skip to main content

Title: A novel CMB component separation method: hierarchical generalized morphological component analysis
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 more » for constructing CMB maps through Bayesian hierarchical analysis. « less
Authors:
; ; ;
Award ID(s):
1813694
Publication Date:
NSF-PAR ID:
10173825
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
494
Issue:
1
Page Range or eLocation-ID:
1507 to 1529
ISSN:
0035-8711
Sponsoring Org:
National Science Foundation
More Like this
  1. ABSTRACT In this work, we examine the impact of our motion with respect to the Cosmic Microwave Background (CMB) rest frame on statistics of CMB maps by examining the one-, two-, three-, and four- point statistics of simulated maps of the CMB and Sunyaev–Zeldovich (SZ) effects. We validate boosting codes by comparing their outcomes for temperature and polarization power spectra up to ℓ ≃ 6000. We derive and validate a new analytical formula for the computation of the boosted power spectrum of a signal with a generic frequency dependence. As an example we show how this increases the boosting correction to the power spectrum of CMB intensity measurements by ${\sim}30{{\ \rm per\ cent}}$ at 150 GHz. We examine the effect of boosting on thermal and kinetic SZ power spectra from semianalytical and hydrodynamical simulations; the boosting correction is generally small for both simulations, except when considering frequencies near the tSZ null. For the non-Gaussian statistics, in general we find that boosting has no impact with two exceptions. We find that, whilst the statistics of the CMB convergence field are unaffected, quadratic estimators that are used to measure this field can become biased at the $O(1){{\ \rm per\ cent}}$ level by boostingmore »effects. We present a simple modification to the standard estimators that removes this bias. Second, bispectrum estimators can receive a systematic bias from the Doppler induced quadrupole when there is anisotropy in the sky – in practice this anisotropy comes from masking and inhomogeneous noise. This effect is unobservable and already removed by existing analysis methods.« less
  2. ABSTRACT

    In order to better analyse the polarization of the cosmic microwave background (CMB), which is dominated by emission from our Galaxy, we need tools that can detect residual foregrounds in cleaned CMB maps. Galactic foregrounds introduce statistical anisotropy and directionality to the polarization pseudo-vectors of the CMB, which can be investigated by using the $\mathcal {D}$ statistic of Bunn and Scott. This statistic is rapidly computable and capable of investigating a broad range of data products for directionality. We demonstrate the application of this statistic to detecting foregrounds in polarization maps by analysing the uncleaned Planck 2018 frequency maps. For the Planck 2018 CMB maps, we find no evidence for residual foreground contamination. In order to examine the sensitivity of the $\mathcal {D}$ statistic, we add a varying fraction of the polarized thermal dust and synchrotron foreground maps to the CMB maps and show the per cent-level foreground contamination that would be detected with 95 per cent confidence. We also demonstrate application of the $\mathcal {D}$ statistic to another data product by analysing the gradient of the minimum-variance CMB lensing potential map (i.e. the deflection angle) for directionality. We find no excess directionality in the lensing potential map when compared to the simulationsmore »provided by the Planck Collaboration.

    « less
  3. ABSTRACT The Cold Spot is a puzzling large-scale feature in the Cosmic Microwave Background temperature maps and its origin has been subject to active debate. As an important foreground structure at low redshift, the Eridanus supervoid was recently detected, but it was subsequently determined that, assuming the standard ΛCDM model, only about 10–20 per cent of the observed temperature depression can be accounted for via its Integrated Sachs–Wolfe imprint. However, R ≳ 100 h−1Mpc supervoids elsewhere in the sky have shown ISW imprints AISW ≈ 5.2 ± 1.6 times stronger than expected from ΛCDM (AISW = 1), which warrants further inspection. Using the Year-3 redMaGiC catalogue of luminous red galaxies from the Dark Energy Survey, here we confirm the detection of the Eridanus supervoid as a significant underdensity in the Cold Spot’s direction at z < 0.2. We also show, with S/N ≳ 5 significance, that the Eridanus supervoid appears as the most prominent large-scale underdensity in the dark matter mass maps that we reconstructed from DES Year-3 gravitational lensing data. While we report no significant anomalies, an interesting aspect is that the amplitude of the lensing signal from the Eridanus supervoid at the Cold Spot centre is about 30 per cent lower thanmore »expected from similar peaks found in N-body simulations based on the standard ΛCDM model with parameters Ωm = 0.279 and σ8 = 0.82. Overall, our results confirm the causal relation between these individually rare structures in the cosmic web and in the CMB, motivating more detailed future surveys in the Cold Spot region.« less
  4. ABSTRACT In the frame of the Solar system, the Doppler and aberration effects cause distortions in the form of mode couplings in the cosmic microwave background (CMB) temperature and polarization power spectra and, hence, impose biases on the statistics derived by the moving observer. We explore several aspects of such biases and pay close attention to their effects on CMB polarization, which, previously, have not been examined in detail. A potentially important bias that we introduce here is boost variance—an additional term in cosmic variance, induced by the observer’s motion. Although this additional term is negligible for whole-sky experiments, in partial-sky experiments it can reach 10 per cent (temperature) to 20 per cent (polarization) of the standard cosmic variance (σ). Furthermore, we investigate the significance of motion-induced power and parity asymmetries in TT, EE, and TE as well as potential biases induced in cosmological parameter estimation performed with whole-sky TTTEEE. Using Planck-like simulations, we find that our local motion induces $\sim 1\!-\!2 {{\ \rm per\ cent}}$ hemispherical asymmetry in a wide range of angular scales in the CMB temperature and polarization power spectra; however, it does not imply any significant amount of parity asymmetry or shift in cosmological parameters. Finally, we examine the prospectsmore »of measuring the velocity of the Solar system w.r.t. the CMB with future experiments via the mode coupling induced by the Doppler and aberration effects. Using the CMB TT, EE, and TE power spectra up to ℓ = 4000, the Simons Observatory and CMB-S4 can make a dipole-independent measurement of our local velocity, respectively, at 8.5σ and 20σ.« less
  5. null (Ed.)
    ABSTRACT Separating galactic foreground emission from maps of the cosmic microwave background (CMB) and quantifying the uncertainty in the CMB maps due to errors in foreground separation are important for avoiding biases in scientific conclusions. Our ability to quantify such uncertainty is limited by our lack of a model for the statistical distribution of the foreground emission. Here, we use a deep convolutional generative adversarial network (DCGAN) to create an effective non-Gaussian statistical model for intensity of emission by interstellar dust. For training data we use a set of dust maps inferred from observations by the Planck satellite. A DCGAN is uniquely suited for such unsupervised learning tasks as it can learn to model a complex non-Gaussian distribution directly from examples. We then use these simulations to train a second neural network to estimate the underlying CMB signal from dust-contaminated maps. We discuss other potential uses for the trained DCGAN, and the generalization to polarized emission from both dust and synchrotron.