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Register a new userA minimal power-spectrum-based moment expansion for CMB B-mode searches
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The characterization and modeling of polarized foregrounds has become a critical issue in the quest for primordial $B$-modes. A typical method to proceed is to factorize and parametrize the spectral properties of foregrounds and their scale dependence (i.e. assuming that foreground spectra are well described everywhere by their sky average). Since in reality foreground properties vary across the Galaxy, this assumption leads to inaccuracies in the model that manifest themselves as biases in the final cosmological parameters (in this case the tensor-to-scalar ratio $r$). This is particularly relevant for surveys over large fractions of the sky, such as the Simons Observatory (SO), where the spectra should be modeled over a distribution of parameter values. Here we propose a method based on the existing ``moment expansion approach to address this issue in a power-spectrum-based analysis that is directly applicable in ground-based multi-frequency data. Additionally, the method uses only a small set of parameters with simple physical interpretation, minimizing the impact of foreground uncertainties on the final $B$-mode constraints. We validate the method using SO-like simulated observations, recovering an unbiased estimate of the tensor-to-scalar ratio $r$ with standard deviation $sigma(r)simeq0.003$, compatible with official forecasts. When applying the method to the public BICEP2/Keck data, we find an upper bound $r<0.06$ ($95%,{rm C.L.}$), compatible with the result found by BICEP2/Keck when parametrizing spectral index variations through a scale-independent frequency decorrelation parameter. We also discuss the formal similarities between the power spectrum-based moment expansion and methods used in the analysis of CMB lensing.
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We present a measurement of the $B$-mode polarization power spectrum of the cosmic microwave background (CMB) using taken from July 2014 to December 2016 with the POLARBEAR experiment. The CMB power spectra are measured using observations at 150 GHz with an instantaneous array sensitivity of $mathrm{NET}_mathrm{array}=23, mu mathrm{K} sqrt{mathrm{s}}$ on a 670 square degree patch of sky centered at (RA, Dec)=($+0^mathrm{h}12^mathrm{m}0^mathrm{s},-59^circ18^prime$). A continuously rotating half-wave plate is used to modulate polarization and to suppress low-frequency noise. We achieve $32,mumathrm{K}$-$mathrm{arcmin}$ effective polarization map noise with a knee in sensitivity of $ell = 90$, where the inflationary gravitational wave signal is expected to peak. The measured $B$-mode power spectrum is consistent with a $Lambda$CDM lensing and single dust component foreground model over a range of multipoles $50 leq ell leq 600$. The data disfavor zero $C_ell^{BB}$ at $2.2sigma$ using this $ell$ range of POLARBEAR data alone. We cross-correlate our data with Planck high frequency maps and find the low-$ell$ $B$-mode power in the combined dataset to be consistent with thermal dust emission. We place an upper limit on the tensor-to-scalar ratio $r < 0.90$ at 95% confidence level after marginalizing over foregrounds.
Detecting the imprint of inflationary gravitational waves on the $B$-mode polarization of the Cosmic Microwave Background (CMB) is one of the main science cases for current and next-generation CMB experiments. In this work we explore some of the challenges that ground-based facilities will have to face in order to carry out this measurement in the presence of Galactic foregrounds and correlated atmospheric noise. We present forecasts for Stage-3 (S3) and planned Stage-4 (S4) experiments based on the analysis of simulated sky maps using a map-based Bayesian foreground cleaning method. Our results thus consistently propagate the uncertainties on foreground parameters such as spatially-varying spectral indices, as well as the bias on the measured tensor-to-scalar ratio $r$ caused by an incorrect modelling of the foregrounds. We find that S3 and S4-like experiments should be able to put constraints on $r$ of the order $sigma(r)=(0.5-1.0)times10^{-2}$ and $sigma(r)=(0.5-1.0)times10^{-3}$ respectively, assuming instrumental systematic effects are under control. We further study deviations from the fiducial foreground model, finding that, while the effects of a second polarized dust component would be minimal on both S3 and S4, a 2% polarized anomalous dust emission (AME) component would be clearly detectable by Stage-4 experiments.
Estimation of the B-mode angular power spectrum of polarized anisotropies of the cosmic microwave background (CMB) is a key step towards a full exploitation of the scientific potential of this probe. In the context of pseudo-spectrum methods the major challenge is related to a contamination of the B-mode spectrum estimate with residual power of much larger E-mode. This so-called E-to-B leakage is unavoidably present whenever an incomplete sky map is only available, as is the case for any realistic observation. The leakage has to be then minimized or removed and ideally in such a way that neither a bias nor extra variance is introduced. In this paper, we compare from these two perspectives three different methods proposed recently in this context Refs. Smith 2006, Zhao & Baskaran 2010, Kim & Naselsky 2010, which we first introduce within a common algebraic framework of the so-called chi-fields and then study their performance on two different experimental configurations - one corresponding to a small-scale experiment covering 1% of the sky motivated by current ground-based or balloon-borne experiments and another - to a nearly full-sky experiment, e.g., a possible CMB B-mode satellite mission. We find that though all these methods allow to reduce significantly the level of the E-to-B leakage, it is the method of Smith 2006, which at the same time ensures the smallest error bars in all experimental configurations studied here, owing to the fact that it permits straightforwardly for an optimization of the sky apodization of the polarization maps used for the estimation. For a satellite-like experiment, this method enables a detection of B-mode power spectrum at large angular scales but only after appropriate binning. The method of Zhao & Baskaran 2010 is a close runner-up in the case of a nearly full sky coverage.
The cosmic microwave background (CMB) power spectrum is a powerful cosmological probe as it entails almost all the statistical information of the CMB perturbations. Having access to only one sky, the CMB power spectrum measured by our experiments is only a realization of the true underlying angular power spectrum. In this paper we aim to recover the true underlying CMB power spectrum from the one realization that we have without a need to know the cosmological parameters. The sparsity of the CMB power spectrum is first investigated in two dictionaries; Discrete Cosine Transform (DCT) and Wavelet Transform (WT). The CMB power spectrum can be recovered with only a few percentage of the coefficients in both of these dictionaries and hence is very compressible in these dictionaries. We study the performance of these dictionaries in smoothing a set of simulated power spectra. Based on this, we develop a technique that estimates the true underlying CMB power spectrum from data, i.e. without a need to know the cosmological parameters. This smooth estimated spectrum can be used to simulate CMB maps with similar properties to the true CMB simulations with the correct cosmological parameters. This allows us to make Monte Carlo simulations in a given project, without having to know the cosmological parameters. The developed IDL code, TOUSI, for Theoretical pOwer spectrUm using Sparse estImation, will be released with the next version of ISAP.
In this work we present a Neural Network (NN) algorithm for the identification of the appropriate parametrization of diffuse polarized Galactic emissions in the context of Cosmic Microwave Background (CMB) $B$-mode multi-frequency observations. In particular, we have focused our analysis on low frequency foregrounds relevant for polarization observation: namely Galactic Synchrotron and Anomalous Microwave Emission (AME). We have implemented and tested our approach on a set of simulated maps corresponding to the frequency coverage and sensitivity represented by future satellite and low frequency ground based probes. The NN efficiency in recognizing the right parametrization of foreground emission in different sky regions reaches an accuracy of about $90%$. We have compared this performance with the $chi^{2}$ information following parametric foreground estimation using multi-frequency fitting, and quantify the gain provided by a NN approach. Our results show the relevance of model recognition in CMB $B$-mode observations, and highlight the exploitation of dedicated procedures to this purpose.
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