Related papers: A Generative Model of Galactic Dust Emission Using…
Interstellar dust at high Galactic latitudes can influence astronomical foreground subtraction, produce diffuse scattered light, and soften the ultraviolet spectra of quasars. In a sample of 94 sight lines toward quasars at high latitude…
The use of machine learning is becoming ubiquitous in astronomy, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a multi-parameter space is swept through in real time to find…
Interstellar dust appears in a number of roles in the interstellar medium. Historically, the most familiar one is as a source of extinction in the optical. Absorbed optical and ultraviolet light heats the dust, whence infrared (including…
Extragalactic astronomy relies on the accurate estimation of source photometry corrected for Milky Way dust extinction. This has motivated the creation of a number of "Galactic" dust maps. We investigate whether these maps are contaminated…
We explore in this paper the ability to constrain the Galactic magnetic field intensity and spatial distribution with the incoming data from the Planck satellite experiment. We perform realistic simulations of the Planck observations at the…
A one-dimensional method for reconstructing the structure of prestellar and protostellar clouds is presented. The method is based on radiative transfer computations and a comparison of theoretical and observed intensity distributions at…
This work uses a combination of a variational auto-encoder and generative adversarial network to compare different dark energy models in light of observations, e.g., the distance modulus from type Ia supernovae. The network finds an…
In Astrophysics, the identification of candidate Globular Clusters through deep, wide-field, single band HST images, is a typical data analytics problem, where methods based on Machine Learning have revealed a high efficiency and…
We present a non-parametric model for inferring the three-dimensional (3D) distribution of dust density in the Milky Way. Our approach uses the extinction measured towards stars at different locations in the Galaxy at approximately known…
Enabling highly-mobile millimeter wave (mmWave) systems is challenging because of the huge training overhead associated with acquiring the channel knowledge or designing the narrow beams. Current mmWave beam training and channel estimation…
We present a new model of the microwave sky in polarization that can be used to simulate data from CMB polarization experiments. We exploit the most recent results from the Planck satellite to provide an accurate description of the diffuse…
Deep generative models are reported to be useful in broad applications including image generation. Repeated inference between data space and latent space in these models can denoise cluttered images and improve the quality of inferred…
We present a novel framework to self-consistently model the effects of radiation fields, dust physics and molecular chemistry (H$_2$) in the interstellar medium (ISM) of galaxies. The model combines a state-of-the-art radiation…
We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…
The B-modes of polarization at frequencies ranging from 50-1000 GHz are produced by Galactic dust, lensing of primordial E-modes in the cosmic microwave background (CMB) by intervening large scale structure, and possibly by primordial…
Using the Planck far-infrared and Arecibo GALFA 21-cm line surveys, we identified a set of isolated interstellar clouds (approximately degree-sized on the sky and comprising 100 solar masses) and assessed the ratio of gas mass to dust mass.…
Variational Autoencoders (VAEs), as a form of deep generative model, have been widely used in recent years, and shown great great peformance in a number of different domains, including image generation and anomaly detection, etc.. This…
With Planck and Herschel, we now have the spectral coverage and angular resolution required to observe dense and cold molecular clouds. As these clouds are optically thick at short wavelength but optically thin at long wavelength, it is…
Young massive stars play an important role in the evolution of the interstellar medium (ISM) and the self-regulation of star formation in giant molecular clouds (GMCs) by injecting energy, momentum, and radiation (stellar feedback) into…
Learning useful representations of complex data has been the subject of extensive research for many years. With the diffusion of Deep Neural Networks, Variational Autoencoders have gained lots of attention since they provide an explicit…