Cosmic Microwave Background Component Research Articles

B-mode polarization forecasts for GreenPol

We present tensor-to-scalar ratio forecasts for GreenPol, a hypothetical ground-based B-mode experiment aiming to survey the cleanest regions of the Northern Galactic Hemisphere at five frequencies between 10 and 44 GHz. Its primary science goal would be to measure large-scale cosmic microwave background (CMB) polarization fluctuations at multipoles ℓ ≲ 500, and thereby constrain the primordial tensor-to-scalar ratio r. The observations for the suggested experiment would take place at the Summit Station (72 ° 34N, 38 ° 27W) on Greenland, at an altitude of 3216 m above sea level. For this paper we simulated various experimental setups, and derived limits on the tensor-to-scalar ratio after CMB component separation using a Bayesian component separation implementation called Commander. When combining the proposed experiment with Planck HFI observations for constraining polarized thermal dust emission, we found a projected limit of r < 0.02 at 95% confidence for the baseline configuration. This limit is very robust with respect to a range of important experimental parameters, including sky coverage, detector weighting, foreground priors, among others. Overall, GreenPol would have the possibility to provide deep CMB polarization measurements of the Northern Galactic Hemisphere at low frequencies.

Frequency dependence of the thermal dust E/B ratio and EB correlation: Insights from the spin-moment expansion

The change of physical conditions across the turbulent and magnetized interstellar medium induces a 3D spatial variation of the properties of Galactic polarized emission. The observed signal results from the averaging of different spectral energy distributions (SEDs) and polarization angles along and between lines of sight. As a consequence, the total Stokes parameters Q and U will have different frequency dependencies, both departing from the canonical emission law, so that the polarization angle becomes frequency dependent. In the present work, we show how this phenomenon similarly induces a different, distorted SED for the three polarized angular power spectra 𝒟𝓁EE, 𝒟𝓁BB, and 𝒟𝓁EB, implying a variation of the 𝒟𝓁EE/𝒟𝓁BB ratio with frequency. We demonstrate how the previously introduced “spin-moment” formalism provides a natural framework to grasp these effects and enables us to derive analytical predictions for the spectral behaviors of the polarized spectra, focusing here on the example of thermal dust polarized emission. After a quantitative discussion based on a model combining emission from a filament with its background, we further reveal that the spectral complexity implemented in the dust models commonly used by the cosmic microwave background (CMB) community includes different distortions for the three polarized power-spectra. This new understanding is crucial for CMB component separation, in which extreme accuracy is required for the modeling of the dust signal to allow for the search of the primordial imprints of inflation or cosmic birefringence. For the latter, as long as the dust EB signal is not measured accurately, great caution is required regarding the assumptions made to model its spectral behavior, as it may not be inferred from the other dust angular power spectra.

Planck2018 results

We present full-sky maps of the cosmic microwave background (CMB) and polarized synchrotron and thermal dust emission, derived from the third set ofPlanckfrequency maps. These products have significantly lower contamination from instrumental systematic effects than previous versions. The methodologies used to derive these maps follow closely those described in earlier papers, adopting four methods (Commander,NILC,SEVEM, andSMICA) to extract the CMB component, as well as three methods (Commander,GNILC, andSMICA) to extract astrophysical components. Our revised CMB temperature maps agree with corresponding products in thePlanck2015 delivery, whereas the polarization maps exhibit significantly lower large-scale power, reflecting the improved data processing described in companion papers; however, the noise properties of the resulting data products are complicated, and the best available end-to-end simulations exhibit relative biases with respect to the data at the few percent level. Using these maps, we are for the first time able to fit the spectral index of thermal dust independently over 3° regions. We derive a conservative estimate of the mean spectral index of polarized thermal dust emission ofβd = 1.55 ± 0.05, where the uncertainty marginalizes both over all known systematic uncertainties and different estimation techniques. For polarized synchrotron emission, we find a mean spectral index ofβs = −3.1 ± 0.1, consistent with previously reported measurements. We note that the current data processing does not allow for construction of unbiased single-bolometer maps, and this limits our ability to extract CO emission and correlated components. The foreground results for intensity derived in this paper therefore do not supersede correspondingPlanck2015 products. For polarization the new results supersede the corresponding 2015 products in all respects.

