Addressing type Ia supernova color variability with a linear spectral template

IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS
C.S. Nascimento , J.P.C. França , R.R.R. Reis
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引用次数: 0

Abstract

Type Ia Supernovae (SNeIa) provided the first evidence of an accelerated expansion of the universe and remain a valuable probe to cosmology. They are deemed standardizable candles due to the observed correlations between their luminosity and photometric quantities. This characteristic can be exploited to estimate cosmological distances after accounting for the observed variations. There is however a remaining dispersion unaccounted for in the current state-of-the-art standardization methods. In an attempt to explore this issue, we propose a simple linear 3-component rest-frame flux description for a light-curve fitter. Since SNIa intrinsic color index variations are expected to be time-dependent, our description builds upon the mathematical expression of the well-known Spectral Adaptive Light Curve Template 2 (SALT2) for rest-frame flux, whilst we drop the exponential factor and add an extra model component with time and wavelength dependencies. The model components are obtained by performing either Principal Component Analysis (PCA) or Factor Analysis (FA) onto a representative training set. The constraining power of the model dubbed Pure Expansion Template for Supernovae (PETS) is evaluated and we found compatible results with SALT2 for Ωm0 and ΩΛ0 within 68% uncertainty between the two models, with PETS’ fit parameters exhibiting non-negligible linear correlations with SALT2’ parameters. For both PCA and FA model versions we verified that the first component mainly describes color index variations, proving it is a dominant effect on SNIa spectra. The model nuisance parameter which multiplies the color index variation-like fit parameter shows evolution with redshift in an initial binned cosmology analysis. This behavior can be due to selection effects and should be further investigated with higher redshift SNeIa samples. Overall, our model shows promise, as there are still a few aspects to be refined; however, it still falls short in reducing the unaccounted dispersion.

用线性光谱模板解决 Ia 型超新星颜色可变性问题
Ia 型超新星(SNeIa)提供了宇宙加速膨胀的第一手证据,至今仍是宇宙学的重要探针。由于观测到Ia型超新星的光度与光度量之间存在相关性,它们被认为是可标准化的烛光。在考虑了观测到的变化之后,可以利用这一特性来估算宇宙学距离。然而,在目前最先进的标准化方法中,仍然存在一个未考虑到的离散性问题。为了探讨这个问题,我们提出了一种简单的线性三分量静帧光通量描述光曲线拟合器。由于SNIa固有色度指数的变化预计与时间有关,我们的描述建立在著名的光谱自适应光曲线模板2(SALT2)的数学表达基础之上,同时去掉了指数因子,并增加了一个与时间和波长有关的额外模型分量。模型分量是通过对代表性训练集进行主成分分析(PCA)或因子分析(FA)获得的。我们评估了被称为 "超新星纯膨胀模板"(PETS)的模型的约束能力,发现Ωm0和ΩΛ0与SALT2的结果是兼容的,两个模型之间的不确定性在68%以内,PETS的拟合参数与SALT2的参数呈不可忽略的线性相关。对于 PCA 和 FA 模型版本,我们都验证了第一分量主要描述了色度指数的变化,这证明它是 SNIa 光谱的主要影响因素。在最初的二进制宇宙学分析中,与色度指数变化类似的拟合参数相乘的模型干扰参数显示了随红移的演变。这种行为可能是由于选择效应造成的,应该用红移更高的 SNeIa 样本来进一步研究。总的来说,我们的模型还是有希望的,因为还有一些方面需要改进;然而,它在减少未计算的离散性方面仍然存在不足。
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来源期刊
Astronomy and Computing
Astronomy and Computing ASTRONOMY & ASTROPHYSICSCOMPUTER SCIENCE,-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.10
自引率
8.00%
发文量
67
期刊介绍: Astronomy and Computing is a peer-reviewed journal that focuses on the broad area between astronomy, computer science and information technology. The journal aims to publish the work of scientists and (software) engineers in all aspects of astronomical computing, including the collection, analysis, reduction, visualisation, preservation and dissemination of data, and the development of astronomical software and simulations. The journal covers applications for academic computer science techniques to astronomy, as well as novel applications of information technologies within astronomy.
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