Related papers: Multi-Layer Perceptron for Predicting Galaxy Param…
We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology Posterior Estimation Network (GaMPEN) estimates values and…
Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian…
The measured star-formation rates (SFRs) of galaxies comprise an important constraint on galaxy evolution and also on their cosmological boundary conditions. Any available tracer of the SFR depends on the shape of the mass-distribution of…
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 use a multilevel perceptron (MLP) neural network to obtain photometry of saturated stars in the All-Sky Automated Survey for Supernovae (ASAS-SN). The MLP can obtain fairly unbiased photometry for stars from g~4 to 14~mag, particularly…
We compare the results of the mark correlation analysis of galaxies in a sample from the Sloan Digital Sky Survey and from two galaxy catalogs obtained by semi-analytical galaxy formation models implemented on the Millennium Simulation. We…
Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work, we analyze the miniJPAS survey, which observed about 1…
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…
To develop galaxy-targeting approaches, the gravitational-wave community built a catalog of stellar mass in the local universe based on the 2MASS spectroscopic and photometric redshift surveys. By cleaning and supplementing this catalog,…
Massive galaxies display extended light profiles that can reach several hundreds of kilo parsecs. These stellar halos provide a fossil record of galaxy assembly histories. Using data that is both wide (~100 square degree) and deep (i>28.5…
We constrain the slope of the star formation rate ($\log\Psi$) to stellar mass ($\log\mathrm{M_{\star}}$) relation down to $\log(\mathrm{M_{\star}/M_{\odot}})=8.4$ ($\log(\mathrm{M_{\star}/M_{\odot}})=9.2$) at $z=0.5$ ($z=2.5$) with a…
This white paper highlights how stellar population gradients, chemical abundance patterns, stellar initial mass function (IMF) variations, and structural signatures in early-type galaxies (ETGs), measured at faint and large galactocentric…
An essential component of galaxy formation theory is the stellar initial mass function (IMF), that describes the parent distribution of stellar mass in star forming regions. We present observational evidence in a sample of early-type…
We present measurements of the specific star-formation rate (SSFR)-stellar mass relation for star-forming galaxies. Our deep spectroscopic samples are based on the Redshift One LDSS3 Emission line Survey, ROLES, and European Southern…
The future astronomical imaging surveys are set to provide precise constraints on cosmological parameters, such as dark energy. However, production of synthetic data for these surveys, to test and validate analysis methods, suffers from a…
Exploiting the sample of 30 local star-forming, undisturbed late-type galaxies in different environments drawn from the GAs Stripping Phenomena in galaxies with MUSE (GASP), we investigate the spatially resolved Star Formation Rate-Mass…
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…
Context. Measuring how the physical properties of galaxies change across cosmic times is essential to understand galaxy formation and evolution. With the advent of numerous ground-based and space-borne instruments launched over the past few…
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our understanding of the galaxy evolution and the unresolved…
We present EzGal, a flexible python program designed to easily generate observable parameters (magnitudes, colors, mass-to-light ratios) for any stellar population synthesis (SPS) model. As has been demonstrated by various authors, the…