Constraints on the Physical Properties of GW190814 through Simulations based on DECam Follow-up Observations by the Dark Energy Survey
R. Morgan, M. Soares-Santos, J. Annis, K. Herner, A. Garcia, A., Palmese, A. Drlica-Wagner, R. Kessler, J. Garcia-Bellido, T. G. Bachmann N., Sherman, S. Allam, K. Bechtol, C. R. Bom, D. Brout, R. E. Butler, M. Butner,, R. Cartier, H. Chen, C. Conselice, E. Cook, T. M. Davis

TL;DR
This study uses DECam follow-up observations and simulations to constrain the physical properties of the GW190814 merger, ruling out certain kilonova configurations and demonstrating effective background reduction for future detections.
Contribution
It introduces a systematic approach combining observational data and simulations to constrain kilonova properties and improve electromagnetic counterpart identification for gravitational wave events.
Findings
Disfavors kilonova ejecta mass > 0.07 solar masses at 2σ
Rules out lanthanide abundance < 10^{-8.56}
Achieves 95% background reduction for future GW-EM associations
Abstract
On 14 August 2019, the LIGO and Virgo Collaborations detected gravitational waves from a black hole and a 2.6 solar mass compact object, possibly the first neutron star -- black hole (NSBH) merger. In search of an optical counterpart, the Dark Energy Survey (DES) obtained deep imaging of the entire 90 percent confidence level localization area with Blanco/DECam 0, 1, 2, 3, 6, and 16 nights after the merger. Objects with varying brightness were detected by the DES Pipeline and we systematically reduced the candidate counterparts through catalog matching, light curve properties, host-galaxy photometric redshifts, SOAR spectroscopic follow-up observations, and machine-learning-based photometric classification. All candidates were rejected as counterparts to the merger. To quantify the sensitivity of our search, we applied our selection criteria to full light curve simulations of supernovae…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
