Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques

We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine-learning tool, named 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, a...

Full description

Bibliographic Details
Main Authors: Hunter Brooks, Dan Caselden, J. Davy Kirkpatrick, Yadukrishna Raghu, Charles A. Elachi, Jake Grigorian, Asa Trek, Andrew Washburn, Hiro Higashimura, Aaron M. Meisner, Adam C. Schneider, Jacqueline K. Faherty, Federico Marocco, Christopher R. Gelino, Jonathan Gagné, Thomas P. Bickle, Shih-Yun Tang, Austin Rothermich, Adam J. Burgasser, Marc J. Kuchner, Paul Beaulieu, John Bell, Guillaume Colin, Giovanni Colombo, Alexandru Dereveanco, Deiby Pozo Flores, Konstantin Glebov, Leopold Gramaize, Les Hamlet, Ken Hinckley, Martin Kabatnik, Frank Kiwy, David W. Martin, Raúl F. Palma Méndez, Billy Pendrill, Lizzeth Ruiz, John Sanchez, Arttu Sainio, Jörg Schümann, Manfred Schonau, Christopher Tanner, Nikolaj Stevnbak, Andres Stenner, Melina Thévenot, Vinod Thakur, Nikita V. Voloshin, Zbigniew Wȩdracki, The Backyard Worlds: Planet 9 Collaboration
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:The Astronomical Journal
Subjects:
Online Access:https://doi.org/10.3847/1538-3881/ad77d2
_version_ 1827064613441634304
author Hunter Brooks
Dan Caselden
J. Davy Kirkpatrick
Yadukrishna Raghu
Charles A. Elachi
Jake Grigorian
Asa Trek
Andrew Washburn
Hiro Higashimura
Aaron M. Meisner
Adam C. Schneider
Jacqueline K. Faherty
Federico Marocco
Christopher R. Gelino
Jonathan Gagné
Thomas P. Bickle
Shih-Yun Tang
Austin Rothermich
Adam J. Burgasser
Marc J. Kuchner
Paul Beaulieu
John Bell
Guillaume Colin
Giovanni Colombo
Alexandru Dereveanco
Deiby Pozo Flores
Konstantin Glebov
Leopold Gramaize
Les Hamlet
Ken Hinckley
Martin Kabatnik
Frank Kiwy
David W. Martin
Raúl F. Palma Méndez
Billy Pendrill
Lizzeth Ruiz
John Sanchez
Arttu Sainio
Jörg Schümann
Manfred Schonau
Christopher Tanner
Nikolaj Stevnbak
Andres Stenner
Melina Thévenot
Vinod Thakur
Nikita V. Voloshin
Zbigniew Wȩdracki
The Backyard Worlds: Planet 9 Collaboration
author_facet Hunter Brooks
Dan Caselden
J. Davy Kirkpatrick
Yadukrishna Raghu
Charles A. Elachi
Jake Grigorian
Asa Trek
Andrew Washburn
Hiro Higashimura
Aaron M. Meisner
Adam C. Schneider
Jacqueline K. Faherty
Federico Marocco
Christopher R. Gelino
Jonathan Gagné
Thomas P. Bickle
Shih-Yun Tang
Austin Rothermich
Adam J. Burgasser
Marc J. Kuchner
Paul Beaulieu
John Bell
Guillaume Colin
Giovanni Colombo
Alexandru Dereveanco
Deiby Pozo Flores
Konstantin Glebov
Leopold Gramaize
Les Hamlet
Ken Hinckley
Martin Kabatnik
Frank Kiwy
David W. Martin
Raúl F. Palma Méndez
Billy Pendrill
Lizzeth Ruiz
John Sanchez
Arttu Sainio
Jörg Schümann
Manfred Schonau
Christopher Tanner
Nikolaj Stevnbak
Andres Stenner
Melina Thévenot
Vinod Thakur
Nikita V. Voloshin
Zbigniew Wȩdracki
The Backyard Worlds: Planet 9 Collaboration
author_sort Hunter Brooks
collection DOAJ
description We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine-learning tool, named 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 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.
