The separation of emissions from different astrophysical processes is an important step towards the understanding of observational data. This topic of component separation is of particular importance in the observation of the relic Cosmic Microwave Background Radiation, as performed by the WMAP satellite and the more recent Planck mission, launched May 14th, 2009 from Kourou and currently taking data. When performing any sort of component separation, some assumptions about the components must be used. One assumption that many techniques typically use is knowledge of the frequency scaling of one or more components. This assumption may be broken in the presence of calibration errors. Here we compare, in the context of imperfect calibration, the recovery of a clean map of emission of the Cosmic Microwave Background from observational data with two methods: FastICA (which makes no assumption of the frequency scaling of the components), and an `Internal Linear Combination' (ILC), which explicitly extracts a component with a given frequency scaling. We find that even in the presence of small calibration errors with a Planck-style mission, the ILC method can lead to inaccurate CMB reconstruction in the high signal-to-noise regime, because of partial cancellation of the CMB emission in the recovered map. While there is no indication that the failure of the ILC will translate to other foreground cleaning or component separation techniques, we propose that all methods which assume knowledge of the frequency scaling of one or more components be careful to estimate the effects of calibration errors.
We propose a new internal linear combination (ILC) method in the pixel space, applicable on large angular scales of the sky, to estimate a foreground minimized Cosmic Microwave Background (CMB) temperature anisotropy map by incorporating prior knowledge about the theoretical CMB covariance matrix. Usual ILC method in pixel space, on the contrary, does not use any information about the underlying CMB covariance matrix. The new approach complements the usual pixel space ILC technique specifically at low multipole region, using global information available from theoretical CMB covariance matrix a…
The Cosmic Microwave Background (CMB) radiation B mode polarization signal contains the unique signature of primordial metric perturbations produced during the inflation. The separation of the weak CMB B-mode signal from strong foreground contamination in observed maps is a complex task, and proposed new generation low noise satellite missions compete with the weak signal level of this gravitational background. In this article, for the first time, we employ a foreground model-independent internal linear combination (ILC) method to reconstruct the CMB B mode signal using simulated observations …
We report an improved technique for diffuse foreground minimization from Cosmic Microwave Background (CMB) maps using a new multi-phase iterative internal-linear-combination (ILC) approach in harmonic space. The new procedure consists of two phases. In phase 1, a diffuse foreground cleaned map is obtained by performing a usual ILC operation in the harmonic space in a single iteration over the desired portion of the sky. In phase 2, we obtain the final foreground cleaned map using an iterative ILC approach also in the harmonic space, however, now, during each iteration of foreground minimizatio…
In this work, we formalize a new technique to investigate joint posterior density of Cosmic Microwave Background (CMB) signal and its theoretical angular power spectrum given the observed data, using the global internal-linear-combination (ILC) method first proposed by Sudevan & Saha (2017). We implement the method on low resolution CMB maps observed by WMAP and Planck satellite missions, using Gibbs sampling, assuming that the detector noise is negligible on large angular scales of the sky. The main products of our analysis are best fit CMB cleaned map and its theoretical angular power spectr…
In this article we present a formalism to incorporate the partial-sky maps to the Gibbs ILC algorithm to estimate the joint posterior density of the Cosmic Microwave Background (CMB) signal and the theoretical CMB angular power spectrum given the observed CMB maps. In order to generate the partial-sky maps we mask all the observed CMB maps provided by WMAP and Planck satellite mission using a Gaussian smoothed mask formed on the basis of thermal dust emissions in Planck 353 GHz map. The central galactic region from all the input maps is removed after the application of the smoothed mask. While…
Residual error in calibration coefficients corresponding to observed CMB maps is an important issue while estimating a pure CMB signal. A component separation method, if these errors in the input foreground contaminated CMB maps are not properly taken into account, may lead to bias in the cleaned CMB map and estimated CMB angular power spectrum. But the inability to exactly determine the calibration coefficients corresponding to each observed CMB map from any CMB experiment makes it very difficult to incorporate their exact and actual values in a component separation analysis. Hence the effect…
