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A New Search Pipeline for Compact Binary Mergers: Results for Binary Black Holes in the First Observing Run of Advanced LIGO

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arxiv 1902.10341 v2 pith:EIMKXETG submitted 2019-02-27 astro-ph.IM astro-ph.HEgr-qc

classification astro-ph.IMastro-ph.HEgr-qc
keywords pipelinebinarydataligostagesadvancedcompactfirst
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we report on the construction of a new and independent pipeline for analyzing the public data from the first observing run of advanced LIGO for mergers of compact binary systems. The pipeline incorporates different techniques and makes independent implementation choices in all its stages including the search design, the method to construct template banks, the automatic routines to detect bad data segments ("glitches") and to insulate good data from them, the procedure to account for the non-stationary nature of the detector noise, the signal-quality vetoes at the single-detector level and the methods to combine results from multiple detectors. Our pipeline enabled us to identify a new binary black-hole merger GW151216 in the public LIGO data. This paper serves as a bird's eye view of the pipeline's important stages. Full details and derivations underlying the various stages will appear in accompanying papers.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation

    gr-qc 2025-07 conditional novelty 6.0 of 10

    A machine learning classifier trained on the extended noise environment around gravitational wave candidates improves search sensitivity for heavy, unequal-mass black hole mergers by up to roughly 20 percent.

  2. Searching for intermediate mass ratio binary black hole mergers in the third observing run of LIGO-Virgo-KAGRA

    gr-qc 2025-07 conditional novelty 6.0 of 10

    No confident intermediate mass ratio inspirals are found in LIGO-Virgo-KAGRA O3 data, yielding 90% upper limits of roughly 30-1000 Gpc^-3 yr^-1 on their local merger rate and showing higher modes boost search volume b...

  3. Searching for binary black hole mergers with deep learning in Advanced LIGO's third observing run

    gr-qc 2025-12 conditional novelty 5.0 of 10

    A hybrid matched-filter/deep-learning pipeline recovers 31 known O3 events and reports a new tentative high-mass candidate, with sensitivity comparable to existing searches only for chirp masses above 25 solar masses.

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