Hierarchical Bayesian CMB component separation with the No-U-Turn Sampler

ABSTRACT In this paper, we present a novel implementation of Bayesian cosmic microwave background (CMB) component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient-based sampling algorithm. Alongside this, we introduce new foreground modelling approaches. We use the mean shift algorithm to define regions on the sky, clustering according to naively estimated foreground spectral parameters. Over these regions we adopt a complete pooling model, where we assume constant spectral parameters, and a hierarchical model, where we model individual pixel spectral parameters as being drawn from underlying hyperdistributions. We validate the algorithm against simulations of the LiteBIRD and C-Band All-Sky Survey (C-BASS) experiments, with an input tensor-to-scalar ratio of r = 5 × 10−3. Considering multipoles 30 ≤ ℓ < 180, we are able to recover estimates for r. With LiteBIRD-only observations, and using the complete pooling model, we recover r = (12.9 ± 1.4) × 10−3. For C-BASS and LiteBIRD observations we find r = (9.0 ± 1.1) × 10−3 using the complete pooling model, and r = (5.2 ± 1.0) × 10−3 using the hierarchical model. Unlike the complete pooling model, the hierarchical model captures pixel-scale spatial variations in the foreground spectral parameters, and therefore produces cosmological parameter estimates with reduced bias, without inflating their uncertainties. Measured by the rate of effective sample generation, NUTS offers performance improvements of ∼103 over using Metropolis–Hastings to fit the complete pooling model. The efficiency of NUTS allows us to fit the more sophisticated hierarchical foreground model that would likely be intractable with non-gradient-based sampling algorithms.

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 for constructing CMB maps through Bayesian hierarchical analysis.

Multi-resolution Bayesian CMB component separation through Wiener filtering with a pseudo-inverse preconditioner

We present a Bayesian model for multi-resolution component separation for cosmic microwave background (CMB) applications based on Wiener filtering and/or computation of constrained realizations, extending a previously developed framework. We also develop an efficient solver for the corresponding linear system for the associated signal amplitudes. The core of this new solver is an efficient preconditioner based on the pseudo-inverse of the coefficient matrix of the linear system. In the full sky coverage case, the method gives an increased speed of the preconditioner, and it is easier to implement in terms of practical computer code. In the case where a mask is applied and prior-driven constrained realization is sought within the mask, this is the first time full convergence has been achieved at the full resolution of the Planck data set.

Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background

Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high energy scales. We develop a new framework for cosmic string inference, constructing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension $G\mu$ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations we demonstrate the application of our framework and evaluate its performance. The method is sensitive to $G\mu \sim 5 \times 10^{-7}$ for Nambu-Goto string simulations that include an integrated Sachs-Wolfe (ISW) contribution only and do not include any recombination effects, before any parameters of the analysis are optimised. The sensitivity of the method compares favourably with other techniques applied to the same simulations.

DETECTION OF NEW POINT SOURCES INWMAP7 YEAR DATA USING INTERNAL TEMPLATES AND NEEDLETS

We have developed a new needlet based method to detect point sources in cosmic microwave background (CMB) maps and have applied it to the WMAP 7 year data. We use both the individual frequency channels as well as internal templates, the difference between pairs of frequency channels, with the advantage that the CMB component is eliminated. Using the area of the sky outside the Kq85 galactic mask, we detect a total of 2102 point sources at the $5\sigma$ level in either the frequency maps or the internal templates. Of these, 1116 are detected either at $5\sigma$ directly in the frequency channels or at $5\sigma$ in the internal templates and $\geq3\sigma$ at the corresponding position in the frequency channels. Of the 1116 sources, 603 are detections which have not been reported so far in WMAP data. We have made a catalogue of these sources available with position and flux estimated in the WMAP channels where they are seen. In total, we identified 1029 of the 1116 sources with counterparts at 5GHz and 69 at other frequencies.