Internal Linear Combination (ILC) methods are some of the most widely used multi-frequency cleaning techniques employed in CMB data analysis. These methods reduce foregrounds by minimizing the total variance in the coadded map (subject to a signal-preservation constraint), although often significant foreground residuals or biases remain. A modification to the ILC method is the constrained ILC (cILC), which explicitly nulls certain foreground components; however, this foreground nulling often comes at a high price for ground-based CMB datasets, with the map noise increasing significantly on sma…
Galactic foregrounds are the main obstacle to observations of the cosmic microwave background (CMB) $B$-mode polarization. In addition to obscuring the inflationary $B$-mode signal by several orders of magnitude, Galactic foregrounds have non-trivial spectral signatures that are partially unknown and distorted by averaging effects along the line-of-sight, within the pixel/beam window, and by various analysis choices (e.g., spherical harmonic transforms and filters). Statistical moment expansion methods provide a powerful tool for modeling the effective Galactic foreground emission resulting fr…
CMB component-separated power spectrum estimation by Spectral Internal Linear Combination (SpILC)
University of Cambridge（剑桥大学）；Kavli Institute for Cosmology Cambridge（卡弗里宇宙学剑桥研究所）；Center for Computational Astrophysics, Flatiron Institute（纽约市立大学富尔顿计算天体物理中心）；Astrophysics Group, Cavendish Laboratory（卡文迪许实验室天体物理学组）
The method of weighted addition of multi-frequency maps, more commonly referred to as {\it Internal Linear Combination} (ILC), has been extensively employed in the measurement of cosmic microwave background (CMB) anisotropies and its secondaries along with similar application in 21cm data analysis. Here we argue and demonstrate that ILC methods can also be applied to data from absolutely-calibrated CMB experiments to extract average-sky signals in addition to the conventional CMB anisotropies. The performance of the simple ILC method is, however, limited, but can be significantly improved by a…
In the recent years, the internal-linear-combination (ILC) method was investigated extensively in the context of reconstruction of Cosmic Microwave Background (CMB) temperature anisotropy signal using observations obtained by WMAP and Planck satellite missions. In this article, we, for the first time, apply the ILC method to reconstruct the large scale CMB E mode polarization signal, which serves as the unique probe of ionization history of the Universe, using simulated observations of 15 frequency CMB polarization maps of future generation COrE satellite mission. We find that usual ILC cleane…
Genetic Algorithm (GA) -- motivated by natural evolution -- is a robust method to estimate the global optimal solutions of problems involving multiple objective functions. In this article, for the first time, we apply GA to reconstruct the CMB temperature anisotropy map over large angular scales of the sky using (internal) linear combination (ILC) of the final-year WMAP and Planck satellite observations. To avoid getting trapped into a local minimum, we implement the GA with generous diversity in the populations by selecting pairs with diverse fitness coefficients and by introducing a small bu…
The Internal Linear Combination (ILC) is widely used to extract the cosmic microwave background (CMB) signal from multi-frequency observation maps, especially for Satellite experiments with quasi-full sky coverage. We extend ILC method to CMB polarization map analysis with a small sky patch which is especially typical for ground-based experiments, by combing ILC with a template cleaning method which can give pure $B$ map free from $EB$ leakage caused by partial sky coverage. The feature of our methods is that we do the ILC analysis on pseudo-scalar $B$ maps, and the advantage is that it totall…
Extragalactic foregrounds in Cosmic Microwave Background (CMB) temperature maps lead to significant biases in CMB lensing reconstruction if not properly accounted for. Combinations of multi-frequency data have been used to minimize the overall map variance (internal linear combination, or ILC), or specifically null a given foreground, but these are not tailored to CMB lensing. In this paper, we derive an optimal multi-frequency combination to jointly minimize CMB lensing noise and bias. We focus on the standard lensing quadratic estimator, as well as the "shear-only" and source-hardened estima…
In this paper we estimate diffuse foreground minimized Cosmic Microwave Background (CMB) Stokes Q and U polarization maps based upon the fundamental concept of Gaussian nature of CMB and strong non-Gaussian nature of astrophysical polarized foregrounds using WMAP nine year published polarization maps. We excise regions of the sky that define position of the known point sources, regions that are strongly contaminated by either the detector noise or by the diffuse foregrounds or both, and then perform foreground minimizations over the surviving sky regions that constitute approximately $50\%$ of…
Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the compu…
Robust CMB B-mode analysis with Needlet-ILC and simulation-based inference
