4.7 Article

EMPIRICAL DELAY-TIME DISTRIBUTIONS OF TYPE Ia SUPERNOVAE FROM THE EXTENDED GOODS/HUBBLE SPACE TELESCOPE SUPERNOVA SURVEY

期刊

ASTROPHYSICAL JOURNAL
卷 713, 期 1, 页码 32-40

出版社

IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/713/1/32

关键词

supernovae: general

资金

  1. NASA [NAS 5-26555, K07R10]
  2. National Space Grant College
  3. Western Kentucky University Research Foundation

向作者/读者索取更多资源

Using the Hubble Space Telescope (HST) Advanced Camera for Surveys imaging of the GOODS North and South fields during Cycles 11, 12, and 13, we derive empirical constraints on the delay-time distribution function for type Ia supernovae (SNe Ia). We extend our previous analysis to the three-year sample of 56 SNe Ia over the range 0.2 < z < 1.8, using a Markov chain Monte Carlo to determine the best-fit unimodal delay-time distribution function. The test, which ultimately compares the star formation rate density history to the unbinned volumetric SN Ia rate history from the GOODS/HST SN survey, reveals a SN Ia delay-time distribution that is tightly confined to 3-4 Gyr (to >95% confidence). This result is difficult to resolve with any intrinsic delay-time distribution function (bimodal or otherwise), in which a substantial fraction (e. g., >10%) of events are prompt, requiring less than approximately 1 Gyr to develop from formation to explosion. The result is, however, strongly motivated by the decline in the number of SNe Ia at z > 1.2. Sub-samples of the HST SN data confined to lower redshifts (z < 1) show plausible delay-time distributions that are dominated by prompt events, which is more consistent with results from low-redshift supernova samples and supernova host galaxy properties. Scenarios in which a substantial fraction of z > 1.2 supernovae are extraordinarily obscured by dust may partly explain the differences in low-z and high-z results. Other possible resolutions may include environmental dependences (such as gas-phase metallicity) that affect the progenitor mechanism efficiency, especially in the early universe.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据