Astrophysical image separation by blind time–frequency source separation methods

In this paper, two prevalent blind time–frequency (TF) source separation methods in the literature are adapted to astrophysical image mixtures and four algorithms are developed to separate them into their astrophysical components. The components considered in this work are cosmic microwave background (CMB) radiation, galactic dust and synchrotron, among which the CMB component is emphasized. These simulated components mixed via realistic coefficients are subjected to simulated additive, nonstationary Gaussian noise components of realistic power levels, to yield image mixtures on which our orthogonal and nonorthogonal TF algorithms are applied. The developed algorithms are compared with the FastICA algorithm and CMB component is found to be recovered with an improvement reaching to 3.25 decibels from CMB–synchrotron mixtures. The proposed techniques are believed to be generically applicable in separating other types of astrophysical components as well.

Angular power spectrum of the fastica cosmic microwave background component from Background Emission Anisotropy Scanning Telescope data

We present the angular power spectrum of the cosmic microwave background (CMB) component extracted with FASTICA from the Background Emission Anisotropy Scanning Telescope (BEAST) data. BEAST is a 2.2-m off-axis telescope with a focal plane comprising eight elements at Q (38‐45 GHz) and Ka (26‐36 GHz) bands. It operates from the UC (University of California) White Mountain Research Station at an altitude of 3800 m. The BEAST CMB angular power spectrum has already been calculated by O’Dwyer et al. using only the Q-band data. With two input channels, FASTICA returns two possible independent components. We found that one of these two has an unphysical spectral behaviour, while the other is a reasonable CMB component. After a detailed calibration procedure based on Monte Carlo (MC) simulations, we extracted the angular power spectrum for the identified CMB component and found a very good agreement with the already published BEAST CMB angular power spectrum and with the Wilkinson Microwave Anisotropy Probe (WMAP) data.

Effect of component separation on the temperature distribution of the cosmic microwave background

We present a study of the effect of component separation on the recovered cosmic microwave background (CMB) temperature distribution, considering Gaussian and non-Gaussian input CMB maps. In particular, the non-Gaussian maps have been generated as a mixture of a Gaussian CMB map and a cosmic strings map in different proportions. First, we extract the CMB component from simulated multifrequency Planck data (in small patches of the sky) using the maximum-entropy method (MEM), Wiener filter (WF) and a method based on the subtraction of foreground templates plus a linear combination of frequency channels (LCFC). We then apply a wavelet-based method to study the Gaussianity of the recovered CMB and compare it with the same analysis for the input map. When the original CMB map is Gaussian (and assuming that point sources have been removed), we find that neither MEM nor WF introduce non-Gaussianity in the CMB reconstruction. Regarding the LCFC, the Gaussian character is also preserved provided that the appropriate combination of frequency channels is used. On the contrary, if the input CMB map is non-Gaussian, all the studied methods produce a reconstructed CMB with lower detections of non-Gaussianity than the original map. This effect is mainly due to the presence of instrumental noise in the data, which clearly affects the quality of the reconstructions. In this case, MEM tends to produce slightly higher non-Gaussian detections in the reconstructed map than WF whereas the detections are lower for the LCFC. We have also studied the effect of point sources in the MEM reconstruction. If no attempt to remove point sources is performed, they clearly contaminate the CMB reconstruction, introducing spurious non-Gaussianity. When the brightest point sources are removed from the data using the Mexican Hat Wavelet, the Gaussian character of the CMB is preserved. However, when analysing larger regions of the sky, the variance of our estimators will be appreciably reduced and, in this case, we expect the point source residuals to introduce spurious non-Gaussianity in the CMB distribution. Therefore, a careful subtraction (or masking) of point source emission is crucial in order to be able to perform Gaussian analysis of the CMB.

