Related papers: An adaptive algorithm for detecting double stars i…
Although primarily aimed at the galactic archeology and evolution, automated all-sky spectroscopic surveys (RAVE, SDSS) are also a valuable source for the binary star research community. Identification of double-lined spectra is easy and it…
Distances to stars are key to revealing a three-dimensional view of the Milky Way, yet their determination is a major challenge in astronomy. Whilst the brightest nearby stars benefit from direct parallax measurements, fainter stars are…
Observations of binary inspiral in a single interferometric gravitational wave detector can be cataloged according to signal-to-noise ratio $\rho$ and chirp mass $\cal M$. The distribution of events in a catalog composed of observations…
The coalescence of binary neutron stars are one of the main sources of gravitational waves for ground-based gravitational wave detectors. As Bayesian inference for binary neutron stars is computationally expensive, more efficient and faster…
Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…
Using the adaptive optics facilities at the 200-in Hale and 10-m Keck II, we observed in the near infrared a sample of 12 binary and multiple stars and one open cluster. We used the near diffraction limited images of these systems to…
We discuss methods for modeling eclipsing binary stars using the "physical", "simplified" and "phenomenological" models. There are few realizations of the "physical" Wilson-Devinney (1971) code and its improvements, e.g. Binary Maker,…
Data-driven stellar classification has a long and important history in astronomy, dating as far back as Annie Jump Cannon's "by eye" classifications of stars into spectral types still used today. In recent years, data-driven spectroscopy…
Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual…
The space-borne gravitational wave detectors will observe a large population of double white dwarf binaries in the Milky Way. However, the search for double white dwarfs in the gravitational wave data will be time-consuming due to the large…
The statistical properties of double main sequence (MS) binaries are very important for binary evolution and binary population synthesis. To obtain these properties, we need to identify these MS binaries. In this paper, we have developed a…
Machine learning (ML) has become a key tool in astronomy, driving advancements in the analysis and interpretation of complex datasets from observations. This article reviews the application of ML techniques in the identification and…
As the sensitivity of the international gravitational wave detector network increases, observing binary neutron star signals will become more common. Moreover, since these signals will be louder, the chances of detecting them before their…
The adaptive optics system at the 3.6 m AEOS telescope was used to measure the astrometry and differential magnitude in I-band of 56 binary stars in 2002. The astrometric measurements will be of use for future orbital determination, and the…
Young, intermediate-mass stars are experiencing renewed interest as targets for direct-imaging planet searches. However, these types of stars are part of multiple systems more often than not. Close stellar companions affect the formation…
We developed a convolutional neural network (CNN) model to distinguish the double-lined spectroscopic binaries (SB2s) from others based on single exposure medium-resolution spectra ($R\sim 7,500$). The training set consists of a large set…
We present the results of an all-sky survey made with the Fine Guidance Sensor on Hubble Space Telescope to search for angularly resolved binary systems among the massive stars. The sample of 224 stars is comprised mainly of Galactic O- and…
The unparalleled photometric data obtained by NASA's Kepler Space Telescope has led to an improved understanding of stellar structure and evolution - in particular for solar-like oscillators in this context. Binary stars are fascinating…
The statistical characteristics of double main-sequence (MS) binaries are essential for investigating star formation, binary evolution, and population synthesis. Our previous study proposed a machine learning-based method to identify MS…
We developed and applied a computer analysis method to detect ring galaxy candidates in the first data release of PanSTARRS. The method works by applying a low-pass filter, followed by dynamic global thresholding to search for closed…