相关论文: Automated Determination of Stellar Population Para…
With the advent of dedicated photometric space missions, the ability to rapidly process huge catalogues of stars has become paramount. Bellinger and Angelou et al. (2016) recently introduced a new method based on machine learning for…
We present a new method of predicting the ages of galaxies using a machine learning (ML) algorithm with the goal of providing an alternative to traditional methods. We aim to match the ability of traditional models to predict the ages of…
We present differential stellar population models, which allow improved determinations of the ages, iron and alpha-element abundances of old stellar populations from spectral fitting. These new models are calibrated at solar abundances…
Machine Learning is an efficient method for analyzing and interpreting the increasing amount of astronomical data that is available. In this study, we show, a pedagogical approach that should benefit anyone willing to experiment with Deep…
We aim to develop a model-driven deep learning approach to age determination, by training neural networks on stellar evolutionary grids. Contrary to the usual data-driven deep learning approach of using prior age estimates as training data,…
We present a detailed spatial analysis of stellar populations based on long-slit optical spectra in a sample of eight luminous early-type galaxies selected from nearby sparse groups and pairs, three of them may be interacting with a galaxy…
Mass loss is a key property to understand stellar evolution and in particular for low-metallicity environments. Our knowledge has improved dramatically over the last decades both for single and binary evolutionary models. However, episodic…
3D spectroscopy produces hundreds of spectra from which maps of the characteristics of stellar populations (age-metallicity) and internal kinematics of galaxies can be derived. We carried on simulations to assess the reliability of…
We analyse the stellar content of a large number of HII galaxies from the continua and absorption features of their spectra using population synthesis methods, in order to gain information about the star formation histories of these…
The aim of this paper is to study the stellar population of galaxies hosting an active galactic nucleus (AGN). We studied a sub-sample of hard X-ray emitting AGNs from the INTEGRAL and Swift catalogs which were previously identified and…
We present a study of the stellar populations of a sample of 39 local, field early-type galaxies whose HI properties are known from interferometric data. Our aim is to understand whether stellar age and chemical composition depend on the HI…
Supervised machine learning models are increasingly being used for solving the problem of stellar classification of spectroscopic data. However, training such models requires a large number of labelled instances, the collection of which is…
It is currently impossible to determine the abundances of stellar populations star-by-star in dense stellar systems more distant than a few megaparsecs. Therefore, methods to analyse the composite light of stellar systems are required. I…
(Abridged) We explore the dependence of galaxy stellar population properties derived from broad-band SED-fitting - such as age, stellar mass, dust reddening, etc. - on a variety of parameters, such as SFHs, metallicity, IMF, dust reddening…
Over the last decades, evolutionary population synthesis models have powered an unmatched leap forward in our understanding of galaxies. From dating the age of the first galaxies in the Universe to detailed measurements of the chemical…
This review deals with stellar population models computed by means of the evolutionary synthesis technique that was pioneered by Beatrice Tinsley roughly three decades ago. The focus is on the simplest models, the so called Simple Stellar…
The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…
The stellar populations of galaxies contain a wealth of detailed information. From the youngest, most massive stars, to almost invisible remnants, the history of star formation is encoded in the stars that make up a galaxy. Extracting some,…
The development of evolutionary stellar population models is central to interpreting observations of galaxies in terms of astrophysical quantities. Stellar population models must therefore be both accurate and compatible with inversion…
We present our new, fully-automated method to detect and measure the ages of star clusters in nearby galaxies, where individual stars can be resolved. The method relies purely on statistical analysis of observations and Monte-Carlo…