The First Two Years of Electromagnetic Follow-Up with Advanced LIGO and Virgo Read on arXiv:1404.5623
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Catalog of simulated events and sky maps for two-detector, HL, 2015 configuration. This is the same configuration as the 2015, recoloured tab, except that the simulated detector noise is Gaussian. See also ASCII tables of simulated signals, detections, and parameter-estimation accuracies in Machine Readable Table format.
The First Two Years of Electromagnetic Follow-Up with Advanced LIGO and Virgo Read on arXiv:1404.5623
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Catalog of simulated events and sky maps for three-detector, HLV, 2016 configuration. The simulated detector noise is Gaussian. See also ASCII tables of simulated signals and detections in Machine Readable Table format.
Parameter Estimation for Binary Neutron-Star Coalescences with Realistic Noise During the Advanced LIGO Era Read on arXiv:1411.6934
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Catalog of simulated events and sky maps for two-detector, HL, 2015 configuration. This is the same configuration as the 2015 tab, except that the simulated detector noise is data from initial LIGO's sixth science run, recoloured (filtered) to have the same PSD as the early Advanced LIGO configuration. See also ASCII tables of simulated signals, detections, and parameter-estimation accuracies in Machine Readable Table format.
The First Two Years of Electromagnetic Follow-Up with Advanced LIGO and Virgo
Singer et al. 2014arXiv:1404.5623 Berry et al. 2015
arXiv:1411.6934
This web page provides additional online material related to the paper "The First Two Years of Electromagnetic Follow-Up with Advanced LIGO and Virgo" and the follow-up paper "Parameter Estimation for Binary Neutron-Star Coalescences with Realistic Noise During the Advanced LIGO Era."
These papers predict the detection, sky-localization, and parameter-estimation capabilities of the Advanced LIGO and Virgo gravitational-wave detector network through two early two- and three-detector configurations. The data release comprises a database of simulated signals, recovered detections candidates, and posterior probability maps resulting from Bayesian parameter estimation.
These are LIGO documents LIGO-P1300187-v25 and LIGO-P1400232-v8.
Contact Leo Singer <leo.singer@ligo.org> for any questions.
Instructions
You can use the tables in the 2015, 2016, and 2015, recoloured tabs above to browse through all of the events and sky maps in the study. You can sort on any column by clicking its header, or show and hide columns using the Show/hide columns button above. You can also use this menu to switch the image previews between equatorial (RA, Dec) and geographic (longitude, latitude) coordinates with continent outlines.
Click any sky map thumbnail to open a larger version with a link to a FITS file representing the posterior in the HEALPix projection. The FITS files always use equatorial coordinates and the NESTED indexing scheme. For reading these files, the authors recommend the Python package Healpy or the official HEALPix C/
In WebGL capable browsers, there is also an option to show any sky map interactively in 3D.
Each table is also available in ASCII form in Machine Readable Table (CDS/VizieR) format. For reading these tables, the journal suggests several Machine Readable Table readers, but the authors also like Astropy's table I/O module.
Some other formats are also available:
| TAR archive of FITS files | 2015 (966 MB) | 2016 (796 MB) | 2015, recoloured (1.3 GB) |
|---|---|---|---|
| ASCII table of simulated signals | 2015 (63 KB) | 2016 (49 KB) | 2015, recoloured (35 kB) |
| ASCII table of detections | 2015 (54 KB) | 2016 (48 KB) | 2015, recoloured (34 kB) |
| ASCII table of all simulated signals, including those not detected | 2015 (4.5 MB) | 2016 (4.5 MB) | 2015, recoloured (3.8 MB) |
| Raw SQLite search pipeline output | 2015 (132 MB) | 2016 (2.7 GB) | 2015, recoloured (83.2 MB) |
Source codes
Here are some LIGO/Virgo source codes that were used to prepare this dataset:
- GSTLAL inspiral detection pipeline (source repository)
- LALSuite: LIGO Algorithm Library (source repository)
XLALSimInspiralSpinTaylorT4, waveform model (source code)XLALSimInspiralTaylorF2, detection templates (source code)- LALInference parameter-estimation library (source code)
- BAYESTAR rapid sky-localization code (source code)
All of the above are free and open source, released under the terms of the GNU General Public License.
This page uses MathJax, under the terms of the Apache License 2.0. It uses Bootstrap, the Simplex theme, Tablecloth.js, TableSorter, and Unveil.js, all of which are under the MIT License.