Related papers: A Generative Model of Galactic Dust Emission Using…
Using a high-resolution cosmological hydrodynamic simulation, we present a method to constrain extinction due to intergalactic grey dust based on the observed magnitudes of distant Type IA supernovae. We apply several simple prescriptions…
The galactic anomalous microwave emission detected between 10 and 90 GHz is a major foreground to CMB fluctuations. Well correlated to dust emission at 100 $\mu$m, the anomalous emission is interstellar but its origin is still debated. Some…
This article gives an overview of the constitution, physical conditions and observables of dust in the interstellar medium of nearby galaxies. We first review the macroscopic, spatial distribution of dust in these objects, and its…
The thermal emission of dust is one of the most important tracers of the interstellar medium: multi-wavelength photometry in the far-infrared (FIR) and submillimeter (submm) can be fitted with a model, providing estimates of the dust mass.…
Generative models (GMs) such as Generative Adversary Network (GAN) and Variational Auto-Encoder (VAE) have thrived these years and achieved high quality results in generating new samples. Especially in Computer Vision, GMs have been used in…
We present a Bayesian parametric component separation method for polarised microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarised foreground components. For the latter,…
In this review, we intend to present the current knowledge of the polarized emission from thermal dust in our Galaxy. We show different methods to estimate the spatial distribution statistics of this emission in the lack of any data from…
We present first results of our study of a sample of Galactic LBV, aimed to contribute to a better understanding of the LBV phenomenon, by recovering the mass-loss history of the central object from the analysis of its associated nebula.…
Recent work in synthetic data generation in the time-series domain has focused on the use of Generative Adversarial Networks. We propose a novel architecture for synthetically generating time-series data with the use of Variational…
Dust attenuation varies substantially from galaxy to galaxy and as of yet cannot be reproduced from first principles in theoretical models. In Nagaraj et al. (2022), we developed the first Bayesian population model of dust attenuation as a…
We present the DustFilaments code, a full sky model for the millimeter Galactic emission of thermal dust. Our model, composed of millions of filaments that are imperfectly aligned with the magnetic field, is able to reproduce the main…
WMAP data when combined with ancillary data on free-free, synchrotron and dust allow an improved understanding of the spectrum of emission from each of these components. Here we examine the sky variation at intermediate and high latitudes…
Three-dimensional (3D) maps of the Galactic interstellar matter (ISM) are a potential tool of wide use, however accurate and detailed maps are still lacking. One of the ways to construct the maps is to invert individual distance-limited ISM…
The cycle of metals between the gas and the dust phases in the neutral interstellar medium (ISM) is an integral part of the baryon cycle in galaxies. The resulting variations in the abundance and properties of interstellar dust have…
Gastrointestinal (GI) imaging via Wireless Capsule Endoscopy (WCE) generates a large number of images requiring manual screening. Deep learning-based Clinical Decision Support (CDS) systems can assist screening, yet their performance relies…
Turbulence plays a key role in star formation in molecular clouds, affecting star cluster primordial properties. As modelling present-day objects hinges on our understanding of their initial conditions, better constraints on turbulence can…
We propose a novel deep clustering method that integrates Variational Autoencoders (VAEs) into the Expectation-Maximization (EM) framework. Our approach models the probability distribution of each cluster with a VAE and alternates between…
Using Planck polarization data, we search for and constrain spatial variations of the polarized dust foreground for cosmic microwave background (CMB) observations, specifically in its spectral index, $\beta_d$. Failure to account for such…
Lada et al. (1994) have described a method for studying the distribution of dust in dark clouds using infrared imaging surveys. In particular they show that the method provides some information about the structure of the gas (dust) on…
We present a coupled Variational Auto-Encoder (VAE) method that improves the accuracy and robustness of the probabilistic inferences on represented data. The new method models the dependency between input feature vectors (images) and weighs…