2021/01/31 by Joel Williams, Nialh McCallum, Aditya Rotti +5 · 5 citations
Environmental Science · Mathematics · Physics and Astronomy · #Algorithm #Astrophysics #Climate variability and models #Computer science #Cosmic background radiation #Cosmic microwave background #Cosmology and Gravitation Theories #Estimator #Galaxies: Formation, Evolution, Phenomena #Galaxy #Gaussian #Mathematics #Optics #Physics #Quadratic equation #Quantum mechanics #Redshift #Statistical physics #Statistics #Weak gravitational lensing #astro-ph.CO
paper · pdf · open access · doi:10.1088/1475-7516/2021/07/016
published in Journal of Cosmology and Astroparticle Physics 2021(07), 016 (Institute of Physics) · 30 pages, 12 figures, prepared for submission to JCAP
openalex created_date 2021/02/01 · openalex publication_date 2021/07/01 · arxiv created 2021/07/10 · arxiv updated 2021/07/13 · openalex updated_date 2026/08/05
Abstract We present the first detailed case study using quadratic estimators (QE) to diagnose and remove systematics present in observed Cosmic Microwave Background (CMB) maps. In this work we focus on the temperature to polarization leakage. We use an iterative QE analysis to remove systematics, in analogy to de-lensing, recovering the primordial B-mode signal and the systematic maps. We introduce a new Gaussian filtering scheme crucial to stable convergence of the iterative cleaning procedure and validate with comparisons to semi-analytical forecasts. We study the limitations of this method by examining its performance both on idealized simulations and on more realistic, non-ideal simulations, where we assume varying de-lensing efficiencies. Finally, we quantify the systematic cleaning efficiency by presenting a likelihood analysis on the tensor to scalar ratio, r , and demonstrate that the blind cleaning results in an un-biased measurement of r , reducing the systematic induced B-mode power by nearly two orders of magnitude.