Impact of noise transients on gravitational-wave burst detection efficiency of the BayesWave pipeline with multi-detector networks
arXiv:2403.16837 · doi:10.1103/PhysRevD.109.082002
Abstract
Detection confidence of the source-agnostic gravitational-wave burst search pipeline BayesWave is quantified by the log signal-versus-glitch Bayes factor, . A recent study shows that increases with the number of detectors. However, the increasing frequency of non-Gaussian noise transients (glitches) in expanded detector networks is not accounted for in the study. Glitches can mimic or mask burst signals resulting in false alarm detections, consequently reducing detection confidence. This paper an empirical study on the impact of false alarms on the overall performance of BayesWave, with expanded detector networks. The noise background of BayesWave for the Hanford-Livingston (HL, two-detector) and Hanford-Livingston-Virgo (HLV, three-detector) networks are measured using a set of non-astrophysical background triggers from the first half of Advanced LIGO and Advanced Virgo's Third Observing Run (O3a). Efficiency curves are constructed by combining of simulated binary black hole signals with the background measurements, to characterize BayesWave's detection efficiency as a function of the per-trigger false alarm probability. The HL and HLV network efficiency curves are shown to be similar. A separate analysis finds that detection significance of O3 gravitational-wave candidates as measured by BayesWave are also comparable for the HL and HLV networks. Consistent results from the two independent analyses suggests that the overall burst detection performance of BayesWave does not improve with the addition of Virgo at O3a sensitivity, because the increased false alarm probability offsets the advantage of higher .
arXiv comment16 pages, 8 figures
References in corpus (71)
- Advanced Virgo: a 2nd generation interferometric gravitational wave detector
- GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs
- Advanced LIGO
- GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
- GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run
- LIGO: The Laser Interferometer Gravitational-Wave Observatory
- Frequency-domain gravitational waves from non-precessing black-hole binaries. II. A phenomenological model for the advanced detector era
- Interferometer design of the KAGRA gravitational wave detector
- Detector configuration of KAGRA - the Japanese cryogenic gravitational-wave detector
- Frequency-domain gravitational waves from non-precessing black-hole binaries. I. New numerical waveforms and anatomy of the signal
- Detection, Measurement and Gravitational Radiation
- The PyCBC search for gravitational waves from compact binary coalescence
- FINDCHIRP: an algorithm for detection of gravitational waves from inspiraling compact binaries
- Gravitational radiation from cosmic (super)strings: bursts, stochastic background, and observational windows
- GW150914: First results from the search for binary black hole coalescence with Advanced LIGO
- Effective-one-body model for black-hole binaries with generic mass ratios and spins
- Method for detection and reconstruction of gravitational wave transients with networks of advanced detectors
- BayesWave: Bayesian Inference for Gravitational Wave Bursts and Instrument Glitches
- A guide to LIGO-Virgo detector noise and extraction of transient gravitational-wave signals
- Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science
- Open data from the third observing run of LIGO, Virgo, KAGRA and GEO
- Networks of gravitational wave detectors and three figures of merit
- Coherent method for detection of gravitational wave bursts
- BayesLine: Bayesian Inference for Spectral Estimation of Gravitational Wave Detector Noise
- Magnetars: Properties, Origin and Evolution
- Constraints on cosmic strings using data from the third Advanced LIGO-Virgo observing run
- Observing gravitational-wave transient GW150914 with minimal assumptions
- The BayesWave analysis pipeline in the era of gravitational wave observations
- All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run
- Detecting binary neutron star systems with spin in advanced gravitational-wave detectors
- An information-theoretic approach to the gravitational-wave burst detection problem
- X-Pipeline: An analysis package for autonomous gravitational-wave burst searches
- Machine-learning non-stationary noise out of gravitational wave detectors
- Blip glitches in Advanced LIGO data
- All-sky search for gravitational-wave bursts in the first joint LIGO-GEO-Virgo run
- GEO 600 and the GEO-HF upgrade program: successes and challenges
- Improving the sensitivity of a search for coalescing binary black holes with non-precessing spins in gravitational wave data
- An Optically Targeted Search for Gravitational Waves emitted by Core-Collapse Supernovae during the First and Second Observing Runs of Advanced LIGO and Advanced Virgo
- Improving the Sensitivity of Advanced LIGO Using Noise Subtraction
- Reducing Scattered Light in LIGO's Third Observing Run
- Improving astrophysical parameter estimation via offline noise subtraction for Advanced LIGO
- An effectual template bank for the detection of gravitational waves from inspiralling compact binaries with generic spins
- All-sky search for short gravitational-wave bursts in the first Advanced LIGO run
- Coherent WaveBurst, a pipeline for unmodeled gravitational-wave data analysis
- The LSC Glitch Group : Monitoring Noise Transients during the fifth LIGO Science Run
- Omicron: a tool to characterize transient noise in gravitational-wave detectors
- All-sky search for short gravitational-wave bursts in the second Advanced LIGO and Advanced Virgo run
- The characterization of Virgo data and its impact on gravitational-wave searches
- Noise Reduction in Gravitational-wave Data via Deep Learning
- All-sky search for short gravitational-wave bursts in the third Advanced LIGO and Advanced Virgo run
- Improving the Data Quality of Advanced LIGO Based on Early Engineering Run Results
- A Bayesian Approach to the Detection Problem in Gravitational Wave Astronomy
- Subtracting glitches from gravitational-wave detector data during the third observing run
- Parameter Estimation and Model Selection of Gravitational Wave Signals Contaminated by Transient Detector Noise Glitches
- Efficient Gravitational-wave Glitch Identification from Environmental Data Through Machine Learning
- Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications
- Search for transient gravitational wave signals associated with magnetar bursts during Advanced LIGO's second observing run
- Parameter estimation for gravitational-wave bursts with the BayesWave pipeline
- On the background estimation by time slides in a network of gravitational wave detectors
- Search for nonlinear memory from subsolar mass compact binary mergers
- Regression of Environmental Noise in LIGO Data
- Enabling high confidence detections of gravitational-wave bursts
- Leveraging waveform complexity for confident detection of gravitational waves
- Global Feed-Forward Vibration Isolation in a km scale Interferometer
- Increasing LIGO sensitivity by feedforward subtraction of auxiliary length control noise
- Replica Monte Carlo Simulation (Revisited)
- Reconstructing gravitational wave signals from binary black hole mergers with minimal assumptions
- Search for gravitational-wave bursts in the third Advanced LIGO-Virgo run with coherent WaveBurst enhanced by Machine Learning
- Utilizing Gaussian mixture models in all-sky searches for short-duration gravitational wave bursts
- Enhancing gravitational-wave burst detection confidence in expanded detector networks with the BayesWave pipeline
- Gravitational Waves from Gamma-Ray Pulsar Glitches