Glitch veto based on unphysical gravitational wave binary inspiral templates

Abstract

Transient signals arising from instrumental or environmental factors, commonly referred to as glitches, constitute the predominant background of false alarms in gravitational wave searches with ground-based detectors. Therefore, effective data analysis methods for vetoing glitch-induced false alarms are crucial to enhancing the sensitivity of a search. We present a veto method for glitches that impact matched filtering-based searches for binary inspiral signals. The veto uses unphysical sectors in the space of chirp time parameters as well as an unphysical extension including negative chirp times to efficiently segregate glitches from gravitational wave signals in data from a single detector. Inhabited predominantly by glitches but nearly depopulated of genuine gravitational wave signals, these unphysical sectors can be efficiently explored using Particle Swarm Optimization. In a test carried out on data taken from both LIGO detectors spanning multiple observation runs, the veto was able to reject $99.9\%$ of glitches with no loss of signals detected with signal-to-noise ratio $\ge 9.0$ and total detector frame mass $\le 80$ $M_{\odot }$. Our results show that extending a matched filter search to unphysical parts of a signal parameter space promises to be an effective strategy for mitigating glitches.

Accepted version; Fig.2 replaced with corrected version; 18 pages, 12 figures

References in corpus (33)

• Observation of Gravitational Waves from a Binary Black Hole Merger
• GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral
• GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs
• GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run
• Gravitational Waves from Mergin Compact Binaries: How Accurately Can One Extract the Binary's Parameters from the Inspiral Waveform?
• LIGO: The Laser Interferometer Gravitational-Wave Observatory
• The PyCBC search for gravitational waves from compact binary coalescence
• Comparison of post-Newtonian templates for compact binary inspiral signals in gravitational-wave detectors
• KAGRA: 2.5 Generation Interferometric Gravitational Wave Detector
• Gravitational-Radiation Damping of Compact Binary Systems to Second Post-Newtonian order
• BayesWave: Bayesian Inference for Gravitational Wave Bursts and Instrument Glitches
• Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data
• A chi-squared time-frequency discriminator for gravitational wave detection
• 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
• IMRPhenomXHM: A multi-mode frequency-domain model for the gravitational wave signal from non-precessing black-hole binaries
• Setting the cornerstone for the IMRPhenomX family of models for gravitational waves from compact binaries: The dominant harmonic for non-precessing quasi-circular black holes
• IndIGO and LIGO-India: Scope and Plans for Gravitational Wave Research and Precision Metrology in India
• Glitch Classification and Clustering for LIGO with Deep Transfer Learning
• Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO
• The MBTA Pipeline for Detecting Compact Binary Coalescences in the Third LIGO-Virgo Observing Run
• Effects of Data Quality Vetoes on a Search for Compact Binary Coalescences in Advanced LIGO's First Observing Run
• Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data
• Mitigation of the instrumental noise transient in gravitational-wave data surrounding GW170817
• A targeted coherent search for gravitational waves from compact binary coalescences
• Distinguishing short duration noise transients in LIGO data to improve the PyCBC search for gravitational waves from high mass binary black hole mergers
• Subtracting glitches from gravitational-wave detector data during the third observing run
• Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications
• Parameterised population models of transient non-Gaussian noise in the LIGO gravitational-wave detectors
• Transient glitch mitigation in Advanced LIGO data with $\text{glitschen}$
• Performance of Particle Swarm Optimization on the fully-coherent all-sky search for gravitational waves from compact binary coalescences
• Glitch subtraction from gravitational wave data using adaptive spline fitting
• Towards a real-time fully-coherent all-sky search for gravitational waves from compact binary coalescences using particle swarm optimization