On the non-Gaussian errors in high-z supernovae type Ia data  

作　　者：Meghendra Singh Ashwini Pandey Amit Sharma Shashikant Gupta Satendra Sharma 

机构地区：[1]Dr. A.EJ. Abdul Kalam Technical University, Uttar Pradesh, Lucknow 226021, India [2]GD Goenka University, Gurgaon, Haryana 122103, India [3]Yobe State University, Damaturu, Yobe State, Nigeria

出　　处：《Research in Astronomy and Astrophysics》2016年第11期53-56,共4页天文和天体物理学研究（英文版）

基　　金：DMRC for support

摘　　要：The nature of random errors in any data set is Gaussian, which is a well established fact according to the Central Limit Theorem. Supernovae type Ia data have played a crucial role in major discoveries in cosmology. Unlike in laboratory experiments, astronomical measurements cannot be performed in controlled situations. Thus, errors in astronomical data can be more severe in terms of systematics and non-Gaussianity compared to those of laboratory experiments. In this paper, we use the Kolmogorov-Smiruov statistic to test non-Gaussianity in high-z supernovae data. We apply this statistic to four data sets, i.e., Gold data （2004）, Gold data （2007）, the Union2 catalog and the Union2.1 data set for our analysis. Our results show that in all four data sets the errors are consistent with a Gaussian distribution.The nature of random errors in any data set is Gaussian, which is a well established fact according to the Central Limit Theorem. Supernovae type Ia data have played a crucial role in major discoveries in cosmology. Unlike in laboratory experiments, astronomical measurements cannot be performed in controlled situations. Thus, errors in astronomical data can be more severe in terms of systematics and non-Gaussianity compared to those of laboratory experiments. In this paper, we use the Kolmogorov-Smiruov statistic to test non-Gaussianity in high-z supernovae data. We apply this statistic to four data sets, i.e., Gold data （2004）, Gold data （2007）, the Union2 catalog and the Union2.1 data set for our analysis. Our results show that in all four data sets the errors are consistent with a Gaussian distribution.

关 键 词：cosmology - data analysis - statistics - probability 

分 类 号：P145.3[天文地球—天体物理]