首页> 外文期刊>The Astrophysical journal >GEMINI SPECTROSCOPY OF SUPERNOVAE FROM THE SUPERNOVA LEGACY SURVEY: IMPROVING HIGH-REDSHIFT SUPERNOVA SELECTION AND CLASSIFICATION
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GEMINI SPECTROSCOPY OF SUPERNOVAE FROM THE SUPERNOVA LEGACY SURVEY: IMPROVING HIGH-REDSHIFT SUPERNOVA SELECTION AND CLASSIFICATION

机译:超新星遗产调查中的超新星双子星光谱:改进高变倍超新星的选择和分类

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We present new techniques for improving the efficiency of supernova (SN) classification at high redshift using 64 candidates observed at Gemini North and South during the first year of the Supernova Legacy Survey (SNLS). The SNLS is an ongoing 5 year project with the goal of measuring the equation of state of dark energy by discovering and following over 700 high-redshift SNe Ia using data from the Canada-France-Hawaii Telescope Legacy Survey. We achieve an improvement in the SN Ia spectroscopic confirmation rate: at Gemini 71% of candidates are now confirmed as SNe Ia, compared to 54% using the methods of previous surveys. This is despite the comparatively high redshift of this sample, in which the median SN Ia redshift is z = 0.81 (0.155 ≤ z ≤ 1.01). These improvements were realized because we use the unprecedented color coverage and light curve sampling of the SNLS to predict whether a candidate is a SN Ia and to estimate its redshift, before obtaining a spectrum, using a new technique called the "SN photo-z." In addition, we have improved techniques for galaxy subtraction and SN template χ~2 fitting, allowing us to identify candidates even when they are only 15% as bright as the host galaxy. The largest impediment to SN identification is found to be host galaxy contamination of the spectrum—when the SN was at least as bright as the underlying host galaxy the target was identified more than 90% of the time. However, even SNe in bright host galaxies can be easily identified in good seeing conditions. When the image quality was better than 0.55″, the candidate was identified 88% of the time. Over the 5 year course of the survey, using the selection techniques presented here, we will be able to add ~170 more confirmed SNe Ia than would be possible using previous methods.
机译:我们提出了在超新星遗产调查(SNLS)的第一年期间使用在双子座北部和南部观察到的64个候选物来提高高红移下超新星(SN)分类效率的新技术。 SNLS是一个正在进行的为期5年的项目,其目的是通过使用来自加拿大-法国-夏威夷望远镜遗留物调查的数据来发现并跟踪700多个高红移SNe Ia,从而测量暗能量的状态方程。我们实现了SN Ia光谱确认率的提高:在双子座,现在有71%的候选人被确认为SNe Ia,而以前的调查方法为54%。尽管此样本的红移相对较高,但其中位数SN Ia的红移为z = 0.81(0.155≤z≤1.01)。之所以能够实现这些改进,是因为我们使用一种称为“ SN photo-z”的新技术,使用了前所未有的SNLS颜色覆盖率和光曲线采样来预测候选者是否为SN Ia,并估计其红移,然后再获得光谱。 ”此外,我们还改进了星系减法和SN模板χ〜2拟合的技术,即使当它们仅比宿主星系亮15%时,也可以识别出候选者。发现SN识别的最大障碍是光谱中的宿主星系污染-当SN至少与下面的宿主星系一样明亮时,超过90%的时间可以识别出目标。但是,即使在明亮的宿主星系中,也可以在良好的观察条件下轻松识别出SNe。当图像质量优于0.55英寸时,在88%的时间内识别出了候选对象。在调查的5年中,使用此处介绍的选择技术,我们将能够比以前的方法添加170多个确认的SNe Ia。

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