Max-Planck-Institut für Astrophysik（马克斯·普朗克天体物理学研究所）；Columbia University（哥伦比亚大学）；Flatiron Institute（平顿研究所）；Princeton University（普林斯顿大学）；University of California Berkeley（加州大学伯克利分校）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；University of Milano-Bicocca（米兰比可卡大学）
Single Frequency CMB Foreground Removal with Inter-scale Machine Learning
Harvard University（哈佛大学）；University of Cambridge（剑桥大学）；Flatiron Institute, New York, NY, USA（纽约市平顿研究所）；Pontificia Universidad Católica de Chile（智利天主教庞蒂菲亚大学）
We present a methodology to recover cosmic microwave background (CMB) polarization in which the quantity $P = Q+ iU$ is linearly combined at different frequencies using complex coefficients. This is the most general linear combination of the $Q$ and $U$ Stokes parameters which preserves the physical coherence of the residual contribution on the CMB estimation. The approach is applied to the internal linear combination (ILC) and the internal template fitting (ITF) methodologies. The variance of $P$ of the resulting map is minimized to compute the coefficients of the linear combination. One of t…
We present a new blind formulation of the Cosmic Microwave Background (CMB) inference problem. The approach relies on a phenomenological model of the multi-frequency microwave sky without the need for physical models of the individual components. For all-sky and high resolution data, it unifies parts of the analysis that have previously been treated separately, such as component separation and power spectrum inference. We describe an efficient sampling scheme that fully explores the component separation uncertainties on the inferred CMB products such as maps and/or power spectra. External info…
We present a new approach to component separation in multifrequency CMB experiments by formulating the problem as that of partitioning the sky into pixel clusters such that within each pixel cluster the foregrounds have similar spectrum, using only the information available in the data. Only spectral information is used for partitioning, allowing spatially far away pixels to belong to the same cluster if their foreground properties are close. We then apply a modified internal linear combination method to each pixel cluster. Since the foregrounds have similar spectrum within each cluster, the n…
A recent article (Liu et al. 2014) looks for evidence in the WMAP internal linear combination map (ILC) of unmodeled emission from the galactic radio loop known as Loop I. The statistically strongest result comes from a cluster analysis that tests whether the "hot spots" within a $20^\circ$ annulus at Loop I are preferentially located near the center line of the annulus. From this cluster analysis the authors report a $p$-value of 0.018% when considering the four highest bins (75-87 $μ$K). I show that the reported statistical significance has been overestimated. First, the analysis does not co…
The Internal Linear Combination (ILC) method has been extensively used to extract the cosmic microwave background (CMB) anisotropy map from foreground contaminated multi-frequency maps. However, the performance of simple ILC is limited and can be significantly improved by heavily constraint equations, dubbed cILC. The standard ILC and cILC works on the spin-0 field. Recently, a generalized version of ILC is developed to estimate polarization maps in which the quantity $Q \pm iU$ is combined at multiple frequencies using complex coefficients called Polarization ILC (PILC). A statistical moment …
Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this met…
The search for primordial $B$-mode polarization of the CMB is limited by the sample variance of $B$-modes produced at later times by gravitational lensing. Constraints can be improved by `delensing': using some proxy of the matter distribution to partially remove the lensing-induced $B$-modes. Current and soon-upcoming experiments will infer a matter map -- at least in part -- from the temperature anisotropies of the CMB. These reconstructions are contaminated by extragalactic foregrounds: radio-emitting galaxies, the cosmic infrared background, or the Sunyaev--Zel'dovich effects. Using the We…
BROOM: a python package for model-independent analysis of microwave astronomical data
International School for Advanced Studies (SISSA)（国际高等研究院）；INFN Sezione di Trieste（意大利国家核物理研究所的里雅斯特分部）；IFPU（伊尔利亚自由大学）；Università di Trento, Dipartimento di Fisica（特伦托大学物理系）
The Topology and Size of the Universe from CMB Temperature and Polarization Data
我们分析了七年和九年WMAP温度图的三个有限平坦拓扑M_0=T^3，M_1=T^2 x R^1，和M_2=S^1 x R^2的签名。我们使用蒙特卡罗模拟与Feldman-Schmidins方法，以获得所考虑的拓扑结构的大小的置信区间。我们分析了V，W和Q频带以及ILC图，结果没有发现显着差异。在95.5%的置信水平下，拓扑结构的大小下限为M_0的1.5L_0，M_1的1.4L_0，M_2的1.1L_0，其中L_0是最后一个散射表面的半径。我们的结果与最近公布的普朗克温度数据的结果非常吻合。我们表明，似然函数的大小不是高斯的，因此模拟是很重要的，以获得准确的界限的大小。然后，我们介绍的形式主义，包括偏振数据的分析。我们从WMAP极化图中发现的改进很小，因为仪器噪声水平很高，但是我们对普朗克图的预测显示出对L的下界有更好的改进。对于M_0拓扑，我们期望在95.5%的置信水平下，L的下限从1.7L_0提高到1.9L_0。使用偏振和温度数据是很重要的，因为它测试的假设，在TT光谱中的偏差在小l起源于原始扰动谱。
Harvard University（哈佛大学）；Stanford University（斯坦福大学）；University of California San Diego（加州大学圣迭戈分校）
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 $N_{\rm side}=256$ simulated sky maps that include dust, synchrotron, free-free and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25\%$ over GMCA in both the regions included and ex…
