Related papers: Photometric Analysis for Predicting Star Formation…
Star Formation Rates or SFRs are crucial to constrain theories of galaxy formation and evolution. SFRs are usually estimated via spectroscopic observations requiring large amounts of telescope time. We explore an alternative approach based…
Global Stellar Formation Rates or SFRs are crucial to constrain theories of galaxy formation and evolution. SFR's are usually estimated via spectroscopic observations which require too much previous telescope time and therefore cannot match…
In this study, we develop an artificial neural network to estimate the infrared (IR) luminosity and star formation rates (SFR) of galaxies. Our network is trained using 'true' IR luminosity values derived from modeling the IR spectral…
In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…
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…
In this paper, we test the age matching hypothesis that the star formation rate (SFR) of a galaxy of fixed stellar mass is determined by its dark matter halo formation history, and as such, that more quiescent galaxies reside in older…
Star-formation activity is a key property to probe the structure formation and hence characterise the large-scale structures of the universe. This information can be deduced from the star formation rate (SFR) and the stellar mass (Mstar),…
We present a classification of galaxies in the Pan-STARRS1 (PS1) 3$\pi$ survey based on their recent star formation history and morphology. Specifically, we train and test two Random Forest (RF) classifiers using photometric features…
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…
Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most…
This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…
The star formation rate - stellar mass relation (SFR-M*) and its evolution (i.e., the SFR main sequence) describes the growth rate of galaxies of a given stellar mass and at a given redshift. Assuming that present-day star-forming galaxies…
We trace the specific star formation rate (sSFR) of massive star-forming galaxies ($\gtrsim\!10^{10}\,\mathcal{M}_\odot$) from $z\sim2$ to 7. Our method is substantially different from previous analyses, as it does not rely on direct…
(Abridged) The star-formation rate (SFR) quantitatively describes the star-formation process in galaxies. Current ways to calibrate this rate do not usually employ observational methods accounting for the low-mass end of stellar populations…
We present multi-wavelength global star formation rate (SFR) estimates for 326 galaxies from the Star Formation Reference Survey (SFRS) in order to determine the mutual scatter and range of validity of different indicators. The widely used…
We construct a model by integrating observational constraints from the Milky Way and nearby galaxies to predict cloud-scale star formation rates (SFRs). In the model, we first estimate the initial total mass of clumps in a cloud based on…
In this work we estimate the Star Formation Rate (SFR) through 333 Long-GRBs detected by Swift. This investigation is based on the empirical model proposed by Y\"uksel et al. (2008), basically, the SFR is estimated using long-GRBs…
[abridged] We study the evolution of the Star Formation Rate Function (SFRF) of massive galaxies over the 0.4<z<1.8 redshift range and its implications for our understanding of the physical processes responsible for galaxy evolution. We use…
Star formation is arguably the most important physical process in the cosmos. It is a fundamental driver of galaxy evolution and the ultimate source of most of the energy emitted by galaxies. A correct interpretation of star formation rate…
Parametric models for galaxy star-formation histories (SFHs) are widely used, though they are known to impose strong priors on physical parameters. This has consequences for measurements of the galaxy stellar-mass function (GSMF),…