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The characterization of the dust polarization foreground to the Cosmic Microwave Background (CMB) is a necessary step towards the detection of the B-mode signal associated with primordial gravitational waves. We present a method to simulate maps of polarized dust emission on the sphere, similarly to what is done for the CMB anisotropies. This method builds on the understanding of Galactic polarization stemming from the analysis of Planck data. It relates the dust polarization sky to the structure of the Galactic magnetic field and its coupling with interstellar matter and turbulence. The Galactic magnetic field is modelled as a superposition of a mean uniform field and a random component with a power-law power spectrum of exponent $alpha_{rm M}$. The model parameters are constrained to fit the power spectra of dust polarization EE, BB and TE measured using Planck data. We find that the slopes of the E and B power spectra of dust polarization are matched for $alpha_{rm M} = -2.5$. The model allows us to compute multiple realizations of the Stokes Q and U maps for different realizations of the random component of the magnetic field, and to quantify the variance of dust polarization spectra for any given sky area outside of the Galactic plane. The simulations reproduce the scaling relation between the dust polarization power and the mean total dust intensity including the observed dispersion around the mean relation. We also propose a method to carry out multi-frequency simulations including the decorrelation measured recently by Planck, using a given covariance matrix of the polarization maps. These simulations are well suited to optimize component separation methods and to quantify the confidence with which the dust and CMB B-modes can be separated in present and future experiments. We also provide an astrophysical perspective on our modeling of the dust polarization spectra.
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Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the field of cosmology. Community-based White Paper to Astro2010 in response to the call for such papers.
Polarized Galactic foregrounds are one of the primary sources of systematic error in measurements of the B-mode polarization of the Cosmic Microwave Background (CMB). Experiments are becoming increasingly sensitive to complexities in the foreground frequency spectra that are not captured by standard parametric models, potentially affecting our ability to efficiently separate out these components. Employing a suite of dust models encompassing a variety of physical effects, we simulate observations of a future seven-band CMB experiment to assess the impact of these complexities on parametric component separation. We identify configurations of frequency bands that minimize the `model errors caused by fitting simple parametric models to more complex `true foreground spectra, which bias the inferred CMB signal. We find that: (a) fits employing a simple two parameter modified blackbody (MBB) dust model tend to produce significant bias in the recovered polarized CMB signal in the presence of physically realistic dust foregrounds; (b) generalized MBB models with three additional parameters reduce this bias in most cases, but non-negligible biases can remain, and can be hard to detect; and (c) line of sight effects, which give rise to frequency decorrelation, and the presence of iron grains are the most problematic complexities in the dust emission for recovering the true CMB signal. More sophisticated simulations will be needed to demonstrate that future CMB experiments can successfully mitigate these more physically realistic dust foregrounds.
Dust emission is the main foreground for cosmic microwave background (CMB) polarization. Its statistical characterization must be derived from the analysis of observational data because the precision required for a reliable component separation is far greater than what is currently achievable with physical models of the turbulent magnetized interstellar medium. This letter takes a significant step toward this goal by proposing a method that retrieves non-Gaussian statistical characteristics of dust emission from noisy Planck polarization observations at 353 GHz. We devised a statistical denoising method based on wavelet phase harmonics (WPH) statistics, which characterize the coherent structures in non-Gaussian random fields and define a generative model of the data. The method was validated on mock data combining a dust map from a magnetohydrodynamic simulation and Planck noise maps. The denoised map reproduces the true power spectrum down to scales where the noise power is an order of magnitude larger than that of the signal. It remains highly correlated to the true emission and retrieves some of its non-Gaussian properties. Applied to Planck data, the method provides a new approach to building a generative model of dust polarization that will characterize the full complexity of the dust emission. We also release PyWPH, a public Python package, to perform GPU-accelerated WPH analyses on images.
The CMB polarization promises to unveil the dawn of time measuring the gravitational wave background emitted by the Inflation. The CMB signal is faint, however, and easily contaminated by the Galactic foreground emission, accurate measurements of which are thus crucial to make CMB observations successful. We review the CMB polarization properties and the current knowledge on the Galactic synchrotron emission, which dominates the foregrounds budget at low frequency. We then focus on the S-Band Polarization All Sky Survey (S-PASS), a recently completed survey of the entire southern sky designed to investigate the Galactic CMB foreground.
Using Planck polarization data, we search for and constrain spatial variations of the polarized dust foreground for cosmic microwave background (CMB) observations, specifically in its spectral index, $beta_d$. Failure to account for such variations will cause errors in the foreground cleaning that propagate into errors on cosmological parameter recovery from the cleaned CMB map. It is unclear how robust prior studies of the Planck data which constrained $beta_d$ variations are due to challenges with noise modeling, residual systematics, and priors. To clarify constraints on $beta_d$ and its variation, we employ two pixel space analyses of the polarized dust foreground at $>3.7^{circ}$ scales on $approx 60%$ of the sky at high Galactic latitudes. A template fitting method, which measures $beta_d$ over three regions of $approx 20%$ of the sky, does not find significant deviations from an uniform $beta_d = 1.55$, consistent with prior Planck determinations. An additional analysis in these regions, based on multifrequency fits to a dust and CMB model per pixel, puts limits on $sigma_{beta_d}$, the Gaussian spatial variation in $beta_d$. At the highest latitudes, the data support $sigma_{beta_d}$ up to $0.45$, $0.30$ at mid-latitudes, and $0.15$ at low-latitudes. We also demonstrate that care must be taken when interpreting the current Planck constraints, $beta_d$ maps, and noise simulations. Due to residual systematics and low dust signal to noise at high latitudes, forecasts for ongoing and future missions should include the possibility of large values of $sigma_{beta_d}$ as estimated in this paper, based on current polarization data.
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