The PyCBC search for gravitational waves from compact binary coalescence

By S. Usman, Alexander H. Nitz, Ian Harry, C. Biwer, Duncan A. Brown, M. Cabero, C. Capano, T. D. Canton, T. Dent, Stephen Fairhurst and 11 more. 2015

555 citations recorded by the source corpus.

We describe the PyCBC search for gravitational waves from compact-object binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) observing run and unambiguously identified two black hole binary mergers, GW150914 and GW151226. At its core, the PyCBC search performs a matched-filter search for binary merger signals using a bank of gravitational-wave template waveforms. We provide a complete description of the search pipeline including the steps used to mitigate the effects of noise transients in the data, identify candidate events and measure their statistical significance. The analysis is able to measure false-alarm rates as low as one per million years, required for confident detection of signals. Using data from initial LIGO's sixth science run, we show that the new analysis reduces the background noise in the search, giving a 30 % increase in sensitive volume for binary neutron star systems over previous searches.

Subfields: Astronomy and Astrophysics, Oceanography

View Paper: https://www.semanticscholar.org/paper/5a60dbbe8379605c0e2783a26f5f64d94d736a52

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Citations in the corpus

2-OGC: Open Gravitational-wave Catalog of Binary Mergers from Analysis of Public Advanced LIGO and Virgo Data (2019, methodology): “Each such analysis is generated by time-shifting the data from one detector by an amount greater than is astrophysically allowed by light travel time considerations Babak et al. (2013); Usman et al. (2016).”
GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run (2020, methodology): “A FAR is then computed for each of these candidate events by estimating the background noise distribution using timeshifted analyses similarly to cWB [29,126,165], triggers from LIGO Livingston being time shifted relative to LIGO Hanford by multiples of 0.”
Detecting Binary Compact-object Mergers with Gravitational Waves: Understanding and Improving the Sensitivity of the PyCBC Search (2017, methodology): “…search that identifies triggers with an estimate of the false alarm rate for rapid follow-up (Nitz et al. 2017a), and an offline search that reprocesses the data with additional detector data-quality information and provides the final statement of candidate significance (Usman et al. 2016).”
Reproducing GW150914: The First Observation of Gravitational Waves From a Binary Black Hole Merger (2020, methodology): “5 Gb HDF5 file that contains the triggers found in coincidence between the LIGO detectors, and the search background estimated using the time-slide method.(7,8) We have archived a compressed version of this HDF5 file on the IEEE DataPort server.”
Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo (2019, unknown): “• search-oriented software such as pycbc [149,150], GstLAL [174] and Coherent Waveburst (cWB) [154];”
GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs (2018, methodology): “For this reason, these artifacts are gated by the searches before analysis, using the procedure described in [8].”
4-OGC: Catalog of Gravitational Waves from Compact Binary Mergers (2021, methodology): “This procedure is the same as that used for the prior 3-OGC (Nitz et al. 2021a) and is implemented using the open-source PyCBC toolkit (Usman et al. 2016; Nitz et al. 2021d).”
The MBTA pipeline for detecting compact binary coalescences in the third LIGO–Virgo observing run (2020, unknown): “37 055002 [18] S. A. Usman et al. 2016 Class.”
Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-encoders (2017, result): “We show that compared with DRDAE, EDRDAE achieves lower mean square error (MSE) and higher overlap [9, 10].”
Tests of general relativity with the binary black hole signals from the LIGO-Virgo catalog GWTC-1 (2019, methodology): “Second, we choose to produce combined constraints only from events that were found in both modeled searches (PyCBC [45–47] and GstLAL [48, 49]) with a FAR of at most one per one-thousand years.”
THE RATE OF BINARY BLACK HOLE MERGERS INFERRED FROM ADVANCED LIGO OBSERVATIONS SURROUNDING GW150914 (2016, methodology): “Both the pycbc pipeline (Usman et al. 2016) and the gstlal pipeline (Messick et al. 2016) perform matched-filter searches for CBC signals using aligned-spin templates (Taracchini et al. 2014; Pürrer 2016) when searching the BBH parts of the CBC parameter space.”
Where Are LIGO’s Big Black Holes? (2017, unknown): “The choice for Mmin is motivated by the empirical lower mass gap, while Mmax and Mtot,max are set by the stellar binary matched-filter search, which defines stellarmass BBHs as those with source-frame total masses m1 +m2≤ 100M (Cannon et al. 2012; Usman et al. 2016; Abbott et al. 2016b).”