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SPECTRAL CLASSIFICATION AND REDSHIFT MEASUREMENT FOR THE SDSS-III BARYON OSCILLATION SPECTROSCOPIC SURVEY

机译:SDSS-III Baryon振荡光谱调查的光谱分类和减量测量

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摘要

We describe the automated spectral classification, redshift determination, and parameter measurement pipeline in use for the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III (SDSS-III) as of the survey's ninth data release (DR9), encompassing 831,000 moderate-resolution optical spectra. We give a review of the algorithms employed, and describe the changes to the pipeline that have been implemented for BOSS relative to previous SDSS-I/II versions, including new sets of stellar, galaxy, and quasar redshift templates. For the color-selected "CMASS" sample of massive galaxies at redshift 0.4 z 0.8 targeted by BOSS for the purposes of large-scale cosmological measurements, the pipeline achieves an automated classification success rate of 98.7% and confirms 95.4% of unique CMASS targets as galaxies (with the balance being mostly M stars). Based on visual inspections of a subset of BOSS galaxies, we find that approximately 0.2% of confidently reported CMASS sample classifications and redshifts are incorrect, and about 0.4% of all CMASS spectra are objects unclassified by the current algorithm which are potentially recoverable. The BOSS pipeline confirms that ~51.5% of the quasar targets have quasar spectra, with the balance mainly consisting of stars and low signal-to-noise spectra. Statistical (as opposed to systematic) redshift errors propagated from photon noise are typically a few tens of km?s–1 for both galaxies and quasars, with a significant tail to a few hundreds of km?s–1 for quasars. We test the accuracy of these statistical redshift error estimates using repeat observations, finding them underestimated by a factor of 1.19-1.34 for galaxies and by a factor of two for quasars. We assess the impact of sky-subtraction quality, signal-to-noise ratio, and other factors on galaxy redshift success. Finally, we document known issues with the BOSS DR9 spectroscopic data set and describe directions of ongoing development.
机译:我们描述了自调查的第九个数据发布(DR9)起,用于斯隆数字天空测量III(SDSS-III)的重子振荡光谱调查(BOSS)的自动光谱分类,红移确定和参数测量管道,涵盖了831,000中分辨率光谱。我们对使用的算法进行了回顾,并描述了相对于以前的SDSS-I / II版本(包括新的恒星,星系和类星体红移模板)为BOSS实施的管线更改。对于以BOSS为目标进行大规模宇宙学测量的,红移0.4 x 0.8的颜色选择的“ CMASS”大质量星系样本,该管道实现了98.7%的自动分类成功率,并确定了95.4%的唯一CMASS目标为星系(其余大部分为M星)。基于对BOSS星系子集的目视检查,我们发现自信地报告的CMASS样本分类和红移中约有0.2%是不正确的,并且所有CMASS光谱中约有0.4%是当前算法未分类的,可能可恢复的物体。 BOSS管道确认了约51.5%的类星体目标具有类星体光谱,其余部分主要由恒星和低信噪比光谱组成。由光子噪声传播的统计(而不是系统的)红移误差对于星系和类星体通常为几十km·s-1,对于类星体则明显为数百km·s-1。我们使用重复观测来测试这些统计红移误差估计的准确性,发现它们被低估了1.19-1.34的星系系数和被类星体的2系数。我们评估了减天质量,信噪比和其他因素对星系红移成功的影响。最后,我们记录了BOSS DR9光谱数据集的已知问题,并描述了正在进行的开发方向。
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