Related papers: Foreground removal from CMB temperature maps using…
One of the main obstacles for extracting the cosmic microwave background (CMB) signal from observations in the mm/sub-mm range is the foreground contamination by emission from Galactic component: mainly synchrotron, free-free, and thermal…
One of the fundamental problems in extracting the cosmic microwave background signal (CMB) from millimeter/submillimeter observations is the pollution by emission from the Milky Way: synchrotron, free-free, and thermal dust emission. To…
In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a…
One of the main obstacles for extracting the Cosmic Microwave Background (CMB) from mm/submm observations is the pollution from the main Galactic components: synchrotron, free-free and thermal dust emission. The feasibility of using simple…
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…
Maps of cosmic microwave background (CMB) are extracted from multi-frequency observations using a variety of cleaning procedures. However, in regions of strong microwave emission, particularly in the galactic plane from our own galaxy Milky…
Accurate estimation of the Cosmic Microwave Background (CMB) angular power spectrum is enticing due to the prospect for precision cosmology it presents. Galactic foreground emissions, however, contaminate the CMB signal and need to be…
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…
Studies of cosmic microwave background (CMB) are often limited by foreground contamination. Foreground cleaning is performed either in harmonic or pixel space after data cuts have excluded sky areas of strong contamination. We present a…
We present a framework for cosmological model selection using Neural Networks (NNs) trained directly on simulated Cosmic Microwave Background (CMB) temperature and polarisation maps. By operating at the map level rather than on compressed…
The cosmic microwave background (CMB) temperature bispectrum is currently the most precise tool for constraining primordial non-Gaussianity (NG). The Planck temperature data tightly constrain the amplitude of local-type NG: $f_{\rm NL}^{\rm…
In Luparello et al. 2023, a new and hitherto unknown CMB foreground was detected. A systematic decrease in Cosmic Microwave Background (CMB) temperatures around nearby large spiral galaxies points to an unknown interaction with CMB photons…
Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for…
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…
One of the key steps in Cosmic Microwave Background (CMB) data analysis is component separation to recover the CMB signal from multi-frequency observations contaminated by foreground emissions. Needlet Internal Linear Combination (NILC) is…
An improved method for subtracting contaminants from Cosmic Microwave Background (CMB) sky maps is presented, and used to estimate how well future experiments will be able to recover the primordial CMB fluctuations. We find that the naive…
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…
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…
We present a new, semi-analytic framework for estimating the level of residuals present in CMB maps derived from multi-frequency Cosmic Microwave Background (CMB) data and forecasting their impact on cosmological parameters. The data are…
Extracting cosmological information from microwave sky observations requires accurate estimation of the underlying Cosmic Microwave Background (CMB) by removing foreground contamination, instrumental noise, and the effects of beam…