2019/05/31 by P. Campeti, Paolo Campeti, D. Poletti +3 · 1 citation
Physics and Astronomy · #Astrophysics #Black Holes and Theoretical Physics #CMB cold spot #Cosmic background radiation #Cosmic microwave background #Cosmology and Gravitation Theories #Galaxies: Formation, Evolution, Phenomena #Galaxy #Gravitational lens #Physics #Principal component analysis #Quantum mechanics #Redshift #Spectral density #Statistical physics #Statistics #Tensor (intrinsic definition) #astro-ph.CO
paper · pdf · doi:10.1088/1475-7516/2019/09/055
published as JCAP09(2019)055 · Published in JCAP, 32 pages, 16 figures
openalex publication_date 2019/09/26 · arxiv created 2019/10/14 · arxiv updated 2019/10/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
We study how the shape of the spectrum of primordial gravitational waves can be constrained by future experiments looking at the B-mode of the Cosmic Microwave Background (CMB) polarization. We implement a Principal Component Analysis (PCA) including the effects of diffuse foreground residuals, following component separation, in the uncertainty of CMB angular power spectra, and taking into account the gravitational lensing by Large Scale Structure. We perform our study by considering the capabilities of future B-mode CMB experiments such as LiteBIRD, the Simons Observatory (SO) and Stage-IV (CMB-S4), in particular in detecting deviations of the primordial tensor spectrum from the scale-invariant behavior. We find that diffuse foreground residuals impact substantially both the derivation of the PCA basis and the corresponding constraining power, in all cases. In particular, depending on which experimental specifications and which value r of tensor-to-scalar ratio for cosmological perturbations are considered, adding foregrounds residuals can determine an increase as large as a factor ∼ 4 both on the uncertainty on r and on the recovery of the PCA modes. We study the limitations of the methodology, including the effect of physicality priors on the PCA, which we quantify via a Monte Carlo Markov chain (MCMC) analysis of the combined cosmological and PCA power spectrum parameter space.