Application of Bayesian graphs to SN Ia data analysis and compression
文献类型：期刊论文
| 作者 | Ma, Cong1,2,3; Corasaniti, Pier-Stefano3; Bassett, Bruce A.4,5,6 |
| 刊名 | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
 |
| 出版日期 | 2016-12-01 |
| 卷号 | 463期号:2页码:1651-1665 |
| ISSN号 | 0035-8711 |
| 关键词 | Methods: Data Analysis Methods: Statistical Supernovae: General Cosmological Parameters Distance Scale |
| DOI | 10.1093/mnras/stw2069 |
| 英文摘要 | Bayesian graphical models are an efficient tool for modelling complex data and derive self-consistent expressions of the posterior distribution of model parameters. We apply Bayesian graphs to perform statistical analyses of Type Ia supernova (SN Ia) luminosity distance measurements from the joint light-curve analysis (JLA) data set. In contrast to the chi(2) approach used in previous studies, the Bayesian inference allows us to fully account for the standard-candle parameter dependence of the data covariance matrix. Comparing with chi(2) analysis results, we find a systematic offset of the marginal model parameter bounds. We demonstrate that the bias is statistically significant in the case of the SN Ia standardization parameters with a maximal 6s shift of the SN light-curve colour correction. In addition, we find that the evidence for a host galaxy correction is now only 2.4s. Systematic offsets on the cosmological parameters remain small, but may increase by combining constraints from complementary cosmological probes. The bias of the chi(2) analysis is due to neglecting the parameter-dependent log-determinant of the data covariance, which gives more statistical weight to larger values of the standardization parameters. We find a similar effect on compressed distance modulus data. To this end, we implement a fully consistent compression method of the JLA data set that uses a Gaussian approximation of the posterior distribution for fast generation of compressed data. Overall, the results of our analysis emphasize the need for a fully consistent Bayesian statistical approach in the analysis of future large SN Ia data sets. |
| WOS关键词 | HUBBLE-SPACE-TELESCOPE ; SUPERNOVA LEGACY SURVEY ; DARK-ENERGY ; SYSTEMATIC UNCERTAINTIES ; COSMOLOGICAL PARAMETERS ; MODEL SELECTION ; STAR-FORMATION ; HOST GALAXIES ; LIGHT CURVES ; SDSS-II |
| WOS研究方向 | Astronomy & Astrophysics |
| 语种 | 英语 |
| 出版者 | OXFORD UNIV PRESS |
| WOS记录号 | WOS:000388122400041 |
| 源URL | [http://libir.pmo.ac.cn/handle/332002/24104]  |
| 专题 | 中国科学院紫金山天文台 |
| 通讯作者 | Ma, Cong |
| 作者单位 | 1.Chinese Acad Sci, Purple Mt Observ, 2 West Beijing Rd, Nanjing 210008, Jiangsu, Peoples R China 2.Univ Chinese Acad Sci, Grad Sch, 19A Yuquan Rd, Beijing 100049, Peoples R China 3.Univ Paris Diderot, PSL Res Univ, Observ Paris, LUTH,UMR CNRS 8102, 5 Pl Jules Janssen, F-92190 Meudon, France 4.Univ Cape Town, Dept Math & Appl Math, Cross Campus Rd, ZA-7700 Rondebosch, South Africa 5.African Inst Math Sci, 6-8 Melrose Rd, ZA-7945 Muizenberg, South Africa 6.South African Astron Observ, Observ Rd, ZA-7925 Observatory, South Africa |
| 推荐引用方式 GB/T 7714 | Ma, Cong,Corasaniti, Pier-Stefano,Bassett, Bruce A.. Application of Bayesian graphs to SN Ia data analysis and compression[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2016,463(2):1651-1665. |
| APA | Ma, Cong,Corasaniti, Pier-Stefano,&Bassett, Bruce A..(2016).Application of Bayesian graphs to SN Ia data analysis and compression.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,463(2),1651-1665. |
| MLA | Ma, Cong,et al."Application of Bayesian graphs to SN Ia data analysis and compression".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 463.2(2016):1651-1665. |
入库方式： OAI收割
来源：紫金山天文台
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。