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Galaxy clusters induce a distinct dipole pattern in the cosmic microwave background (CMB) through the effect of gravitational lensing. Extracting this lensing signal will enable us to constrain cluster masses, even for high redshift…
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…
We first compare the CMB lensing model of Seljak (1996) with the empirical model of Lieu & Mittaz (2005) to determine if the latter approach implies a larger effect on the CMB power-spectrum. We find that the empirical model gives…
The patchiness in the reionization process alters the statistics of Cosmic Microwave Background (CMB), with the kinematic Sunyaev-Zeldovich (kSZ) effect in the CMB temperature power spectrum being a notable consequence. In this work, we aim…
The intra-cluster light (ICL) in observations is usually identified through the surface brightness limit method. In this paper, for the first time we produce the mock images of galaxy groups and clusters using a cosmological hydro-…
We use a new approach based on self-supervised deep learning networks originally applied to transparency separation in order to simultaneously extract the components of the extragalactic submillimeter sky, namely the cosmic microwave…
The detection of Cosmic Microwave Background primordial $B$-mode polarization would constitute a ``smoking gun" signal of primordial gravitational waves. However, this measurement requires accurate removal of polarized Galactic foregrounds…
The WMAP 7-year temperature maps have been re-analized to extract a CMB map and CMB power spectrum with reduced contamination by astrophysical foregrounds and noise. The method used is based on linear combinations of WMAP data and…
Accurate uncertainty quantification is crucial for the safe deployment of machine learning models, and prior research has demonstrated improvements in the calibration of modern language models (LMs). We study in-context learning (ICL), a…
Most analysis of Cosmic Microwave Background spherical harmonic coefficients a_lm has focused on estimating the power spectrum C_l=<|a_lm|^2> rather than the coefficients themselves. We present a minimum-variance method for measuring a_lm…
Ever since Cosmic Microwave Background (CMB) signal is being measured by various satellites based observations with increasing experimental accuracies there has been a parallel increase in the demand for a CMB reconstruction technique which…
We develop a new method for reconstructing cluster mass profiles and large-scale structure from the cosmic microwave background (CMB). By analyzing the likelihood of CMB lensing, we analytically prove that standard quadratic estimators for…
Analysis and denoising of Cosmic Microwave Background (CMB) maps are performed using wavelet multiresolution techniques. The method is tested on $12^{\circ}.8\times 12^{\circ}.8$ maps with resolution resembling the experimental one expected…
We present circular and linear cross-correlation tests and the "friend-of-friend" analysis for phases of the Internal Linear Combination Map (ILC) and the WMAP foregrounds for all K--W frequency bands at the range of multipoles…
Composed Image Retrieval (CIR) is a complex task that aims to retrieve images based on a multimodal query. Typical training data consists of triplets containing a reference image, a textual description of desired modifications, and the…
We explore the possible application of linear covariance-based (LCB) filtering to line-intensity mapping (LIM) signal reconstructions. Originally introduced for reconstruction of the integrated Sachs-Wolfe effect in the cosmic microwave…
This paper introduces a technique called NKL, which cleans both polarized and unpolarized foregrounds from HI intensity maps by applying a Karhunen-Lo\`eve transform on the needlet coefficients. In NKL, one takes advantage of correlations…
Lensing reconstruction maps from the cosmic microwave background (CMB) provide direct observations of the matter distribution of the universe without the use of a biased tracer. Such maps, however, constitute projected observables along the…
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…
We seek to remove foreground contaminants from 21cm intensity mapping observations. We demonstrate that a deep convolutional neural network (CNN) with a UNet architecture and three-dimensional convolutions, trained on simulated…