Related papers: The Cannon: A data-driven approach to stellar labe…
Stellar light curves are well known to encode physical stellar properties. Precise, automated and computationally inexpensive methods to derive physical parameters from light curves are needed to cope with the large influx of these data…
The goal of this paper is to describe the science verification of Milky Way Mapper (MWM) APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) data products published in Data Release 19 (DR19) of the fifth phase of the Sloan…
Galah is an ongoing high-resolution spectroscopic survey with the goal of disentangling the formation history of the Milky Way, using the fossil remnants of disrupted star formation sites which are now dispersed around the Galaxy. It is…
Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra obtained by the LAMOST survey. The CNN is trained on a dataset…
We present a semi-empirical spectral classification scheme for normal B-type stars using near-infrared spectra (1.5-1.7 $\mu$m) from the SDSS APOGEE2-N DR14 database. The main motivation for working with B-type stars is their importance in…
Detailed chemical abundances of Galactic stars are needed in order to improve our knowledge of the formation and evolution of our galaxy, the Milky Way. We took advantage of the GIANO archive spectra to select a sample of Galactic disc…
Upcoming large-scale spectroscopic surveys such as WEAVE and 4MOST will provide thousands of spectra of massive stars, which need to be analysed in an efficient and homogeneous way. Studies on massive stars are usually based on samples of a…
Low-resolution spectra are proved competitive to high-resolution spectra in determining many stellar labels at comparable precision. It is useful to consider the spectral information content when assessing the capability of a stellar…
Context. Spectroscopic surveys like APOGEE, GALAH, and LAMOST have significantly advanced our understanding of the Milky Way by providing extensive stellar parameters and chemical abundances. Complementing these, photometric surveys with…
We present a machine learning (ML) pipeline to identify star clusters in the multi{color images of nearby galaxies, from observations obtained with the Hubble Space Telescope as part of the Treasury Project LEGUS (Legacy ExtraGalactic…
Massive stars play a significant role in different branches of astronomy, from shaping the processes of star and planet formation to influencing the evolution and chemical enrichment of the distant universe. Despite their high astrophysical…
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification…
We propose a new method for measuring the spatial density distribution of the stellar halo of the Milky Way. Our method is based on a pairwise statistic of the distribution of stars on the sky, the angular two-point correlation function…
New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…
Dusty stellar point sources are a significant stage in stellar evolution and contribute to the metal enrichment of galaxies. These objects can be classified using photometric and spectroscopic observations with color-magnitude diagrams…
Context. There are more than 3000 known Galactic planetary nebulae (PNe), but only 492 central stars of Galactic planetary nebulae (CSPN) have known spectral types. It is vital to increase this number in order to have reliable statistics,…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
The achievable level of precision on photospheric abundances of stars is a major limiting factor on investigations of exoplanet host star characteristics, the chemical histories of star clusters, and the evolution of the Milky Way and other…
We derive stellar parameters and abundances (`stellar labels') of 40,034 late-B and A-type main-sequence stars extracted from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope Medium Resolution Survey (LAMOST--MRS). The primary…
We analyze a large sample of 885 GCs giants from the APOGEE survey. We used the Cannon results to separate the red giant branch and the asymptotic giant branch stars, not only allowing for a refinement of surface gravity from isochrones,…