first_indexed 2025-03-19T22:49:56Z
format Article
id doaj.art-a7245ff2ae714ce8a73b7467348fb0e7
institution Directory Open Access Journal
issn 1538-3881
language English
last_indexed 2025-03-19T22:49:56Z
publishDate 2024-01-01
publisher IOP Publishing
record_format Article
series The Astronomical Journal
spelling doaj.art-a7245ff2ae714ce8a73b7467348fb0e72024-10-17T07:57:56ZengIOP PublishingThe Astronomical Journal1538-38812024-01-01168521110.3847/1538-3881/ad77d2Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning TechniquesHunter Brooks0https://orcid.org/0000-0002-5253-0383Dan Caselden1https://orcid.org/0000-0001-7896-5791J. Davy Kirkpatrick2https://orcid.org/0000-0003-4269-260XYadukrishna Raghu3https://orcid.org/0000-0001-9778-7054Charles A. Elachi4Jake Grigorian5https://orcid.org/0000-0002-2466-865XAsa Trek6https://orcid.org/0009-0008-3778-487XAndrew Washburn7https://orcid.org/0009-0005-6222-6026Hiro Higashimura8https://orcid.org/0009-0004-9088-7510Aaron M. Meisner9https://orcid.org/0000-0002-1125-7384Adam C. Schneider10https://orcid.org/0000-0002-6294-5937Jacqueline K. Faherty11https://orcid.org/0000-0001-6251-0573Federico Marocco12https://orcid.org/0000-0001-7519-1700Christopher R. Gelino13https://orcid.org/0000-0001-5072-4574Jonathan Gagné14https://orcid.org/0000-0002-2592-9612Thomas P. Bickle15https://orcid.org/0000-0003-2235-761XShih-Yun Tang16https://orcid.org/0000-0003-4247-1401Austin Rothermich17https://orcid.org/0000-0003-4083-9962Adam J. Burgasser18https://orcid.org/0000-0002-6523-9536Marc J. Kuchner19https://orcid.org/0000-0002-2387-5489Paul Beaulieu20John Bell21Guillaume Colin22https://orcid.org/0000-0002-7630-1243Giovanni Colombo23https://orcid.org/0000-0002-8295-542XAlexandru Dereveanco24Deiby Pozo Flores25Konstantin Glebov26Leopold Gramaize27https://orcid.org/0000-0002-8960-4964Les Hamlet28https://orcid.org/0000-0002-7389-2092Ken Hinckley29https://orcid.org/0000-0002-4733-4927Martin Kabatnik30https://orcid.org/0000-0003-4905-1370Frank Kiwy31https://orcid.org/0000-0001-8662-1622David W. Martin32Raúl F. Palma Méndez33Billy Pendrill34Lizzeth Ruiz35John Sanchez36Arttu Sainio37https://orcid.org/0000-0003-4864-5484Jörg Schümann38https://orcid.org/0000-0002-7587-7195Manfred Schonau39Christopher Tanner40Nikolaj Stevnbak41https://orcid.org/0000-0003-4714-3829Andres Stenner42Melina Thévenot43https://orcid.org/0000-0001-5284-9231Vinod Thakur44Nikita V. Voloshin45Zbigniew Wȩdracki46The Backyard Worlds: Planet 9 CollaborationDepartment of Astronomy and Planetary Science, Northern Arizona University , Flagstaff, AZ 86011, USA; NSF National Optical-Infrared Astronomy Research Laboratory , 950 N. Cherry Avenue, Tucson, AZ 85719, USADepartment of Astrophysics , American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, USAIPAC , Mail Code 100-22, Caltech, 1200 E. California Boulevard, Pasadena, CA 91125, USABackyard Worlds: Planet 9Seaver College, Pepperdine University , Malibu, CA 90263, USAUniversity of Southern California, University Park Campus , Los Angeles, CA 90089, USABackyard Worlds: Planet 9Backyard Worlds: Planet 9Earl of March Intermediate School , 4 The Pkwy, Kanata, ON K2K 1Y4, CanadaNSF National Optical-Infrared Astronomy Research Laboratory , 950 N. Cherry Avenue, Tucson, AZ 85719, USAUnited States Naval Observatory , Flagstaff Station, 10391 West Naval Observatory Road, Flagstaff, AZ 86005, USADepartment of Astrophysics , American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, USAIPAC , Mail Code 100-22, Caltech, 1200 E. California Boulevard, Pasadena, CA 91125, USAIPAC , Mail Code 100-22, Caltech, 1200 E. California Boulevard, Pasadena, CA 91125, USAPlanétarium de Montrál , Espace pour la Vie, 4801 av. Pierre-de Coubertin, Montréal, Québec, Canada; Trottier Institute for Research on Exoplanets, Université de Montréal , Département de Physique, C.P. 6128 Succ. Centre-ville, Montréal, QC H3C 3J7, CanadaBackyard Worlds: Planet 9; School of Physical Sciences, The Open University , Milton Keynes, MK7 6AA, UKDepartment of Physics and Astronomy, Rice University , 6100 Main Street, Houston, TX 77005, USA; Lowell Observatory , 1400 West Mars Hill Road, Flagstaff, AZ 86001, USADepartment of Astrophysics , American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, USA; Backyard Worlds: Planet 9; Department of Physics, Graduate Center, City University of New York , 365 5th Avenue, New York, NY 10016, USA; Department of Physics and Astronomy, Hunter College, City University of New York , 695 Park Avenue, New York, NY 10065, USADepartment of Astronomy & Astrophysics , UC San Diego, La Jolla, CA, USANASA Goddard Space Flight Center , Exoplanets and Stellar Astrophysics Laboratory, Code 667, Greenbelt, MD 20771, USABackyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9Backyard Worlds: Planet 9We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine-learning tool, named 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 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.https://doi.org/10.3847/1538-3881/ad77d2Brown dwarfsSubdwarf starsLow mass stars
