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arXiv 1606.01779astro-ph.CO
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用改进的通量平均技术探索JLA超新星数据的宇宙学后果

Exploring the cosmological consequences of JLA supernova data with improved flux-averaging technique

Shuang Wang, Sixiang Wen, Miao Li

摘要:

在这项工作中,我们探索的宇宙学后果的“联合光变曲线分析”(JLA)超新星(SN)的数据,通过使用改进的通量平均(FA)技术,其中只有Ia型超新星(SNe Ia)在高红移的通量平均。采用品质因数(FoM)准则,考虑六种暗能量(DE)参数化,在$(z_{cut}, Δz)$平面上寻找最佳的FA配方,使DE约束最紧,其中$z_{cut}$和$Δz$分别为FA的红移截止和红移区间.在此基础上,讨论了不同的$z_{cut}$和不同的$Δz$对SN颜色光度参数的影响,回顾了SN颜色光度参数$β$的演化过程,研究了采用不同的FA配方对参数估计的影响。我们发现:(1)最佳FA配方是$(z_{cut} = 0.6, Δz=0.06)$,它对特定的DE参数不敏感。(2)在$z_{cut} \geq 0.4$上的通量平均JLA样本将产生比不使用FA的情况更严格的DE约束。(3)使用FA可以显著降低$β$的红移演化。(4)最佳FA配方有利于较大的分数物质密度$Ω_{m}$。总之,我们提出了一种处理JLA数据的替代方法,该方法可以降低SNe Ia的系统不确定性,同时给出更严格的DE约束。我们的方法将是有用的使用SNe Ia数据的精密宇宙学。

英文摘要:

In this work, we explore the cosmological consequences of the "Joint Light-curve Analysis" (JLA) supernova (SN) data by using an improved flux-averaging (FA) technique, in which only the type Ia supernovae (SNe Ia) at high redshift are flux-averaged. Adopting the criterion of figure of Merit (FoM) and considering six dark energy (DE) parameterizations, we search the best FA recipe that gives the tightest DE constraints in the $(z_{cut}, Δz)$ plane, where $z_{cut}$ and $Δz$ are redshift cut-off and redshift interval of FA, respectively. Then, based on the best FA recipe obtained, we discuss the impacts of varying $z_{cut}$ and varying $Δz$, revisit the evolution of SN color luminosity parameter $β$, and study the effects of adopting different FA recipe on parameter estimation. We find that: (1) The best FA recipe is $(z_{cut} = 0.6, Δz=0.06)$, which is insensitive to a specific DE parameterization. (2) Flux-averaging JLA samples at $z_{cut} \geq 0.4$ will yield tighter DE constraints than the case without using FA. (3) Using FA can significantly reduce the redshift-evolution of $β$. (4) The best FA recipe favors a larger fractional matter density $Ω_{m}$. In summary, we present an alternative method of dealing with JLA data, which can reduce the systematic uncertainties of SNe Ia and give the tighter DE constraints at the same time. Our method will be useful in the use of SNe Ia data for precision cosmology.

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