GCN Circular 25871
Subject
LIGO/Virgo S190930s: Identification of a GW compact binary merger candidate
Date
2019-09-30T14:07:14Z (5 years ago)
From
Olivier Minazzoli at LIGO Virgo Collaboration <olivier.minazzoli@ligo.org>
The LIGO Scientific Collaboration and the Virgo Collaboration report:
We identified the compact binary merger candidate S190930s during real-time
processing of data from LIGO Hanford Observatory (H1) and LIGO Livingston
Observatory (L1) at 2019-09-30 13:35:41.247 UTC (GPS time: 1253885759.247).
The candidate was found by the GstLAL [1], MBTAOnline [2], PyCBC Live [3],
and SPIIR [4] analysis pipelines.
S190930s is an event of interest because its false alarm rate, as estimated
by the online analysis, is 3e-09 Hz, or about one in 10 years. The event's
properties can be found at this URL:
https://gracedb.ligo.org/superevents/S190930s
The classification of the GW signal, in order of descending probability, is
MassGap (95%), Terrestrial (5%), BNS (<1%), BBH (<1%), or NSBH (<1%).
Assuming the candidate is astrophysical in origin, there is strong evidence
against the lighter compact object having a mass < 3 solar masses (HasNS:
<1%). 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 trigger
time. For the bayestar.fits.gz,0 sky map, the 90% credible region is 1998
deg2. Marginalized over the whole sky, the a posteriori luminosity distance
estimate is 752 +/- 224 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] Adams et al. CQG 33, 175012 (2016)
[3] Nitz et al. PRD 98, 024050 (2018)
[4] Qi Chu, PhD Thesis, The University of Western Australia (2017)
[5] Singer & Price PRD 93, 024013 (2016)