Automated Stellar Spectral Classification and Parameterization for the Masses [PDF]
, 2002 Stellar spectroscopic classification has been successfully automated by a number of groups. Automated classification and parameterization work best when applied to a homogeneous data set, and thus these techniques primarily have been developed for and ...
Ted von Hippel +2 more
openalex +5 more sources
Gaia Data Release 3. Apsis. III. Non-stellar content and source classification [PDF]
Astronomy & Astrophysics, 2022 Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination
L. Delchambre +80 more
semanticscholar +1 more source
Gaia Data Release 3. Validating the classification of variable young stellar object candidates [PDF]
Astronomy & Astrophysics, 2022 Context. The Gaia third Data Release (DR3) presents the first catalogue of full-sky variable Young Stellar Object (YSO) candidates observed by the Gaia space telescope during the initial 34 months of science operations. Aims.
G. Marton +16 more
semanticscholar +1 more source
Mira variables in the Milky Way’s nuclear stellar disc: discovery and classification [PDF]
Monthly notices of the Royal Astronomical Society, 2022 The properties of the Milky Way’s nuclear stellar disc give crucial information on the epoch of bar formation. Mira variables are promising bright candidates to study the nuclear stellar disc, and through their period–age relation dissect its star ...
J. Sanders +5 more
semanticscholar +1 more source
TESS Data for Asteroseismology (T’DA) Stellar Variability Classification Pipeline: Setup and Application to the Kepler Q9 Data [PDF]
Astronomical Journal, 2021 The NASA Transiting Exoplanet Survey Satellite (TESS) is observing tens of millions of stars with time spans ranging from ∼27 days to about 1 yr of continuous observations.
J. Audenaert +18 more
semanticscholar +1 more source
The Astrophysical Journal, 2023 We present precise photometric estimates of stellar parameters, including effective temperature, metallicity, luminosity classification, distance, and stellar age, for nearly 26 million stars using the methodology developed in the first paper of this ...
Yang Huang +20 more
doaj +1 more source
Stellar Classification based on Various Star Characteristics using Machine Learning Algorithms
Journal of student-scientists' research, 2023 The task of stellar classification can be tedious and lengthy when done manually. One can expedite stellar classification by creating an artificial intelligence model to automate the process.
Jesus Tamez Villarreal, Sophia Barton
semanticscholar +1 more source
BCD Spectrophotometry and Rotation of Active B-Type Stars: Theory and Observations
Galaxies, 2023 This review has two parts. The first one is devoted to the Barbier–Chalonge–Divan (BCD) spectrophotometric system, also known as the Paris spectral classification system.
Juan Zorec
doaj +1 more source
“In-System” Fission-Events: An Insight into Puzzles of Exoplanets and Stars?
Universe, 2021 In expansion of our recent proposal that the solar system’s evolution occurred in two stages—during the first stage, the gaseous giants formed (via disk instability), and, during the second stage (caused by an encounter with a particular stellar-object ...
Elizabeth P. Tito, Vadim I. Pavlov
doaj +1 more source
On the use of logistic regression for stellar classification [PDF]
Experimental astronomy (Print), 2018 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 years and they ...
L. Beitia-Antero +2 more
semanticscholar +1 more source