Optimal Follow-up of Gravitational-wave Events with the UltraViolet EXplorer (UVEX)
Creators
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1.
Goddard Space Flight Center
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2.
University of Maryland, College Park
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3.
University of Minnesota
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4.
Vanderbilt University
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Fisk University
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University of Ouagadougou
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Astrophysique Relativiste, Théories, Expériences, Métrologie, Instrumentation, Signaux
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California Institute of Technology
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Johns Hopkins University
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Space Telescope Science Institute
Abstract
The UltraViolet EXplorer (UVEX) is a wide-field ultraviolet space telescope selected as a NASA Medium-Class Explorer mission for launch in 2030. UVEX will undertake deep, cadenced surveys of the entire sky to probe low mass galaxies and explore the ultraviolet (UV) time-domain sky, and it will carry the first rapidly deployable UV spectroscopic capability for a broad range of science applications. One of UVEX’s prime objectives is to follow up gravitational wave (GW) binary neutron star mergers as targets of opportunity (ToOs), rapidly scanning across their localization regions to search for their kilonova (KN) counterparts. Early-time multiband ultraviolet light curves of KNe are key to explaining the interplay between jet and ejecta in binary neutron star mergers. Owing to high Galactic extinction in the ultraviolet and the variation of GW distance estimates over the sky, the sensitivity to kilonovae can vary significantly across the GW localization and even across the footprint of a single image given UVEX’s large field of view. Good ToO observing strategies to trade off between area and depth are neither simple nor obvious. We present an optimal strategy for GW follow-up with UVEX in which exposure time is adjusted dynamically for each field individually to maximize the overall probability of detection. We model the scheduling problem using the expressive and powerful mathematical framework of mixed integer linear programming (MILP), and employ a state-of-the-art MILP solver to automatically generate observing plan timelines that achieve high probabilities of kilonova detection. We have implemented this strategy in an open-source astronomical scheduling software package called Multi-Mission Multi-Messenger Observation Planning Toolkit, on GitHub at https://github.com/m4opt/m4opt.
Copyright and License
© 2025. The Author(s). Published by IOP Publishing Ltd on behalf of the Astronomical Society of the Pacific (ASP). Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 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
This work was performed in part at the Aspen Center for Physics, which is supported by the U.S. National Science Foundation (NSF) grant PHY-2210452.
This work used Expanse at the San Diego Supercomputing Center (SDSC) and Delta at the National Center for Supercomputing Applications (NCSA) through allocation AST200029, “Towards a complete catalog of variable sources to support efficient searches for compact binary mergers and their products,” from the Advanced Cyberinfrastructure Coordination Ecosystem: Services and Support (ACCESS) program, which is supported by NSF grants #2138259, #2138286, #2138307, #2137603, and #2138296.
S.C.L. and M.W.C. acknowledge support from NSF with grant Nos. PHY-2308862 and PHY-2117997.
We thank Steve Crawford at NASA Headquarters for help and support with the NASA software release process.
The code, data, and software environment to reproduce the figures and tables in this paper are available from Zenodo (Singer 2025).
This is LIGO document P2500008-v3.
Software References
astropy (Astropy Collaboration et al. 2013, 2018), astroquery (Ginsburg et al. 2019), dust_extinction (Gordon 2024), dustmaps (Green 2018), healpix (Górski et al. 2005), healpy (Zonca et al. 2019), ligo.skymap (Singer & Price 2016; Singer et al. 2016a, 2016b), matplotlib (Hunter 2007), m4opt (Singer et al. 2025), numpy (Harris et al. 2020), regions (Bradley et al. 2022), scipy (Virtanen et al. 2020), spiceypy (Annex et al. 2020), sympy (Meurer et al. 2017), synphot (STScI Development Team 2018).
Files
10.1088_1538-3873_adcfc6.pdf
Additional details
Related works
- Is new version of
- Discussion Paper: arXiv:2502.17560 (arXiv)
- Is supplemented by
- Supplemental Material: https://iopscience.iop.org/article/10.1088/1538-3873/adcfc6/data (URL)
- Dataset: 10.5281/zenodo.15176276 (DOI)
- Software: https://github.com/m4opt/m4opt (URL)
Funding
- National Science Foundation
- PHY-2210452
- National Science Foundation
- PHY-2308862
- National Science Foundation
- PHY-2117997
- National Science Foundation
- 2138259
- National Science Foundation
- 2138286
- National Science Foundation
- 2138307
- National Science Foundation
- 2137603
- National Science Foundation
- 2138296
Dates
- Accepted
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2025-04-23
- Available
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2025-07-14Published
Caltech Custom Metadata
- Caltech groups
- Astronomy Department, LIGO, Space Radiation Laboratory, Division of Physics, Mathematics and Astronomy (PMA)
- Other Numbering System Name
- LIGO
- Other Numbering System Identifier
- P2500008-v3
- Publication Status
- Published