A novel CMB component separation method: hierarchical generalized morphological component analysis
[1];
- Department of Physics, Harvard University, Cambridge, MA 02138, USA, Department of Physics, Stanford University, Stanford, CA 94305, USA
- Department of Mathematics, Harvard University, Cambridge, MA 02138, USA, Department of Computer Science and Engineering, University of California San Diego, San Diego, CA 92092, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
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), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $$25{{\ \rm per\ cent}}$$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $$\lt 0.26{{\ \rm per\ cent}}$$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.
- Sponsoring Organization:
- USDOE; National Science Foundation (NSF)
- Grant/Contract Number:
- SC0020223
- OSTI ID:
- 1632766
- Journal Information:
- Monthly Notices of the Royal Astronomical Society, Journal Name: Monthly Notices of the Royal Astronomical Society Journal Issue: 1 Vol. 494; ISSN 0035-8711
- Publisher:
- Royal Astronomical SocietyCopyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
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