The PyCBC search for gravitational waves from compact binary coalescence
arXiv:1508.02357 · doi:10.1088/0264-9381/33/21/215004
Abstract
We describe the PyCBC search for gravitational waves from compact-object binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced LIGO observing run and unambiguously identified two black hole binary mergers, GW150914 and GW151226. At its core, the PyCBC search performs a matched-filter search for binary merger signals using a bank of gravitational-wave template waveforms. We provide a complete description of the search pipeline including the steps used to mitigate the effects of noise transients in the data, identify candidate events and measure their statistical significance. The analysis is able to measure false-alarm rates as low as one per million years, required for confident detection of signals. Using data from initial LIGO's sixth science run, we show that the new analysis reduces the background noise in the search, giving a 30% increase in sensitive volume for binary neutron star systems over previous searches.
29 pages, 7 figures, accepted by Classical and Quantum Gravity
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- The Design Strain Sensitivity of the Schenberg Spherical Resonant Antenna for Gravitational Waves
- Waveform systematics in identifying strongly gravitationally lensed gravitational waves: Posterior overlap method
- Pinpointing coalescing binary neutron star sources with the IGWN, including LIGO-Aundha
- A Case Study of On-the-Fly Wide-Field Radio Imaging Applied to the Gravitational-wave Event GW 151226
- A Unified for Gravitational Waves: Consistently Combining Information from Multiple Search Pipelines
- SciTokens: Demonstrating Capability-Based Access to Remote Scientific Data using HTCondor
- Sensitivity of spin-aligned searches for neutron star-black hole systems using future detectors
- Employing Deep Learning for Detection of Gravitational Waves from Compact Binary Coalescences
- Time delay interferometry with minimal null frequencies
- Convolutional Neural Networks for signal detection in real LIGO data
- Prospects for reconstructing the gravitational-wave signals from core-collapse supernovae with Advanced LIGO-Virgo and the BayesWave algorithm
- cDVGAN: One Flexible Model for Multi-class Gravitational Wave Signal and Glitch Generation
- Targeted Search for Gravitational Waves from Highly Spinning Light Compact Binaries
- Reconstruction of binary black hole harmonics in LIGO using deep learning
- New approach to template banks of gravitational waves with higher harmonics: Reducing matched-filtering cost by over an order of magnitude
- Optimizing the Placement of Numerical Relativity Simulations using a Mismatch Predicting Neural Network
- Binary Neutron Star Merger Search Pipeline Powered by Deep Learning
- Wavelet-based tools to analyze, filter, and reconstruct transient gravitational-wave signals
- Fast and faithful interpolation of numerical relativity surrogate waveforms using meshfree approximation
- Theory-agnostic searches for non-gravitational modes in black hole ringdown
- GW230814: investigation of a loud gravitational-wave signal observed with a single detector
- Probing nontensorial gravitational waves with a next-generation ground-based detector network
- Detection of GW200105 with a targeted eccentric search
- Driving unmodelled gravitational-wave transient searches using astrophysical information
- Beyond GWTC-3: Analysing and verifying new gravitational-wave events from community catalogues
- Gravitational-wave searches in the era of Advanced LIGO and Virgo
- The impact of local noise recorded at the ET candidate sites on the signal to noise ratio of CBC gravitational wave signals for the ET triangle configuration
- Identifying and Mitigating Machine Learning Biases for the Gravitational Wave Detection Problem
- A follow-up on intermediate-mass black hole candidates in the second LIGO-Virgo observing run with the Bayes Coherence Ratio
- Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
- Uncovering faint lensed gravitational-wave signals and reprioritizing their follow-up analysis using galaxy lensing forecasts with detected counterparts
- A novel multi-layer modular approach for real-time fuzzy-identification of gravitational-wave signals
- Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers
- WINTER on S250206dm: A near-infrared search for an electromagnetic counterpart to a gravitational-wave event
- Obtaining Statistical Significance of Gravitational Wave Signals in Hierarchical Search
- Robust, Rapid, and Simple Gravitational-wave Parameter Estimation
- Accounting for the Known Unknowns: A Parametric Framework to Incorporate Systematic Waveform Errors in Gravitational-Wave Parameter Estimation
- Leveraging cross-detector parameter consistency measures to enhance sensitivities of gravitational wave searches
- Deep Multimessenger Search for Compact Binary Mergers in LIGO, Virgo, and Fermi/GBM Data from 2016-2017
- Beyond the Long Wavelength Approximation: Next-generation Gravitational-Wave Detectors and Frequency-dependent Antenna Patterns
- Sensing and vetoing loud transient noises for the gravitational-wave detection
- Gravitational lensing aided luminosity distance estimation for compact binary coalescences
- Digital Infrastructure in Astrophysics
- Mitigating the effect of the population model uncertainty on the strong lensing Bayes factor using nonparametric methods
- Quantum Bayesian Inference with Renormalization for Gravitational Waves
- Identification of Strongly Lensed Gravitational Wave Events Using Squeeze-and-Excitation Multilayer Perceptron Data-efficient Image Transformer
- Improved binary black hole searches through better discrimination against noise transients
- Data Access for LIGO on the OSG
- Multi-detector null-stream-based statistic for compact binary coalescence searches
- Binary black hole population inference combining confident and marginal events from the search pipeline
- Is GW190521 a gravitational wave echo of wormhole remnant from another universe?
