Related papers: Deep Needlet: A CNN based full sky component separ…

Observations of the Cosmic Microwave Background (CMB) radiation have made significant contributions to our understanding of cosmology. While temperature observations of the CMB have greatly advanced our knowledge, the next frontier lies in…

We evaluate the ability of future cosmic microwave background (CMB) experiments to measure the power spectrum of large scale structure using quadratic estimators of the weak lensing deflection field. We calculate the sensitivity of upcoming…

The measurement and characterization of the lensing of the cosmic microwave background (CMB) is key goal of the current and next generation of CMB experiments. We perform a case study of a three-channel balloon-borne CMB experiment…

We propose Path-CNN, a method for the segmentation of centerlines of tubular structures by embedding convolutional neural networks (CNNs) into the progressive minimal path method. Minimal path methods are widely used for topology-aware…

The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly…

We use the full-mission $\textit{Planck}$ PR4 data to construct maps of the thermal Sunyaev$--$Zel'dovich effect (Compton-$y$ parameter) in our Universe. To do so, we implement a custom needlet internal linear combination (NILC) pipeline in…

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian…

Convolutional Neural Network (CNN) have been widely used in image classification. Over the years, they have also benefited from various enhancements and they are now considered as state of the art techniques for image like data. However,…

In computer vision, convolutional networks (CNNs) often adopts pooling to enlarge receptive field which has the advantage of low computational complexity. However, pooling can cause information loss and thus is detrimental to further…

We introduce NeedATool (Needlet Analysis Tool), a software for data analysis based on needlets, a wavelet rendition which is powerful for the analysis of fields defined on a sphere. Needlets have been applied successfully to the treatment…

Model based iterative reconstruction (MBIR) algorithms for low-dose X-ray CT are computationally expensive. To address this problem, we recently proposed a deep convolutional neural network (CNN) for low-dose X-ray CT and won the second…

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…

Molecular communication (MC) is a promising paradigm for applications where traditional electromagnetic communications are impractical. However, decoding chemical signals, especially in multi-transmitter systems, remains a key challenge due…

This paper provides full sky maps of foreground emission in all WMAP channels, with very low residual contamination from the Cosmic Microwave Background (CMB) anisotropies and controlled level of instrumental noise. Foreground maps are…

We propose a convolutional neural network (CNN) architecture for image classification based on subband decomposition of the image using wavelets. The proposed architecture decomposes the input image spectra into multiple critically sampled…

We develop a new method to reconstruct the power spectrum of primordial curvature perturbations, $P(k)$, by using both the temperature and polarization spectra of the cosmic microwave background (CMB). We test this method using several mock…

We present a novel application of partial convolutional neural networks (PCNN) that can inpaint masked images of the cosmic microwave background. The network can reconstruct both the maps and the power spectra to a few percent for circular…

We present an application of the fast Independent Component Analysis (FastICA) to the WMAP 3yr data with the goal of extracting the CMB signal. We evaluate the confidence of our results by means of Monte Carlo simulations including CMB,…

The cosmic microwave background (CMB) stands as a pivotal source for studying weak gravitational lensing. While the lensed CMB aids in constraining cosmological parameters, it simultaneously smooths the original CMB's features. The angular…

Line intensity maps (LIMs) are in principle sensitive to a large amount of information about faint, distant galaxies which are invisible to conventional surveys. However, actually extracting that information from a confused,…