相关论文: Predicting the Neutral Hydrogen Content of Galaxie…

We use machine learning to classify galaxies according to their HI content, based on both their optical photometry and environmental properties. The data used for our analyses are the outputs in the range $z = 0-1$ from MUFASA cosmological…

We propose to employ emission line luminosities obtained via optical spectroscopy to estimate the content of neutral hydrogen (HI) in galaxies. We use the optical spectroscopy data from the Mapping of Nearby Galaxies at APO (MaNGA) survey…

We introduce a new photometric estimator of the HI mass fraction (M_HI/M_*) in local galaxies, which is a linear combination of four parameters: stellar mass, stellar surface mass density, NUV-r colour, and g-i colour gradient. It is…

We develop a machine learning (ML) framework to populate large dark matter-only simulations with baryonic galaxies. Our ML framework takes input halo properties including halo mass, environment, spin, and recent growth history, and outputs…

Modelling the distribution of neutral hydrogen (HI) in dark matter halos is important for studying galaxy evolution in the cosmological context. We use a novel approach to infer the HI-dark matter connection at the massive end ($m_{\rm HI}…

A galaxy's morphological features encode details about its gas content, star formation history, and feedback processes, which play important roles in regulating its growth and evolution. We use deep convolutional neural networks (CNNs) to…

We propose an innovative method for measuring the neutral hydrogen (HI) content of an optically-selected spectroscopic sample of galaxies through cross-correlation with HI intensity mapping measurements. We show that the HI-galaxy…

We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…

Aims. We explore machine learning techniques to forecast star formation rate, stellar mass, and metallicity across galaxies with redshifts ranging from 0.01 to 0.3. Methods. Leveraging CatBoost and deep learning architectures, we utilize…

We examine the global HI properties of galaxies in quarter-billion particle cosmological simulations using Gadget-2, focusing on how galactic outflows impact HI content. We consider four outflow models, including a new one (ezw) motivated…

We present new multi-wavelength scaling relations between the neutral hydrogen content (HI) and the stellar properties of nearby galaxies selected from the HI Parkes All-Sky Survey (HIPASS). We use these new scaling relations to investigate…

Upcoming 21cm surveys will map the spatial distribution of cosmic neutral hydrogen (HI) over unprecedented volumes. Mock catalogues are needed to fully exploit the potential of these surveys. Standard techniques employed to create these…

We examine galaxy star formation rates (SFRs), metallicities, and gas contents predicted by the MUFASA cosmological hydrodynamic simulations, which employ meshless hydrodynamics and novel feedback prescriptions that yield a good match to…

Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of objects is also taken under consideration, it becomes very…

One of the key science drivers for the development of the SKA is to observe the neutral hydrogen, HI, in galaxies as a means to probe galaxy evolution across a range of environments over cosmic time. Over the past decade, much progress has…

Photometric redshift estimation is a key requirement for modern large-area surveys, where spectroscopic measurements are observationally prohibitive. Seyfert II galaxies provide a particularly challenging test case due to the combined…

Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This…

We describe a simulation for the distribution of galaxies focusing on the atomic Hydrogen content. We aim to make predictions for surveys of galaxies using the redshifted 21 cm line emission. We take the expected distribution of HI masses,…

We extend the results of previous analyses towards constraining the abundance and clustering of post-reionization ($z \sim 0-5$) neutral hydrogen (HI) systems using a halo model framework. We work with a comprehensive HI dataset including…

(abridged) Mass loss is a key parameter in the evolution of massive stars, with discrepancies between theory and observations and with unknown importance of the episodic mass loss. To address this we need increased numbers of classified…