spellingShingle Hunter Brooks
Dan Caselden
J. Davy Kirkpatrick
Yadukrishna Raghu
Charles A. Elachi
Jake Grigorian
Asa Trek
Andrew Washburn
Hiro Higashimura
Aaron M. Meisner
Adam C. Schneider
Jacqueline K. Faherty
Federico Marocco
Christopher R. Gelino
Jonathan Gagné
Thomas P. Bickle
Shih-Yun Tang
Austin Rothermich
Adam J. Burgasser
Marc J. Kuchner
Paul Beaulieu
John Bell
Guillaume Colin
Giovanni Colombo
Alexandru Dereveanco
Deiby Pozo Flores
Konstantin Glebov
Leopold Gramaize
Les Hamlet
Ken Hinckley
Martin Kabatnik
Frank Kiwy
David W. Martin
Raúl F. Palma Méndez
Billy Pendrill
Lizzeth Ruiz
John Sanchez
Arttu Sainio
Jörg Schümann
Manfred Schonau
Christopher Tanner
Nikolaj Stevnbak
Andres Stenner
Melina Thévenot
Vinod Thakur
Nikita V. Voloshin
Zbigniew Wȩdracki
The Backyard Worlds: Planet 9 Collaboration
Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
The Astronomical Journal
Brown dwarfs
Subdwarf stars
Low mass stars
title Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
title_full Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
title_fullStr Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
title_full_unstemmed Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
title_short Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques
title_sort discovery of 118 new ultracool dwarf candidates using machine learning techniques
topic Brown dwarfs
Subdwarf stars
Low mass stars
url https://doi.org/10.3847/1538-3881/ad77d2
work_keys_str_mv AT hunterbrooks discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT dancaselden discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT jdavykirkpatrick discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT yadukrishnaraghu discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT charlesaelachi discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT jakegrigorian discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT asatrek discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT andrewwashburn discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT hirohigashimura discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT aaronmmeisner discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT adamcschneider discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT jacquelinekfaherty discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT federicomarocco discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT christopherrgelino discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT jonathangagne discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT thomaspbickle discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT shihyuntang discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT austinrothermich discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT adamjburgasser discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT marcjkuchner discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT paulbeaulieu discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT johnbell discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT guillaumecolin discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT giovannicolombo discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT alexandrudereveanco discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT deibypozoflores discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT konstantinglebov discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT leopoldgramaize discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT leshamlet discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT kenhinckley discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT martinkabatnik discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT frankkiwy discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT davidwmartin discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT raulfpalmamendez discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT billypendrill discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT lizzethruiz discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT johnsanchez discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT arttusainio discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT jorgschumann discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT manfredschonau discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT christophertanner discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT nikolajstevnbak discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT andresstenner discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT melinathevenot discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT vinodthakur discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT nikitavvoloshin discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT zbigniewwedracki discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques
AT thebackyardworldsplanet9collaboration discoveryof118newultracooldwarfcandidatesusingmachinelearningtechniques