Reconstructing the evolution of deceleration parameter with the non-parametric Bayesian method

被引:2
|
作者
Xu, Bing [1 ,2 ,3 ]
Xia, Li-Xin [4 ]
机构
[1] Anhui Sci & Technol Univ, Sch Elect & Elect Engn, Bengbu 233030, Anhui, Peoples R China
[2] Hunan Normal Univ, Dept Phys, Changsha 410081, Hunan, Peoples R China
[3] Hunan Normal Univ, Synergist Innovat Ctr Quantum Effects & Applicat, Changsha 410081, Hunan, Peoples R China
[4] Kashgar Univ, Dept Phys, Kashgar 844006, Xinjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Cosmology; Cosmic acceleration; Deceleration parameter; BARYON ACOUSTIC-OSCILLATIONS; PROBE WMAP OBSERVATIONS; COSMIC ACCELERATION; SAMPLE;
D O I
10.1007/s10509-020-03755-z
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
In order to answer the question of whether the current acceleration of the cosmic expansion is slowing down or not, in this paper we use a non-parametric Bayesian method to reconstruct the evolution of the deceleration parameter q(z)from the latest observations including the type Ia supernova data, the baryon acoustic oscillation data, the Planck cosmic microwave background data, the Hubble data as well as the local value of Hubble constant. We find that all the data support a currently increasing cosmic acceleration, a spatially flat universe is favored and the effects of the spatial curvature on the reconstructed result are negligible. Moreover, the evolution of q(z) displays an oscillatory behavior, which is preferred by observations at the 3.2 sigma confidence level as compared with that in the CDM. But, the reconstructed q(z) is punished by the Bayesian information criteria due to more many model parameters.
引用
收藏
页数:7
相关论文
共 50 条
  • [31] Bayesian non-parametric method for decision support: Forecasting online product sales
    Wu, Ziyue
    Chen, Xi
    Gao, Zhaoxing
    DECISION SUPPORT SYSTEMS, 2023, 174
  • [32] MRI Denoising Based on a Non-Parametric Bayesian Image Sparse Representation Method
    Chen, Xian-bo
    Ding, Xing-hao
    Liu, Hui
    ADVANCED RESEARCH ON INFORMATION SCIENCE, AUTOMATION AND MATERIAL SYSTEM, PTS 1-6, 2011, 219-220 : 1354 - 1358
  • [33] A parametric reconstruction of the deceleration parameter
    Abdulla Al Mamon
    Sudipta Das
    The European Physical Journal C, 2017, 77
  • [34] A parametric reconstruction of the deceleration parameter
    Al Mamon, Abdulla
    Das, Sudipta
    EUROPEAN PHYSICAL JOURNAL C, 2017, 77 (07):
  • [35] Parametric and Non-parametric Bayesian Imputation for Right Censored Survival Data
    Moghaddam, Shirin
    Newell, John
    Hinde, John
    DEVELOPMENTS IN STATISTICAL MODELLING, IWSM 2024, 2024, : 153 - 158
  • [36] Bayesian Non-Parametric Parsimonious Gaussian Mixture for Clustering
    Chamroukhi, Faicel
    Bartcus, Marius
    Glotin, Herve
    2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2014, : 1460 - 1465
  • [37] Bayesian rendering with non-parametric multiscale prior model
    Mignotte, M
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL I, PROCEEDINGS, 2002, : 247 - 250
  • [38] Bayesian non-parametric detection heterogeneity in ecological models
    Daniel Turek
    Claudia Wehrhahn
    Olivier Gimenez
    Environmental and Ecological Statistics, 2021, 28 : 355 - 381
  • [39] Non-parametric and unsupervised Bayesian classification with Bootstrap sampling
    Zribi, M
    IMAGE AND VISION COMPUTING, 2004, 22 (01) : 1 - 8
  • [40] Controlling the reinforcement in Bayesian non-parametric mixture models
    Lijoi, Antonio
    Mena, Ramses H.
    Prunster, Igor
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2007, 69 : 715 - 740