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Discovery of 118 New Ultracool Dwarf Candidates Using Machine Learning Techniques

Fuente: arXiv

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Main Authors:	Brooks, Hunter, Caselden, Dan, Kirkpatrick, J. Davy, Raghu, Yadukrishna, Elachi, Charles, Grigorian, Jake, Trek, Asa, Washburn, Andrew, Higashimura, Hiro, Meisner, Aaron, Schneider, Adam, Faherty, Jacqueline, Marocco, Federico, Gelino, Christopher, Gagné, Jonathan, Bickle, Thomas, Tang, Shih-yun, Rothermich, Austin, Burgasser, Adam, Kuchner, Marc J., Beaulieu, Paul, Bell, John, Colin, Guillaume, Colombo, Giovanni, Dereveanco, Alexandru, Flores, Deiby, Glebov, Konstantin, Gramaize, Leopold, Hamlet, Les, Hinckley, Ken, Kabatnik, Martin, Kiwy, Frank, Martin, David, Palma, Raul, Pendrill, William, Ruiz, Lizzeth, Sanchez, John, Sainio, Arttu, SchÜmann, JÖrg, Schonau, Manfred, Tanner, Christopher, Andersen, Nikolaj Stevnbak, Stenner, Andrés, Thévenot, Melina, Thakur, Vinod, Voloshin, Nikita, Wedracki, Zbigniew
Format:	Preprint
Published:	2024
Subjects:	Solar and Stellar Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
Online Access:	Acceder al recurso
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_version_	1866916410535444480
author	Brooks, Hunter Caselden, Dan Kirkpatrick, J. Davy Raghu, Yadukrishna Elachi, Charles Grigorian, Jake Trek, Asa Washburn, Andrew Higashimura, Hiro Meisner, Aaron Schneider, Adam Faherty, Jacqueline Marocco, Federico Gelino, Christopher Gagné, Jonathan Bickle, Thomas Tang, Shih-yun Rothermich, Austin Burgasser, Adam Kuchner, Marc J. Beaulieu, Paul Bell, John Colin, Guillaume Colombo, Giovanni Dereveanco, Alexandru Flores, Deiby Glebov, Konstantin Gramaize, Leopold Hamlet, Les Hinckley, Ken Kabatnik, Martin Kiwy, Frank Martin, David Palma, Raul Pendrill, William Ruiz, Lizzeth Sanchez, John Sainio, Arttu SchÜmann, JÖrg Schonau, Manfred Tanner, Christopher Andersen, Nikolaj Stevnbak Stenner, Andrés Thévenot, Melina Thakur, Vinod Voloshin, Nikita Wedracki, Zbigniew
author_facet	Brooks, Hunter Caselden, Dan Kirkpatrick, J. Davy Raghu, Yadukrishna Elachi, Charles Grigorian, Jake Trek, Asa Washburn, Andrew Higashimura, Hiro Meisner, Aaron Schneider, Adam Faherty, Jacqueline Marocco, Federico Gelino, Christopher Gagné, Jonathan Bickle, Thomas Tang, Shih-yun Rothermich, Austin Burgasser, Adam Kuchner, Marc J. Beaulieu, Paul Bell, John Colin, Guillaume Colombo, Giovanni Dereveanco, Alexandru Flores, Deiby Glebov, Konstantin Gramaize, Leopold Hamlet, Les Hinckley, Ken Kabatnik, Martin Kiwy, Frank Martin, David Palma, Raul Pendrill, William Ruiz, Lizzeth Sanchez, John Sainio, Arttu SchÜmann, JÖrg Schonau, Manfred Tanner, Christopher Andersen, Nikolaj Stevnbak Stenner, Andrés Thévenot, Melina Thakur, Vinod Voloshin, Nikita Wedracki, Zbigniew
contents	We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine learning tool, named \texttt{SMDET}, 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 2 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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2408_14447
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	Discovery of 118 New Ultracool Dwarf Candidates Using Machine Learning Techniques Brooks, Hunter Caselden, Dan Kirkpatrick, J. Davy Raghu, Yadukrishna Elachi, Charles Grigorian, Jake Trek, Asa Washburn, Andrew Higashimura, Hiro Meisner, Aaron Schneider, Adam Faherty, Jacqueline Marocco, Federico Gelino, Christopher Gagné, Jonathan Bickle, Thomas Tang, Shih-yun Rothermich, Austin Burgasser, Adam Kuchner, Marc J. Beaulieu, Paul Bell, John Colin, Guillaume Colombo, Giovanni Dereveanco, Alexandru Flores, Deiby Glebov, Konstantin Gramaize, Leopold Hamlet, Les Hinckley, Ken Kabatnik, Martin Kiwy, Frank Martin, David Palma, Raul Pendrill, William Ruiz, Lizzeth Sanchez, John Sainio, Arttu SchÜmann, JÖrg Schonau, Manfred Tanner, Christopher Andersen, Nikolaj Stevnbak Stenner, Andrés Thévenot, Melina Thakur, Vinod Voloshin, Nikita Wedracki, Zbigniew Solar and Stellar Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine learning tool, named \texttt{SMDET}, 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 2 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.
title	Discovery of 118 New Ultracool Dwarf Candidates Using Machine Learning Techniques
topic	Solar and Stellar Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
url	https://arxiv.org/abs/2408.14447