House, Lindsay R. http://orcid.org/0000-0002-1496-6514
Gebhardt, Karl http://orcid.org/0000-0002-8433-8185
Finkelstein, Keely http://orcid.org/0000-0003-0792-5877
Cooper, Erin Mentuch http://orcid.org/0000-0002-2307-0146
Davis, Dustin http://orcid.org/0000-0002-8925-9769
Ciardullo, Robin http://orcid.org/0000-0002-1328-0211
Farrow, Daniel J http://orcid.org/0000-0003-2575-0652
Finkelstein, Steven L. http://orcid.org/0000-0001-8519-1130
Gronwall, Caryl http://orcid.org/0000-0001-6842-2371
Jeong, Donghui http://orcid.org/0000-0002-8434-979X
Johnson, L. Clifton http://orcid.org/0000-0001-6421-0953
Liu, Chenxu http://orcid.org/0000-0001-5561-2010
Thomas, Benjamin P. http://orcid.org/0000-0002-0977-1974
Zeimann, Gregory http://orcid.org/0000-0003-2307-0629
Funding for this research was provided by:
National Science Foundation (2008793)
NASA ∣ Office of STEM Engagement (21-CSSFP21-0009)
National Science Foundation (DGE 2137420)
Article Title: Using Dark Energy Explorers and Machine Learning to Enhance the Hobby–Eberly Telescope Dark Energy Experiment
Journal Title: The Astrophysical Journal
Article Type: paper
Copyright Information: © 2023. The Author(s). Published by the American Astronomical Society.
Publication dates
Date Received: 2023-02-21
Date Accepted: 2023-04-13
Online publication date: 2023-06-13