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Title: Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
Abstract We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine-learning tool, namedSMDET, applied to time-series images from the Wide-field Infrared Survey Explorer. We gathered photometric and astrometric data to estimate each candidate’s spectral type, distance, and tangential velocity. This sample has a photometrically estimated spectral class distribution of 28 M dwarfs, 64 L dwarfs, and 18 T dwarfs. We also identify a T-subdwarf candidate, two extreme T-subdwarf candidates, and two candidate young ultracool dwarfs. Five objects did not have enough photometric data for any estimations to be made. To validate our estimated spectral types, spectra were collected for two objects, yielding confirmed spectral types of T5 (estimated T5) and T3 (estimated T4). Demonstrating the effectiveness of machine-learning tools as a new large-scale discovery technique.  more » « less
Award ID(s):
2009177 2238468
PAR ID:
10571614
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; « less
Corporate Creator(s):
Publisher / Repository:
The Astronomical Journal
Date Published:
Journal Name:
The Astronomical Journal
Volume:
168
Issue:
5
ISSN:
0004-6256
Page Range / eLocation ID:
211
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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