α$ flux estimates calculated by fitting spectral energy distribution (SED) models to the five optical magnitudes of the Canada France Hawaii Telescope Legacy Survey (CFHTLS) Wide catalog. The survey started in March 2012, and all the observations were completed in July 2014. In total, we achieved $121$ pointings of FMOS (each pointing has a $30$ arcmin diameter circular footprint) covering $20.6$ deg$^2$ by tiling the four fields of the CFHTLS Wide in a hexagonal pattern. Emission lines were detected from $\sim 4,000$ star forming galaxies by an automatic line detection algorithm applied to 2D spectral images. This is the first in a series of papers based on FastSound data, and we describe the details of the survey design, target selection, observations, data reduction, and emission line detections.
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。
