The PyCBC search for gravitational waves from compact binary coalescence

Abstract

Abstract. We describe the PyCBC search for gravitational waves from compactobject binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced 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.

Binary Black Hole Mergers in the First Advanced LIGO Observing Run

“…Two different, largely independent, analyses have been implemented to search for stellar-mass BBH signals in the data of O1: PyCBC [2][3][4] and GstLAL [5][6][7]. Both these analyses employ matched filtering [52][53][54][55][56][57][58][59][60] with waveforms given by models based on general relativity [8,9] to search for gravitational waves from binary neutron stars, BBHs, and neutron star-black hole binaries.…”

“…The average noise power spectral density of the LIGO detectors was measured over the period September 12 to September 26, 2015. The harmonic mean of these noise spectra from the two detectors was used to place a single template bank that was employed for the duration of the search [3].…”

“…[2][3][4], and the configuration used to analyze the first 16 days of O1 data, containing GW150914, is described in Ref. [44].…”

“…The search was performed using two independently implemented analyses, referred to as PyCBC [2][3][4] and GstLAL [5][6][7]. These analyses use a common set of template waveforms [8][9][10] but differ in their implementations of matched filtering [11,12], their use of detector data-quality information [13], the techniques used to mitigate the effect of non-Gaussian noise transients in the detector [5,14], and the methods for estimating the noise background of the search [3,15]. We obtain results that are consistent between the two analyses.…”

Accurate inspiral-merger-ringdown gravitational waveforms for nonspinning black-hole binaries including the effect of subdominant modes

“…The most sensitive GW detection pipelines use the technique of matched filtering to detect GW signals from binary black holes [6,7], which involves cross-correlating the data with theoretical templates of expected signals. Post detection, the physical and astrophysical properties of the GW source are inferred by comparing the data with theoretical signal templates, by means of Bayesian inference [8].…”