Related papers: Neural Networks for cosmological model selection 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…
We propose a novel approach using neural networks (NNs) to differentiate between cosmological models, and implemented LIME as an interpretability approach to identify the key features influencing our model's decisions. We show the potential…
Measurements of the cosmic microwave background (CMB) radiation provide a unique opportunity for a direct study of the primordial cosmic plasma at redshift z ~1000. The angular power spectra of temperature and polarisation fluctuations are…
Forthcoming cosmic microwave background experiments (CMB) will provide precise new tests of structure-formation theories. The geometry of the Universe may be determined robustly, and the classical cosmological parameters, such as the…
We present an updated data-analysis comparison of the most recent observations of the Cosmic Microwave Background temperature anisotropies and polarization angular power spectra released by four different experiments: the Planck satellite…
Cosmic microwave background (CMB) anisotropy is our richest source of cosmological information; the standard cosmological model was largely established thanks to study of the temperature anisotropies. By the end of the decade, the Planck…
Observations of the polarization of the cosmic microwave backround (CMB) have the potential to place much tighter constraints on cosmological parameters than observations of the fluctuations in temperature alone. We discuss using CMB…
We examine the degree to which observations of large-scale cosmic microwave background (CMB) polarization can shed light on the puzzling large-scale power modulation in maps of CMB anisotropy. We consider a phenomenological model in which…
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…
We propose a machine learning approach to the blind detection of extragalactic point sources on maps of the temperature anisotropies of the cosmic microwave background. Using realistic simulations of the microwave sky as seen by Planck, we…
Since the temperature fluctuations in cosmic microwave background (CMB) on large-angular scales probe length scales that were super-horizon sized at photon decoupling and hence insensitive to microphysical processes, the low-multipole CMB…
Planck's Cosmic Microwave Background temperature and polarization observations are the premier dataset for constraining cosmological models. Cosmic variance limited temperature at large and intermediate scales today dominates the…
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…
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…
Much recent work on the cosmic microwave background (CMB) has focussed on the angular power spectrum of temperature anisotropies and particularly on the recovery of cosmological parameters from acoustic peaks in the power spectrum. However,…
The anisotropies of the cosmic microwave background are a gold mine for cosmology and fundamental physics. ESA's Planck satellite should soon extract all information from the temperature vein but will be limited concerning the measurement…
One of the main obstacles in extracting the Cosmic Microwave Background (CMB) signal from observations in the mm-submm range is the foreground contamination by emission from galactic components: mainly synchrotron, free-free and thermal…
The increasing precision of cosmological datasets is opening up new opportunities to test predictions from cosmic inflation. Here we study the impact of high precision constraints on the primordial power spectrum and show how a new…
We use a high-accuracy computational code to investigate the precision with which cosmological parameters could be reconstructed by future cosmic microwave background (CMB) experiments, in particular the two satellite missions MAP and…
In cosmology, the analysis of observational evidence is very important to test theoretical models of the Universe. Artificial neural networks are powerful and versatile computational tools for data modelling and are recently being…