Related papers: Application of Machine Learning to 21 cm Cosmology
[Abridged] The spatially averaged global spectrum of the redshifted 21cm line has generated much experimental interest, for it is potentially a direct probe of the Epoch of Reionization and the Dark Ages. Since the cosmological signal here…
21-cm emission from neutral hydrogen during and before the epoch of cosmic reionisation is gravitationally lensed by material at all lower redshifts. Low-frequency radio observations of this emission can be used to reconstruct the projected…
The redshifted 21-cm radiation from the atomic hydrogen (HI) provides an excellent direct probe to study the evolution of HI in IGM and thus reveal the nature of the first luminous objects, their evolution and role during Cosmic Dawn (CD)…
The 21cm line of neutral hydrogen is a powerful probe of the high-redshift universe (Cosmic Dawn and the Epoch of Reionization), with an unprecedented potential to inform us about key processes of early galaxy formation, the first stars and…
Methane ($CH_4$) is a potent anthropogenic greenhouse gas, contributing 86 times more to global warming than Carbon Dioxide ($CO_2$) over 20 years, and it also acts as an air pollutant. Given its high radiative forcing potential and…
Theoretical computation of cosmological observables is an intensive process, restricting the speed at which cosmological data can be analysed and cosmological models constrained, and therefore limiting research access to those with high…
We present here 21 cm predictions from high dynamic range simulations for a range of reionization histories that have been tested against available Lyman-alpha and CMB data. We assess the observability of the predicted spatial 21 cm…
The potential use of the redshifted 21 cm line from neutral hydrogen for probing the epoch of reionization is motivating the construction of several low-frequency interferometers. There is also much interest in the possibility of…
This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to evaluate and synthesize existing research to identify…
The 21-cm forest signal is a promising probe of the Epoch of Reionization complementary to other 21-cm line observables and Ly$\alpha$ forest signal. Prospects of detecting it have significantly improved in the last decade thanks to the…
The hyperfine structure absorption lines of neutral hydrogen in spectra of high-redshift radio sources, known collectively as the 21-cm forest, have been demonstrated as a sensitive probe to the small-scale structures governed by the dark…
The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand…
Measuring distances of cosmological sources such as galaxies, stars and quasars plays an increasingly critical role in modern cosmology. Obtaining the optical spectrum and consequently calculating the redshift as a distance indicator could…
Modern spacecraft are increasingly relying on machine learning (ML). However, physical equipment in space is subject to various natural hazards, such as radiation, which may inhibit the correct operation of computing devices. Despite plenty…
Low-frequency radio observations of neutral hydrogen during and before the epoch of cosmic reionization will provide hundreds of quasi-independent source planes, each of precisely known redshift, if a resolution of ~ 1 arcminutes or better…
Material scientists are increasingly adopting the use of machine learning (ML) for making potentially important decisions, such as, discovery, development, optimization, synthesis and characterization of materials. However, despite ML's…
Machine Learning (ML) serves as a general-purpose, highly adaptable, and versatile framework for investigating complex systems across domains. However, the resulting computational resource demands, in terms of the number of parameters and…
We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and…
The efficient classification of different types of supernova is one of the most important problems for observational cosmology. However, spectroscopic confirmation of most objects in upcoming photometric surveys, such as the The Rubin…
Spatial variations in the Lyman-$\alpha$ forest opacity at $z<6$ seem to require a late end to cosmic reionization. In this picture, the universe contains neutral hydrogen 'islands' of up to 100 cMpc$/h$ in extent down to redshifts as low…