FINDCHIRP: an algorithm for detection of gravitational waves from inspiraling compact binaries

By B. Allen, W. Anderson, Patrick R. Brady, Duncan A. Brown, Jolien D. E. Creighton. 2005

429 citations recorded by the source corpus.

Matched-filter searches for gravitational waves from coalescing compact binaries by the LIGO Scientific Collaboration use the FINDCHIRP algorithm: an implementation of the optimal filter with innovations to account for unknown signal parameters and to improve performance on detector data that has nonstationary and non-Gaussian artifacts. We provide details on the FINDCHIRP algorithm as used in the search for subsolar mass binaries, binary neutron stars, neutron starblack hole binaries, and binary black holes.

Subfields: Astronomy and Astrophysics, Oceanography

View Paper: https://www.semanticscholar.org/paper/016e7db0d29bbec929b590fd1cdbe99bfc773ed0

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Citations in the corpus

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): “This analysis performs direct matched filtering of the data against a bank of template waveforms to calculate the signal-to-noise ratio (SNR) for each combination of detector, template waveform, and coalescence time [70].”
THE RATE OF BINARY BLACK HOLE MERGERS INFERRED FROM ADVANCED LIGO OBSERVATIONS SURROUNDING GW150914 (2016, background): “In these searches, single-detector triggers are recorded at maxima of the signal-to-noise ratio (S/N) time series for each template (Allen et al. 2012); coincident search triggers are formed when pairs of triggers, one from each detector, occur in the same template with a time difference of ±15 ms…”
Binary Black Hole Mergers in the First Advanced LIGO Observing Run (2016, methodology): “The matched-filter SNR ρ for each template waveform and each detector’s data as a function of time is calculated according to [11,208]”
Search for New Physics with Atoms and Molecules (2017, methodology): “…sophisticated data analysis techniques to search for similar correlated “burst” signals from a worldwide network of gravitational wave detectors (Allen et al., 2012; Anderson et al., 2001), and the GNOME collaboration has demonstrated that these data analy- sis techniques can be adapted to…”
Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue (2020, methodology): “Following Allen et al. (2012), segments are Tukey windowed with a 0.4 s roll-off to suppress spectral leakage (Abbott et al. 2019a), before computing their one-sided power spectra.”
The MBTA pipeline for detecting compact binary coalescences in the third LIGO–Virgo observing run (2020, neutral): “33 21 [19] B. Allen et al. 2012 Phys.”
GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run (2021, methodology): “The GW data until the end of third observing run (O3) have been made available to the public by the LVC.”
Multi-messenger observations of a binary neutron star merger (2017, background): “…models(Blanchet et al. 1995, 2004, 2006; Bohé et al. 2013) to construct a matchedfilter search(Sathyaprakash & Dhurandhar 1991; Cutler et al. 1993; Allen et al. 2012) for gravitational waves from the coalescence of compact-object binary systems in the (detector frame) total mass range M2 500 – .”
1-OGC: The First Open Gravitational-wave Catalog of Binary Mergers from Analysis of Public Advanced LIGO Data (2018, methodology): “To search for gravitational waves from compact-object mergers, we use matched filtering(Allen et al. 2012) implemented in the open-source PyCBC library(Dal Canton et al. 2014; Usman et al. 2016; Nitz et al. 2018c).”
Challenges and opportunities of gravitational-wave searches at MHz to GHz frequencies (2020, background): “• The most efficient signal-to-noise ratio metric for broadband detection of transient sources uses matched-filtering [13,15,18]:”
Detecting Binary Compact-object Mergers with Gravitational Waves: Understanding and Improving the Sensitivity of the PyCBC Search (2017, methodology): “…PyCBC binary-merger search (Dal Canton et al. 2014; Usman et al. 2016; Nitz et al. 2017b) uses matched filtering (Wiener 1949; Cutler et al. 1993; Allen et al. 2012) with accurate models of gravitational waveforms (Blanchet 2002; Buonanno & Damour 1999; Faye et al. 2012; Taracchini et al. 2014;…”