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arXiv 1010.4040astro-ph.CO
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卡内基超新星计划:用SNooPy进行光变曲线拟合

The Carnegie Supernova Project: Light Curve Fitting with SNooPy

Christopher R. Burns, Maximilian Stritzinger, M. M. Phillips, ShiAnne Kattner, S. E. Persson, Barry F. Madore, Wendy L. Freedman, Luis Boldt, Abdo Campillay, Ca… 展开作者

Christopher R. Burns, Maximilian Stritzinger, M. M. Phillips, ShiAnne Kattner, S. E. Persson, Barry F. Madore, Wendy L. Freedman, Luis Boldt, Abdo Campillay, Carlos Contreras, Gaston Folatelli, Sergio Gonzalez, Wojtek Krzeminski, Nidia Morrell, Francisco Salgado, Nicholas B. Suntzeff

摘要:

在提供宇宙膨胀历史的独立测量时,卡内基超新星计划(CSP)在近红外波段Y和J观测到71颗高z Ia型超新星(SNe Ia),这些可以用来构建静止框架i波段光变曲线,当与低z样本相比时,产生的距离模量对消光和/或下降率校正的敏感性低于光学。然而,与近红外观测和i波段静止帧测光工作提出了独特的挑战,并有必要开发一套新的观测工具,以减少和分析低z和高z CSP样本。我们在本文中提出的方法来生成uBVgriYJH光变曲线模板的基础上的一个样本的24个高品质的低z CSP SNe。我们还提出了两种方法来确定距离的主机的超新星Ia事件。一个更大的样本的30个低z超新星Ia在哈勃流被用来校准这些方法。然后,我们应用的方法,并得出距离七个星系是如此之近,他们的运动并不占主导地位的哈勃流。

英文摘要:

In providing an independent measure of the expansion history of the Universe, the Carnegie Supernova Project (CSP) has observed 71 high-z Type Ia supernovae (SNe Ia) in the near-infrared bands Y and J. These can be used to construct rest-frame i-band light curves which, when compared to a low-z sample, yield distance moduli that are less sensitive to extinction and/or decline-rate corrections than in the optical. However, working with NIR observed and i-band rest frame photometry presents unique challenges and has necessitated the development of a new set of observational tools in order to reduce and analyze both the low-z and high-z CSP sample. We present in this paper the methods used to generate uBVgriYJH light-curve templates based on a sample of 24 high-quality low-z CSP SNe. We also present two methods for determining the distances to the hosts of SN Ia events. A larger sample of 30 low-z SNe Ia in the Hubble Flow are used to calibrate these methods. We then apply the method and derive distances to seven galaxies that are so nearby that their motions are not dominated by the Hubble flow.

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。

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