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GCN Circular 25829

Subject
LIGO/Virgo S190924h: Identification of a GW compact binary merger candidate
Date
2019-09-24T03:14:19Z (5 years ago)
From
Geoffrey Mo at LIGO <geoffrey.mo@ligo.org>
The LIGO Scientific Collaboration and the Virgo Collaboration report:

We identified the compact binary merger candidate S190924h during
real-time processing of data from LIGO Hanford Observatory (H1), LIGO
Livingston Observatory (L1), and Virgo Observatory (V1) at 2019-09-24
02:18:46.847 UTC (GPS time: 1253326744.847). The candidate was found
by the GstLAL [1], PyCBC Live [2], MBTAOnline [3], and SPIIR [4]
analysis pipelines.

S190924h is an event of interest because its false alarm rate, as
estimated by the online analysis, is 8.9e-19 Hz, or about one in 1e11
years. The event's properties can be found at this URL:
https://gracedb.ligo.org/superevents/S190924h

The classification of the GW signal, in order of descending
probability, is MassGap (>99%), Terrestrial (<1%), BNS (<1%), BBH
(<1%), or NSBH (<1%).

Assuming the candidate is astrophysical in origin, there is
indeterminate evidence for the lighter compact object having a mass <
3 solar masses (HasNS: 30%). Using the masses and spins inferred from
the signal, there is strong evidence against matter outside the final
compact object (HasRemnant: <1%).

One sky map is available at this time and can be retrieved from the
GraceDB event page:
 * bayestar.fits.gz,0, an updated localization generated by BAYESTAR
[5], distributed via GCN notice about 6 minutes after the candidate

For the bayestar.fits.gz,0 sky map, the 90% credible region is 515
deg2. Marginalized over the whole sky, the a posteriori luminosity
distance estimate is 514 +/- 132 Mpc (a posteriori mean +/- standard
deviation).

For further information about analysis methodology and the contents of
this alert, refer to the LIGO/Virgo Public Alerts User Guide
<https://emfollow.docs.ligo.org/userguide/>.

 [1] Messick et al. PRD 95, 042001 (2017)
 [2] Nitz et al. PRD 98, 024050 (2018)
 [3] Adams et al. CQG 33, 175012 (2016)
 [4] Qi Chu, PhD Thesis, The University of Western Australia (2017)
 [5] Singer & Price PRD 93, 024013 (2016)
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