相关论文: Imbalanced learning for RR Lyrae stars

We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to train an optimised random forest classifier using photometry from the SDSS and the Widefield Infrared Survey Explorer (WISE). We applied this…

The results of nonlinear, convective models of RR Lyrae pulsators with metal content Z=0.0001 to 0.006 are discussed and several predicted relations connecting pulsational (period and amplitude of pulsation) and evolutionary parameters…

We present a view of the stellar halo in the inner-central regions of the Milky Way (R <~ 10 kpc) mapped by RR Lyrae stars. The combined BRAVA-RR/APOGEE RR Lyrae catalog is used to obtain a sample of 281 RR Lyrae stars located in the bulge…

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the…

We present a group of 3740 previously identified RR Lyrae variables well-observed with the Wide-field Infrared Survey Explorer (WISE). We explore how the shape of the generic RR Lyrae mid-infrared light curve evolves in period-space,…

Context. The environment plays a crucial role in galaxy evolution, particularly for galaxies infalling into clusters. Accurately estimating the infall times of galaxies from observations can significantly enhance our understanding of the…

With the development of a series of Galaxy sky surveys in recent years, the observations increased rapidly, which makes the research of machine learning methods for galaxy image recognition a hot topic. Available automatic galaxy image…

We use the extended and updated OGLE Collection of Variable Stars to thoroughly analyze distribution of RR Lyrae stars in the Magellanic Bridge. We use photometric metallicities to derive absolute Wesenheit magnitude and then individual…

Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify…

We present a sample of ~5,000 RR Lyrae stars selected from the recalibrated LINEAR dataset and detected at heliocentric distances between 5 kpc and 30 kpc over ~8,000 deg^2 of sky. The coordinates and light curve properties, such as period…

The first catalog of the RR Lyrae stars (RRLS) in the Galactic halo by the QUEST Survey has been searched for significant overdensities that may be debris from disrupted dwarf galaxies or globular clusters. Away from the major…

We present a method for photometric selection of metal-poor halo giants from the imaging data of the Sloan Digital Sky Survey (SDSS). These stars are offset from the stellar locus in the (g-r) vs. (u-g) color-color diagram. Based on a…

Context. Globular clusters (GCs) are witnesses of the past accretion events onto the Milky Way (MW). In particular, the GCs of the Sagittarius (Sgr) dwarf galaxy are important probes of an on-going merger. Aims. Our main goal is to search…

We describe and summarize the findings from our CCD time-series photometry of globular clusters (GCs) program and the use of difference image analysis (DIA) in the extraction of very precise light curves even in the crowded central regions…

RR Lyrae (RR Lyr) stars are a well-known and useful distance indicator for old stellar populations such as globular clusters and dwarf galaxies. Fundamental-mode RR Lyr (RRab) stars are commonly used to measure distances, and the accuracy…

In this experiment, we created a Multiple-Input Neural Network, consisting of Convolutional and Multi-layer Neural Networks. With this setup the selected highest-performing neural network was able to distinguish variable stars based on the…

We present a new complete Near-Infrared (NIR, $JHK_s$) census of RR Lyrae stars (RRLs) in the globular $\omega$ Cen (NGC 5139). We collected 15,472 $JHK_s$ images with 4-8m class telescopes over 15 years (2000-2015) covering a sky area…

We develop a machine learning based algorithm using a convolutional neural network (CNN) to identify low HI column density Ly$\alpha$ absorption systems ($\log{N_{\mathrm{HI}}}/{\rm cm}^{-2}<17$) in the Ly$\alpha$ forest, and predict their…

The projected density distribution of type ab RR Lyrae (RRab) stars was characterised from the innermost regions of the Milky Way to the halo, with the aim of placing constraints on the Galaxys evolution. The compiled sample (N_RRab =…

We used a combination of public RR Lyrae star catalogs and a Bayesian methodology to derive robust structural parameters of the inner Halo (<25 kpc) and Thick Disc of the Milky Way. RR Lyrae stars are an unequivocal tracer of old metal-poor…