Related papers: Stellar Populations With Optical Spectra: Deep Lea…
Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their…
We perform a pixel-by-pixel analysis of 467 galaxies in the GOODS-VIMOS survey to study systematic effects in extracting properties of stellar populations (age, dust, metallicity and SFR) from pixel colors using the pixel-z method. The…
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…
Stellar population studies provide unique clues to constrain galaxy formation models. So far, detailed studies based on absorption line strengths have mainly focused on the optical spectral range although many diagnostic features are…
The calibrations linking observed luminosities to the star formation rate depend on the assumed stellar population synthesis model, initial mass function, star formation and metal enrichment history, and whether reprocessing by dust and gas…
We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…
The possibility to constrain cosmological parameters from galaxy surveys using field-level machine learning methods that bypass traditional summary statistics analyses, depends crucially on our ability to generate simulated training sets.…
Spectral energy distribution (SED) models are widely used to infer the physical properties of galaxies from multi-wavelength photometry, but their accuracy is difficult to assess because the true properties of observed galaxies are…
High-resolution galaxy spectra encode information about the stellar populations within galaxies. The properties of the stars, such as their ages, masses, and metallicities, provide insights into the underlying physical processes that drive…
The integrated spectra of stellar systems contain a wealth of information, and its analysis can reveal fundamental parameters such as metallicity, age and star formation history. Widely used methods to analyze these spectra are based on…
We first presented an isochrone database that can be widely used for stellar population synthesis studies and colour-magnitude diagram (CMD) fitting. The database consists of the isochrones of both single star and binary star simple stellar…
Numerous high-$z$ galaxies have recently been observed with JWST, providing new insights into early galaxy evolution. Their physical properties are typically derived through spectral energy distribution (SED) fitting, but the reliability of…
When completed, the PHANGS-HST project will provide a census of roughly 50,000 compact star clusters and associations, as well as human morphological classifications for roughly 20,000 of those objects. These large numbers motivated the…
In the present work we compare in detail some of the major theoretical libraries with observations, aiming at detecting weaknesses and strengths from the stellar population modelling point of view. We compared model predictions and…
We used a convolutional neural network to infer stellar rotation periods from a set of synthetic light curves simulated with realistic spot evolution patterns. We convolved these simulated light curves with real TESS light curves containing…
Spectra of galaxies contain an enormous amount of information about the relative mixture of ages and metallicities of constituent stars. We present a comprehensive study designed to extract the maximum information from spectra of data…
Interpreting galaxy properties from astronomical surveys relies heavily on spectral energy distribution (SED) modelling, yet uncertainties in key model ingredients are often overlooked. By leveraging a $z\sim0$ galaxy sample from the EAGLE…
We present the results of a MOPED analysis of ~3 x 10^5 galaxy spectra from the Sloan Digital Sky Survey Data Release Three (SDSS DR3), with a number of improvements in data, modelling and analysis compared with our previous analysis of…
Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supervised machine learning method (GoogLeNet) to automatically…
We test the predictions of spectral synthesis models based on seven different massive-star prescriptions against Legacy ExtraGalactic UV Survey (LEGUS) observations of eight young massive clusters in two local galaxies, NGC 1566 and NGC…