Swift follow-up of gravitational wave triggers: results from the first aLIGO run and optimisation for the future
P.A. Evans, J.A. Kennea, D.M. Palmer, M. Bilicki, J.P. Osborne, P.T., O'Brien, N.R. Tanvir, A.Y. Lien, S.D. Barthelmy, D. N. Burrows, S. Campana,, S.B. Cenko, V. D'Elia, N. Gehrels, F. E. Marshall, K.L. Page, M.Perri, B., Sbarufatti, M.H. Siegel, G. Tagliaferri, E. Troja

TL;DR
This paper discusses the Swift follow-up observations of gravitational wave triggers from the first aLIGO run, analyzes the challenges of future GW detections, and proposes methods to optimize electromagnetic follow-up using galaxy catalogues.
Contribution
It introduces strategies for improving follow-up observations of GW events, emphasizing the use of galaxy catalogues like 2MPZ for better prioritization in future runs.
Findings
No X-ray sources associated with GW triggers were identified.
2MPZ galaxy catalogue is highly suitable for follow-up optimization.
Challenges of increased GW sensitivity and distance estimation are discussed.
Abstract
During its first observing run, in late 2015, the advanced LIGO facility announced 3 gravitational wave (GW) triggers to electromagnetic follow-up partners. Two of these have since been confirmed as being of astrophysical origin: both are binary black hole mergers at ~500 Mpc; the other trigger was later found not to be astrophysical. In this paper we report on the Swift follow up observations of the second and third triggers, including details of 21 X-ray sources detected; none of which can be associated with the GW event. We also consider the challenges that the next GW observing run will bring as the sensitivity and hence typical distance of GW events will increase. We discuss how to effectively use galaxy catalogues to prioritise areas for follow up, especially in the presence of distance estimates from the GW data. We also consider two galaxy catalogues and suggest that the high…
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.
