A novel CMB component separation method: hierarchical generalized morphological component analysis

• DOI: 10.1093/mnras/staa744
• Publication Date: 2020-03-18T13:40:03Z
• Authors: Sebastian Wagner-...; Max Hopkins; Ana Diaz Rivero; Cora Dvorkin
• Keywords: Cosmic background radiation; Component (thermodynamics); Hierarchical database model

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), Bayesian graphical model test our method Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous emission, show HGMCA reduces contamination $25{{\ \rm per\ cent}}$ over in both regions included excluded Planck UT78 mask, decreases error measurement CMB temperature power spectrum 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ all ℓ), correlation foregrounds. find equivalent or improved performance when compared state-of-the-art internal linear combination type algorithms these simulations, suggesting may be competitive alternative separation techniques previously applied observed data. Additionally, does not suffer perturb parameters alter realization, which suggests algorithm generalizes well beyond simplified simulations. Our results open new avenue constructing through analysis.