Related papers: Using Neural Network Models to Estimate Stellar Ag…
We present an empirical model of age-dependent photospheric lithium depletion, calibrated using a large, homogeneously-analysed sample of 6200 stars in 52 open clusters, with ages from 2--6000 Myr and $-0.3<{\rm [Fe/H}]<0.2$, observed in…
We explore the application of artificial neural networks (ANNs) for the estimation of atmospheric parameters (Teff, logg, and [Fe/H]) for Galactic F- and G-type stars. The ANNs are fed with medium-resolution (~ 1-2 A) non flux-calibrated…
Artificial neural networks (ANN) have different applications in Astronomy, including data reduction and data mining. In this work we propose the use ANNs in the identification of stellar model solutions. We illustrate this method, by…
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…
New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…
We present a survey of lithium abundances in 185 main- sequence field stars with Teff between 5600 and 6600 K and [Fe/H] from -1.4 to +0.2 based on high-resolution spectra of 130 stars and a reanalysis of data from Lambert et al. (1991).…
Identification of metal-poor stars among field stars is extremely useful for studying the structure and evolution of the Galaxy and of external galaxies. We search for metal-poor stars using the artificial neural network (ANN) and extend…
Our study is a follow-up of the SACY project, an extended survey in the Southern Hemisphere targeted to search for young nearby associations. Nine associations have either been newly identified, or had their member list better defined.…
The lithium doublet at 6708 \AA\ provides an age diagnostic for main sequence FGK dwarfs. We measured the abundance of lithium in 1305 stars with detected transiting planets from the Kepler Mission using high-resolution spectroscopy. Our…
Determining the physical parameters of pulsating variable stars such as RR Lyrae is essential for understanding their internal structure, pulsation mechanisms, and evolutionary state. In this study, we present a machine learning framework…
The artificial neural network (ANN) is a well-established mathematical technique for data prediction, based on the identification of correlations and pattern recognition in input training sets. We present the application of ANNs to predict…
We estimate cluster ages from lithium depletion in five pre-main-sequence groups found within 100 pc of the Sun: TW Hydrae Association, Eta Chamaeleontis Cluster, Beta Pictoris Moving Group, Tucanae-Horologium Association and AB Doradus…
A new approach to estimating photometric redshifts - using Artificial Neural Networks (ANNs) - is investigated. Unlike the standard template-fitting photometric redshift technique, a large spectroscopically-identified training set is…
Stellar ages are key to improving our understanding of different astrophysical phenomena. However, many techniques to estimate stellar ages are highly model-dependent. The lithium depletion boundary (LDB), based on the presence or absence…
Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades will demand novel, fully automatic methods of data analysis. Artificial intelligence approaches hold great…
The dispersed remnants of stellar nurseries, stellar associations provide unparalleled samples of coeval stars critical for studies of stellar and planetary formation and evolution. The Carina Stellar Association is one of the closest…
All-sky photometric time-series missions have allowed for the monitoring of thousands of young ($t_{\rm age} < 800$Myr) to understand the evolution of stellar activity. Here we developed a convolutional neural network (CNN),…
Previous studies of open clusters have shown that lithium depletion is not only strongly age dependent but also shows a complex pattern with other parameters that is not yet understood. For pre- and main-sequence late-type stars, these…
With its origin coming from several sources (Big Bang, stars, cosmic rays) and given its strong depletion during its stellar lifetime, the lithium element is of great interest as its chemical evolution in the Milky Way is not well…
Age is a fundamental parameter of stars, yet in many cases ages of individual stars are presented without robust estimates of the uncertainty. We have developed a Bayesian framework, BAFFLES, to produce the age posterior for a star from its…