Deblurring the early Universe: reconstruction of primordial power spectrum from Planck CMB using image analysis techniques

被引:0
|
作者
Sohn, Wuhyun [1 ]
Shafieloo, Arman [1 ,2 ]
Hazra, Dhiraj Kumar [3 ,4 ,5 ]
机构
[1] Korea Astron & Space Sci Inst, 776 Daedeok Daero, Daejeon 34055, South Korea
[2] Univ Sci & Technol, Daejeon 34113, South Korea
[3] HBNI, Inst Math Sci, Chennai 600113, India
[4] Homi Bhabha Natl Inst, Training Sch Complex, Mumbai 400094, India
[5] Osservatorio Astrofis & Sci Spazio, INAF OAS Bologna, Area Ric CNR INAF, Via Gobetti 101, I-40129 Bologna, Italy
基金
新加坡国家研究基金会;
关键词
cosmological parameters from CMBR; physics of the early universe; Statistical sampling techniques; Frequentist statistics; APM GALAXY SURVEY; FEATURES;
D O I
暂无
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
While the simplest inflationary models predict the primordial perturbations to be near scale -invariant, the primordial power spectrum (PPS) can exhibit oscillatory features in many physically well -motivated models. We search for hints of such features via freeform reconstructions of the PPS based on Planck 2018 CMB temperature and polarization anisotropies. In order to robustly invert the oscillatory integrals and handle noisy unbinned data, we draw inspiration from image analysis techniques. In previous works, the RichardsonLucy deconvolution algorithm for deblurring images has been modified for reconstructing PPS from the CMB temperature angular power spectrum. We extensively develop the methodology by including CMB polarization and introducing two new regularization techniques, also inspired by image analysis and adapted for our cosmological context. Regularization is essential for improving the fit to the temperature and polarization channels (TT, TE and EE) simultaneously without sacrificing one for another. The reconstructions we obtain are consistent with previous findings from temperature -only analyses. We evaluate the statistical significance of the oscillatory features in our reconstructions using mock data and find the observations to be consistent with having a featureless PPS. The machinery developed here will be a complimentary tool in the search for features with upcoming CMB surveys. Our methodology also shows competitive performance in image deconvolution tasks, which have various applications from microscopy to medical imaging.
引用
收藏
页数:24
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