Related papers: A Challenge of Developing a Classifier for Multi-B…
The importance of using fast and automatic methods to classify variable stars for large amounts of data is undeniable. There have been many attempts to classify variable stars by traditional algorithms like Random Forest. In recent years,…
Variable stars have a unique part to play in Galactic astronomy. Among the most important of these variables are the Cepheids (types I and II), the RR Lyraes and the Miras (O- and C-rich). The current status of the basic calibration of…
Modern large-scale photometric surveys have provided us with multi-band photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (\teff) and metallicities (\feh), absolute…
With the availability of large-scale surveys like Kepler and TESS, there is a pressing need for automated methods to classify light curves according to known classes of variable stars. We introduce a new algorithm for classifying light…
The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to monitor the entire sky, currently with a cadence of $\lesssim 24$ hours down to $g \lesssim 18.5$ mag. ASAS-SN has routinely operated since 2013,…
We have compiled the first all-sky mid-infrared variable-star catalog based on Wide-field Infrared Survey Explorer (WISE) five-year survey data. Requiring more than 100 detections for a given object, 50,282 carefully and robustly selected…
An analysis of a group of seven variables stars, classed by ASAS-SN as uncertain RRab, is performed comparing their position in a H-R diagram with respect to a sample of variables of the same type built from public astronomical databases.
With the availability of multi-object spectrometers and the designing \& running of some large scale sky surveys, we are obtaining massive spectra. Therefore, it becomes more and more important to deal with the massive spectral data…
Machine learning has achieved an important role in the automatic classification of variable stars, and several classifiers have been proposed over the last decade. These classifiers have achieved impressive performance in several…
Constraints on the formation and evolution of the Milky Way Galaxy require multi-dimensional measurements of kinematics, abundances, and ages for a large population of stars. Ages for luminous giants, which can be seen to large distances,…
This work is part of an effort to detect secular variable objects in large scale surveys by analysing their path in color-magnitude diagrams. To this aim, we first present the variability morphologies in the V/V-I diagram of several types…
The All-Sky Automated Survey for Supernovae (ASAS-SN) provides long baseline (${\sim}4$ yrs) light curves for sources brighter than V$\lesssim17$ mag across the whole sky. As part of our effort to characterize the variability of all the…
Modern photometric multiband digital surveys produce large amounts of data that, in order to be effectively exploited, need automatic tools capable to extract from photometric data an objective classification. We present here a new method…
Information on the spectral types of stars is of great interest in view of the exploitation of space-based imaging surveys. In this article, we investigate the classification of stars into spectral types using only the shape of their…
RV variable stars are important in astrophysics. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has provided ~ 6.5 million stellar spectra in its Data Release 4 (DR4). During the survey, ~ 4.7…
In order to study transient phenomena in the Universe, existing and forthcoming imaging surveys are covering wide areas of sky repeatedly over time, with a range of cadences, point spread functions, and depths. We describe here a framework…
Photometric redshift classifiers provide a means of estimating galaxy redshifts from observations using a small number of broad-band filters. However, the accuracy with which redshifts can be determined is sensitive to the star formation…
Context: It is crucial to develop a method for classifying objects detected in deep surveys at infrared wavelengths. We specifically need a method to separate galaxies from stars using only the infrared information to study the properties…
We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SV) and burst-like (BL) transients, using multi-band image-differencing time-series…
Many decades ago a search for variable stars was one of the main areas of astrophysical research. Such searches, conducted with CCD detectors rather than with photographic plates, became a by-product of several projects seeking…