Abstract

The first observing run of Advanced LIGO spanned 4 months, from 12 September 2015 to 19 January 2016, during which gravitational waves were directly detected from two binary black hole systems, namely GW150914 and GW151226. Confident detection of gravitational waves requires an understanding of instrumental transients and artifacts that can reduce the sensitivity of a search. Studies of the quality of the detector data yield insights into the cause of instrumental artifacts and data quality vetoes specific to a search are produced to mitigate the effects of problematic data. In this paper, the systematic removal of noisy data from analysis time is shown to improve the sensitivity of searches for compact binary coalescences. The output of the PyCBC pipeline, which is a python-based code package used to search for gravitational wave signals from compact binary coalescences, is used as a metric for improvement. GW150914 was a loud enough signal that removing noisy data did not improve its significance. However, the removal of data with excess noise decreased the false alarm rate of GW151226 by more than two orders of magnitude, from 1 in 770 yr to less than 1 in 186 000 yr.

Highlights

  • The Advanced Laser Interferometer Gravitational-Wave Observatory is comprised of two dual-recycled Michelson interferometers [1] located in Livingston, LA (L1) and Hanford, WA (H1)

  • The VT ratios are calculated at both the 1 per 100 yr and the 1 per 1000 yr levels. These significance levels are expressed as inverse false alarm rates (IFAR)

  • The actual gravitational wave signals discovered in the PyCBC search, GW150914 and GW151226, were part of a full search that was broken into 3 bins but reported as a single table of results

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Summary

Introduction

The Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO) is comprised of two dual-recycled Michelson interferometers [1] located in Livingston, LA (L1) and Hanford, WA (H1). A primary goal of this observing run was the detection of gravitational waves from compact binary coalescences (CBC) [2] This goal was achieved with the detections of GW150914 and GW151226, both signals from binary black hole systems, which marked the first direct detections of gravitational waves [3, 4]. Throughout the observing run, noisy data were identified in the form of data quality (DQ) vetoes to ensure that the analysis pipelines did not analyze data known to be contaminated with excess noise [15].

Data selection
The PyCBC search pipeline
Data quality vetoes
Measuring the effects of data quality vetoes
Measuring search sensitivity
Comparing search backgrounds
Search sensitivity
Background distribution with no DQ
BNS bin
Limiting noise sources
Blip transients
Conclusions
Full Text
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