Related papers: A self-contained guide to the CMB Gibbs sampler
The Microwave Anisotropy Probe and Planck missions will provide low noise maps of the temperature of the cosmic microwave background (CMB). These maps will allow measurement of the power spectrum of the CMB with measurement noise below…
The detection of point-sources in microwave maps is a critical step in the analysis of the Cosmic Microwave Background (CMB) data. If not properly removed, these sources have adverse effects on the estimation of the power-spectrum and/or…
Cosmic voids gravitationally lens the cosmic microwave background (CMB) radiation, resulting in a distinct imprint on degree scales. We use the simulated CMB lensing convergence map from the MICE N-body simulation to calibrate our detection…
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…
Gibbs state preparation is an important subroutine in quantum computing. In this work we use the detectability lemma to improve Gibbs state preparation. Specifically, we design new Gibbs state preparation methods that do not rely on…
We present the first halo model based description of the Cosmic Infrared Background (CIB) non-Gaussianity (NG) that is fully parametric. To this end, we introduce, for the first time, a diagrammatic method to compute high order polyspectra…
State space models (SSMs) are widely used to describe dynamic systems. However, when the likelihood of the observations is intractable, parameter inference for SSMs cannot be easily carried out using standard Markov chain Monte Carlo or…
Finite mixture models are frequently used to uncover latent structures in high-dimensional datasets (e.g.\ identifying clusters of patients in electronic health records). The inference of such structures can be performed in a Bayesian…
Non-Gaussian distributions of cosmic microwave background (CMB) anisotropies have been proposed to reconcile the discrepancies between different experiments at half-degree scales (Coulson et al. 1994). Each experiment probes a different…
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…
We explore the use of the cosmic infrared background as a tracer of the LSS for cross-correlating with the CMB and exploit the ISW. We use the improved linear CIB model of Maniyar et al (2018) and derive the theoretical CIBxISW…
By actively distorting the Cosmic Microwave Background (CMB) over our past light cone, cosmic strings are unavoidable sources of non-Gaussianity. Developing optimal estimators able to disambiguate a string signal from the primordial type of…
In this paper we present a new method to estimate a foreground cleaned Cosmic Microwave Background (CMB) map at a resolution of $1^\circ$ by minimizing the non-Gaussian properties of the cleaned map which arise dominantly due to diffuse…
In this follow-up work to the High Energy Physics Community Summer Study 2013 (HEP CSS 2013, a.k.a. Snowmass), we explore the scientific capabilities of a future Stage-IV Cosmic Microwave Background polarization experiment (CMB-S4) under…
We present a novel method to significantly speed up cosmological parameter sampling. The method relies on constructing an interpolation of the CMB-log-likelihood based on sparse grids, which is used as a shortcut for the…
We analyze the possibility of delensing CMB polarization maps using foreground weak lensing (WL) information. We build an estimator of the CMB lensing potential out of optimally combined projected potential estimators to different source…
Galaxies are often used as tracers of the large scale structure (LSS) to measure the Integrated Sachs-Wolfe effect (ISW) by cross-correlating the galaxy survey maps with the Cosmic Microwave Background (CMB) map. We use the Cosmic Infrared…
We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are 1) conditional…
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…
One of the most powerful tools to probe the existence of cosmic defects in the early universe is through the Cosmic Microwave Background (CMB) radiation. It is well known that computations with causal sources are more involved than the…