A Low Metallicity Massive Contact Binary Star System Candidate in WLM Identified by Hubble and James Webb Space Telescope Imaging
- Creators
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Gull, Maude1
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Weisz, Daniel R.1
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El-Badry, Kareem2
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Henneco, Jan3, 4
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Savino, Alessandro1
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Durbin, Meredith1
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Choi, Yumi5
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Cohen, Roger E.6
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Cole, Andrew A.7
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Correnti, Matteo8, 9
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Dalcanton, Julianne J.10, 11
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Gilbert, Karoline M.12, 13
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Goldman, Steven R.12
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Guhathakurta, Puragra14
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McQuinn, Kristen B. W.12, 6
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Newman, Max J. B.6
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Skillman, Evan D.15
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Williams, Benjamin F.11
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1.
University of California, Berkeley
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2.
California Institute of Technology
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3.
Heidelberg Institute for Theoretical Studies
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4.
Heidelberg University
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5.
NOIRLab
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6.
Rutgers, The State University of New Jersey
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7.
University of Tasmania
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8.
Astronomical Observatory of Rome
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9.
Agenzia Spaziale Italiana
- 10. Flatiron Institute
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11.
University of Washington
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12.
Space Telescope Science Institute
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13.
Johns Hopkins University
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14.
University of California, Santa Cruz
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15.
University of Minnesota
Abstract
We present archival Hubble Space Telescope (HST) and JWST ultraviolet through near-infrared time series photometric observations of a massive minimal-contact binary candidate in the metal-poor galaxy Wolf–Lundmark–Melotte (Z = 0.14Z⊙). This discovery marks the lowest metallicity contact binary candidate observed to date. We determine the nature of the two stars in the binary by using the eclipsing binary modeling software PHysics Of Eclipsing BinariEs (PHOEBE) to train a neural network to fit our observed panchromatic multiepoch photometry. The best-fit model consists of two hot main-sequence stars (T₁=29800₋₁₇₀₀⁺²³⁰⁰ K, M₁=16₋₃⁺² M⊙, and T₂=18000₋₅₀₀₀⁺⁵⁰⁰⁰ K, M₂=7₋₃⁺⁵ M⊙). We discuss plausible evolutionary paths for the system, and suggest the system is likely to be currently in a contact phase. Future spectroscopy will help to further narrow down evolutionary pathways. This work showcases a novel use of data of JWST and HST imaging originally taken to characterize RR Lyrae. We expect time series imaging from LSST, BlackGEM, etc. to uncover similar types of objects in nearby galaxies.
Copyright and License
© 2025. The Author(s). Published by the American Astronomical Society.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Acknowledgement
M.G. thanks the referee for helpful discussions, feedback, or comments. M.G. thanks Sabrina Drammis, Jessica Lu, and Jacqueline Blaum for the helpful discussion. M.G. acknowledges support of the UC Berkeley Cranor Fellowship and the Schweizerische Studienstiftung. Support for this work was provided by NASA through grants GO-15275, GO-15921, GO-16149, GO-16162, GO-16717, AR-15056, AR-16120, HST-HF2-51457.001-A, and JWST-DD-1334 from the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555.
This research used the Savio computational cluster resource provided by the Berkeley Research Computing program at the University of California, Berkeley (supported by the UC Berkeley Chancellor, Vice Chancellor for Research, and Chief Information Officer).
This work is based on photometric observations made with the NASA/ESA Hubble Space Telescope, obtained from the data archive at the Space Telescope Science Institute. STScI is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS 5-26555. The HST data presented in this article can be obtained from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute. The WLM-CB1 and WLM-CB1 UV observations analyzed can be accessed via doi:10.17909/v5pa-y253 and doi:10.17909/xxwx-ca38, respectively. The JWST data can also be obtained from the MAST. The observations are part of the ERS JWSTSTARS High Level Science product and can be accessed via D. Weisz (2024).
This work made extensive use of NASA's Astrophysics Data System Bibliographic Services.
Software References
astropy (Astropy Collaboration et al. 2013, 2018, 2022), astrML (J. Vanderplas et al. 2012), corner (D. Foreman-Mackey 2016), DOLPHOT (A. Dolphin 2016), matplotlib (J. D. Hunter 2007), numpy (C. R. Harris et al. 2020), MESA (B. Paxton et al. 2011, 2013, 2015, 2018, 2019), Optuna (T. Akiba et al. 2019), PHOEBE (A. Prša et al. 2016; M. Horvat et al. 2018; K. E. Conroy et al. 2020; D. Jones et al. 2020), pyphot, PyTorch (A. Paszke et al. 2019), UltraNest (J. Buchner 2021).
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Additional details
- University of California, Berkeley
- Cranor Fellowship -
- Swiss Study Foundation
- National Aeronautics and Space Administration
- GO-15275
- National Aeronautics and Space Administration
- GO-15921
- National Aeronautics and Space Administration
- GO-16149
- National Aeronautics and Space Administration
- GO-16162
- National Aeronautics and Space Administration
- GO-16717
- National Aeronautics and Space Administration
- AR-15056
- National Aeronautics and Space Administration
- AR-16120
- National Aeronautics and Space Administration
- HST-HF2-51457.001-A
- Space Telescope Science Institute
- JWST-DD-1334
- National Aeronautics and Space Administration
- NAS5-26555
- Accepted
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2025-04-04
- Available
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2025-06-03Published
- Caltech groups
- Astronomy Department, Division of Physics, Mathematics and Astronomy (PMA)
- Publication Status
- Published