Related papers: Exploring galactic properties with machine learnin…

We infer stellar metallicity and abundance ratio gradients for a sample of red galaxies in the Sloan Digital Sky Survey (SDSS) Main galaxy sample. Because this sample does not have multiple spectra at various radii in a single galaxy, we…

We study relations between stellar mass, star formation and gas-phase metallicity in a sample of 177,071 unique emission line galaxies from the SDSS-DR7, as well as in a sample of 43,767 star forming galaxies at z=0 from the cosmological…

We present an analysis of the quenching of star formation in galaxies, bulges, and disks throughout the bulk of cosmic history, from $z=2-0$. We utilise observations from the SDSS and MaNGA at low redshifts. We complement these data with…

Determination of the star formation rate can be done using mid-IR photometry or Balmer line luminosity after a proper correction for extinction effects. Both methods show convergent results while those based on UV or on [OII]3727…

We introduce the "Engineering Dwarfs at Galaxy formation's Edge" (EDGE) project to study the cosmological formation and evolution of the smallest galaxies in the Universe. In this first paper, we explore the effects of resolution and…

This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute…

We apply Random Forest and XGBoost machine learning algorithms to determine which galaxy properties most effectively predict star formation and quenching in simulated galaxies. Using spatially-resolved data from approximately 63,000 annular…

Modern astronomy relies on massive databases collected by robotic telescopes and digital sky surveys, acquiring data in a much faster pace than what manual analysis can support. Among other data, these sky surveys collect information about…

We present a metric to quantify systematic labeling bias in galaxy morphology data sets stemming from the quality of the labeled data. This labeling bias is independent from labeling errors and requires knowledge about the intrinsic…

Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…

Stellar masses play a crucial role in the exploration of galaxy properties and the evolution of the galaxy population. In this paper, we explore the minimum possible uncertainties in stellar mass-to-light (M/L) ratios from the assumed star…

Although measuring the gas metallicity in galaxies at various redshifts is crucial to constrain galaxy evolutionary scenarios, only rest-frame optical emission lines have been generally used to measure the metallicity. This has prevented us…

The metallicity and its relationship with other galactic properties is a fundamental probe of the evolution of galaxies. In this work, we select about 750,000 star-forming spatial pixels from 1122 blue galaxies in the MaNGA survey to…

We search for parameters defined from photometric images to quantify the ex situ stellar mass fraction of galaxies. We created mock images using galaxies in the cosmological hydrodynamical simulations TNG100, EAGLE, and TNG50 at redshift…

We present results exploring the role that probabilistic deep learning models can play in cosmology from large scale astronomical surveys through estimating the distances to galaxies (redshifts) from photometry. Due to the massive scale of…

Accurate redshift estimates are a vital component in understanding galaxy evolution and precision cosmology. In this paper, we explore approaches to increase the applicability of machine learning models for photometric redshift estimation…

We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All Sky Survey using two new training-set methods. We utilize the broad-band…

We derive stellar metallicities, light-weighted ages and stellar masses for a magnitude-limited sample of 175,128 galaxies drawn from the Sloan Digital Sky Survey Data Release Two (SDSS DR2). We compute median-likelihood estimates of these…

We investigate the resolved star formation properties of a sample of 45 massive galaxies (M_*>10^11M_solar) within a redshift range of 1.5 < z < 3 detected in the GOODS NICMOS Survey (Conselice et al. 2011), a HST H-band imaging program. We…

In the era of large sky surveys, photometric redshifts (photo-z) represent crucial information for galaxy evolution and cosmology studies. In this work, we propose a new Machine Learning (ML) tool called Galaxy morphoto-Z with neural…