Bulk Comptonization of the Cosmic Microwave Background by Extragalactic Jets as a Probe of Their Matter Content

We propose a method for estimating the composition, i.e. the relative amounts of leptons and protons, of extragalactic jets which exhibit X-ray bright knots in their kpc scale jets. The method relies on measuring, or setting upper limits on, the component of the Cosmic Microwave Background (CMB) radiation that is bulk-Comptonized by cold electrons in the relativistically flowing jet. These measurements, along with modeling of the broadband knot emission that constrain the bulk Lorentz factor of the jets, can yield estimates of the jet power carried by protons and leptons. We provide an explicit calculation of the spectrum of the bulk-Comptonized (BC) CMB component and apply these results to PKS 0637--752 and 3C 273, two superluminal quasars with Chandra-detected large scale jets. What makes these sources particularly suited for such a procedure is the absence of significant non-thermal jet emission in the `bridge', the region between the core and the first bright jet knot, which guarantees that most of the electrons are cold there, leaving the BC scattered CMB radiation as the only significant source of photons in this region. At lambda=3.6-8.0 microns the most likely band to observe the BC scattered CMB emission, the Spitzer angular resolution (~ 1''-3) is considerably smaller than the `bridges' of these jets (~10''), making it possible to both measure and resolve this emission.

Reionization history from coupled cosmic microwave background/21-cm line data

We study cosmic microwave background (CMB) secondary anisotropies produced by inhomogeneous reionization by means of cosmological simulations coupled with the radiative transfer code CRASH. The reionization history is consistent with the Wilkinson Microwave Anisotropy Probe Thomson optical depth determination. We find that the signal arising from this process dominates over the primary CMB component for l? 4000 and reaches a maximum amplitude of l(l + 1)C l /2π ≃ 1.6 x 10 -13 on arcmin scales (i.e. / as large as several thousands). We then cross-correlate secondary CMB anisotropy maps with neutral hydrogen 21-cm line emission fluctuations obtained from the same simulations. The two signals are highly anticorrelated on angular scales corresponding to the typical size of H II regions (including overlapping) at the 21-cm map redshift. We show how the CMB/21-cm cross-correlation can be used: (i) to study the nature of the reionization sources; (ii) to reconstruct the cosmic reionization history; (iii) to infer the mean cosmic ionization level at any redshift. We discuss the feasibility of the proposed experiment with forthcoming facilities.

Foreground separation using a flexible maximum-entropy algorithm: an application to COBE data

A flexible maximum-entropy component separation algorithm is presented that accommodates anisotropic noise, incomplete sky-coverage and uncertainties in the spectral parameters of foregrounds. The capabilities of the method are determined by first applying it to simulated spherical microwave data sets emulating the COBE-DMR, COBE-DIRBE and Haslam surveys. Using these simulations we find that is very difficult to determine unambiguously the spectral parameters of the galactic components for this data set due to their high level of noise. Nevertheless, we show that is possible to find a robust cosmic microwave background (CMB) reconstruction, especially at high galactic latitude. The method is then applied to these real data sets to obtain reconstructions of the CMB component and galactic foreground emission over the whole sky. The best reconstructions are found for values of the spectral parameters: T d = 19 K, α d = 2, β ff = -0.19 and β syn = -0.8. The CMB map has been recovered with an estimated statistical error of ∼22 μK on an angular scale of 7° outside the galactic cut, whereas the low galactic latitude region presents contamination from the foreground emissions.

First‐Year Wilkinson Microwave Anisotropy Probe ( WMAP ) Observations: Temperature‐Polarization Correlation

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies of 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 σ. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systematic errors. The correlations are present in all WMAP frequency bands with similar amplitude from 23 to 94 GHz and are consistent with a superposition of a cosmic microwave background (CMB) signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales (θ 20 agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. We detect excess power on large angular scales (θ > 10°) compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift 11 < zr < 30 at 95% confidence, depending on the ionization history. A model-independent fit to reionization optical depth yields results consistent with the best-fit Λ-dominated cold dark matter model, with best-fit value τ = 0.17 ± 0.04 at 68% confidence, including systematic and foreground uncertainties. This value is larger than expected given the detection of a Gunn-Peterson trough in the absorption spectra of distant quasars and implies that the universe has a complex ionization history: WMAP has detected the signal from an early epoch of reionization.