Related papers: Imbalanced learning for RR Lyrae stars
We discuss a sample of over 3000 candidate RR Lyrae stars selected by various methods using Sloan Digital Sky Survey data for about 1000 deg^2 of sky. These stars probe the halo structure out to ~100 kpc from the Galactic center. Their…
The TESS space telescope is collecting continuous, high-precision optical photometry of stars throughout the sky, including thousands of RR Lyrae stars. In this paper, we present results for an initial sample of 118 nearby RR Lyrae stars…
In this work, we derive systemic velocities and subsequently orbits for 8456 RR~Lyrae stars. We identify interlopers from other Milky Way (MW) structures, which amount to 22 percent of the total sample. Most interlopers are associated with…
We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few…
A programming tactic involving polyhedra is reported that has been widely applied in the polyhedral analysis of (constraint) logic programs. The method enables the computations of convex hulls that are required for polyhedral analysis to be…
This paper describes an algorithm obtained by merging a recursive star identification algorithm with a recently developed adaptive SVD-based estimator of the angular velocity vector (QuateRA). In a recursive algorithm, the more accurate the…
We present new $P -\phi_{31}-{\rm [Fe/H]}$ and $P -\phi_{31}- A_2 - {\rm [Fe/H]}$ relations for fundamental-mode (RRab) and first-overtone mode (RRc) RR Lyrae stars (RRLs), respectively. The relations were calibrated based on pulsation…
We present a comprehensive photometric study of RR Lyrae stars in the M3 globular cluster, utilising a vast dataset of 3140 optical ($UBVRI$) CCD images spanning 35 years from astronomical data archives. We have successfully identified…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this…
We present a careful and detailed light curve analysis of publicly available $I$-band data on fundamental mode RR Lyrae (RRab) stars of the Large Magellanic Cloud (LMC) obtained by the Optical Gravitational Lensing Experiment (OGLE)…
The Laser Interferometer Space Antenna (LISA) will open a new observational window in the millihertz gravitational-wave band, enabling the detection of tens of thousands of compact stellar remnant binaries across the Milky Way. Most of…
Classification of intermediate redshift ($z$ = 0.3--0.8) emission line galaxies as star-forming galaxies, composite galaxies, active galactic nuclei (AGN), or low-ionization nuclear emission regions (LINERs) using optical spectra alone was…
Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to…
Ultraviolet (UV) galaxies have been selected from GALEX. The presence of a FUV-dropout in their spectral energy distributions proved to be a very complete (83.3%) but not very efficient (21.4%) tool for identifying Lyman Break Galaxies…
In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…
Star-shaped bodies are an important nonconvex generalization of convex bodies (e.g., linear programming with violations). Here we present an efficient algorithm for sampling a given star-shaped body. The complexity of the algorithm grows…
Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…
I review statistical parallax absolute magnitude determinations which employ data from the HIPPARCOS satellite for RR Lyrae and Cepheid variables, and for several other stellar classes. Five groups have studied the RR Lyrae stars, and the…
We present a machine learning method to estimate the physical parameters of classical pulsating stars such as RR Lyrae and Cepheid variables based on an automated comparison of their theoretical and observed light curve parameters at…