相关论文: Foreground separation methods for satellite observ…
In our previous study, we introduced a machine-learning technique, namely CMBFSCNN, for the removal of foreground contamination in cosmic microwave background (CMB) polarization data. This method was successfully employed on actual…
This paper proposes a new approach to separate the $\mu$ spectral distortions of the cosmic microwave background from foregrounds with poorly defined spectral shapes. The idea is based on finding the optimal response to the observed signal.…
We present a novel method for Cosmic Microwave Background (CMB) foreground removal based on deep learning techniques. This method employs a Transformer model, referred to as \texttt{TCMB}, which is specifically designed to effectively…
AIMS: The separation of foreground contamination from cosmic microwave background (CMB) observations is one of the most challenging and important problem of digital signal processing in Cosmology. In literature, various techniques have been…
Component separation is the process of extracting one or more emission sources in astrophysical maps. It is therefore crucial to develop models that can accurately clean the cosmic microwave background (CMB) in current and future…
Primordial B-mode detection is one of the main goals of current and future cosmic microwave background (CMB) experiments. However, the weak B-mode signal is overshadowed by several Galactic polarized emissions, such as thermal dust emission…
Upcoming cosmic microwave background (CMB) experiments aim to detect primordial gravitational waves with unprecedented sensitivity. Effective foreground removal is essential to avoid biases in the measurement of the tensor-to-scalar ratio…
We present an analysis of errors on the tensor-to-scalar ratio due to residual diffuse foregrounds. We use simulated observations of a CMB polarization satellite, the Cosmic Origins Explorer, using the specifications of the version proposed…
In these proceedings, we discuss the extraction, in WMAP 5 year data, of a clean CMB map, of foreground emission (dominated by emission of the interstellar medium of our galaxy), and of the tiny signal from Sunyaev Zel'dovich effect in the…
The Maximum Entropy Method (MEM) for the deconvolution of radio interferometry images is mathematically well based and presents a number of advantages over the usual CLEAN deconvolution, such as appreciably higher resolution. The…
Mitigation of the impact of foreground contributions to measurements of Cosmic Microwave Background (CMB) polarization is a crucial step in modern CMB data analysis and is of particular importance for a detection of large-scale CMB $B$…
We investigate the performance of the parametric Maximum Likelihood component separation method in the context of the CMB B-mode signal detection and its characterization by small-scale CMB suborbital experiments. We consider…
We present the application of the Fast Independent Component Analysis ({\ica}) technique for blind component separation to polarized astrophysical emission. We study how the Cosmic Microwave Background (CMB) polarized signal, consisting of…
We reconsider the pixel-based, "template" polarized foreground removal method within the context of a next-generation, low-noise, low-resolution (0.5 degree FWHM) space-borne experiment measuring the cosmological B-mode polarization signal…
We present a formalism for performance forecasting and optimization of future cosmic microwave background (CMB) experiments. We implement it in the context of nearly full sky, multifrequency, B-mode polarization observations, incorporating…
The 'Internal Linear Combination' (ILC) component separation method has been extensively used to extract a single component, the CMB, from the WMAP multifrequency data. We generalise the ILC approach for separating other millimetre…
The polarization of the Cosmic Microwave Background (CMB)is a powerful observational tool at hand for modern cosmology. It allows to break the degeneracy of fundamental cosmological parameters one cannot obtain using only anisotropy data…
We discuss an approach to the component separation of microwave, multi-frequency sky maps as those typically produced from Cosmic Microwave Background (CMB) Anisotropy data sets. The algorithm is based on the two step, parametric,…
The cosmic microwave background (CMB), carrying the inhomogeneous information of the very early universe, is of great significance for understanding the origin and evolution of our universe. However, observational CMB maps contain serious…
Foreground contamination is the fundamental hindrance to the cosmic microwave background (CMB) signals and its separation from it represents a fundamental question in Cosmology. One of the most popular algorithm used to disentangle…