Related papers: Automatic classification of K2 pulsating stars usi…
Spinspotter is a robust and automated algorithm designed to extract stellar rotation periods from large photometric datasets with minimal supervision. Our approach uses the autocorrelation function (ACF) to identify stellar rotation periods…
This work aims to develop a computationally inexpensive approach, based on machine learning techniques, to accurately predict thousands of stellar rotation periods. The innovation in our approach is the use of the XGBoost algorithm to…
The exploitation of present and future synoptic (multi-band and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation. In this work, using data extracted from the Catalina Real Time…
Searching for extraterrestrial, transient signals in astronomical data sets is an active area of current research. However, machine learning techniques are lacking in the literature concerning single-pulse detection. This paper presents a…
Symbiotic stars (SySts) are interacting binaries composed of a red giant transferring material to a hot compact star, typically a white dwarf. Although only about 300 systems are confirmed, the Galactic population is estimated at 1.2 x 10^3…
Galaxy redshift surveys can be used to detect gravitationally-lensed quasars if the spectra obtained are searched for the quasars' emission lines. Previous investigations of this possibility have used simple models to show that the 2 degree…
The Kepler Mission revolutionized exoplanet science and stellar astrophysics by obtaining highly precise photometry of over 200,000 stars over 4 years. A critical piece of information to exploit Kepler data is its selection function, since…
The NASA K2 mission that succeeded the nominal Kepler mission observed several hundreds of thousands of stars during its operations. While most of the stars were observed in single campaigns of 80 days, some of them were targeted for more…
Visual classification of the variability classes of over 120,000 Kepler, K2 and TESS stars is presented. The sample is mainly based on stars with known spectral types. Since variability classification often requires the location of the star…
Pulsar detection has become an active research topic in radio astronomy recently. One of the essential procedures for pulsar detection is pulsar candidate sifting (PCS), a procedure of finding out the potential pulsar signals in a survey.…
In this work we focus on the determination of the relative distributions of young, intermediate-age and old populations of stars in galaxies. Starting from a grid of theoretical population synthesis models we constructed a set of model…
Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution…
We report in this paper spectroscopic and photometric analysis of eight massive stars observed during Campaign 8 of the Kepler/K2 mission from January to March 2016. Spectroscopic data were obtained on these stars at OPD/LNA, Brazil, and…
We report progress in the development of automatic star/galaxy classifier for processing images generated by large galaxy surveys like APM. Our classification method is based on neural networks using the Kohonen Self-Organizing Map…
Upcoming synoptic surveys are set to generate an unprecedented amount of data. This requires an automatic framework that can quickly and efficiently provide classification labels for several new object classification challenges. Using data…
With the step-and-stare approach of the K2 mission, Kepler will be able to observe a large number of Cepheid an RR Lyrae stars. In this paper we describe the target selection efforts, and the first impressions based on the K2 two-wheel…
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…
The large number of stars for which uninterrupted high-precision photometric timeseries data are being collected with \textit{Kepler} and CoRoT initiated the development of automated methods to analyse the stochastically excited…
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…
We present the Signal Detection using Random-Forest Algorithm (SIDRA). SIDRA is a detection and classification algorithm based on the Machine Learning technique (Random Forest). The goal of this paper is to show the power of SIDRA for quick…