- Bayesian Analysis of Wave-Optics Gravitationally Lensed Massive Black Hole Binaries with Space-Based Gravitational Wave Detector
- Effect of kick velocity on gravitational wave detection of binary black holes with space- and ground-based detectors
- Beyond FINDCHIRP: Breaking the memory wall and optimal FFTs for Gravitational-Wave Matched-Filter Searches with Ratio-Filter Dechirping
- Impact of noise transients on gravitational-wave burst detection efficiency of the BayesWave pipeline with multi-detector networks
- Calibrating approximate Bayesian credible intervals of gravitational-wave parameters
- Chirp mass based glitch identification in long duration gravitational wave transients
- Boosting the Efficiency of Parametric Detection with Hierarchical Neural Networks
- Unmasking noise transients masquerading as intermediate-mass black hole binaries
- Search for exotic gravitational wave signals beyond general relativity using deep learning
- Hierarchical searches for subsolar-mass binaries and the third-generation gravitational wave detector era
- PycWB: A User-friendly, Modular, and Python-based Framework for Gravitational Wave Unmodelled Search
- Tidal reconstruction of neutron star mergers from their late inspiral
- A nonparametric method to assess significance of events in search for gravitational waves with false discovery rate
- Glitch veto based on unphysical gravitational wave binary inspiral templates
- Learning and Interpreting Gravitational-Wave Features from CNNs with a Random Forest Approach
- Scalable matched-filtering pipeline for gravitational-wave searches of compact binary mergers
- Pearson cross-correlation in the first four black hole binary mergers
- The impact of precession and higher-order multipoles for gravitational wave cosmological inference
- Reducing systematic uncertainties in gravitational-wave population analyses by increasing the detection threshold
- Probing cosmic strings via gravitational-wave lensing
- Learning to detect continuous gravitational waves: an open data-analysis competition
- GWAI: Artificial Intelligence Platform for Enhanced Gravitational Wave Data Analysis
- Improved Binary Black Hole Search Discriminator from the Singular Value Decomposition of Non-Gaussian Noise Transients
- SAGE: using CubeSats for Gravitational Wave Detection
- Using machine learning to auto-tune chi-squared tests for gravitational wave searches
- Reconsidering the consistent use of precessing, higher order multipole models for gravitational wave analyses
- Quantum Search for Gravitational Wave of Massive Black Hole Binaries
- Search for Precessing Binary Black Holes in Advanced LIGO's Third Observing Run using Harmonic Decomposition
- Constraining the Time of Gravitational Wave Emission from Core-Collapse Supernovae
- Enhancing gravitational-wave detection: a machine learning pipeline combination approach with robust uncertainty quantification
- Regression of Suspension Violin Modes in KAGRA O3GK Data with Kalman Filters
- Astrophysical or Terrestrial: Machine learning classification of gravitational-wave candidates using multiple-search information
- Quantum phase estimation with optimal confidence interval using three control qubits
- Could the high-mass black holes from gravitational-wave observations be explained by lensing?
- Searches for Compact Binary Coalescence Events Using Neural Networks in LIGO/Virgo Third Observation Period
- Measuring spin precession from massive black hole binaries with gravitational waves: insights from time-domain signal morphology
- A template-free approach for waveform extraction of gravitational wave events
- Effects of local cosmic inhomogeneities on the gravitational wave event rate
- Hierarchical search for compact binary coalescences in the Advanced LIGO's first two observing runs
- Chasing Gamma-Ray Signals from Binary Neutron Star Coalescences with the Cherenkov Telescope Array: Prospects and Observing Strategies
- Unveiling gravitational waves from core-collapse supernovae with MUSE
- Extract non-Gaussian Features in Gravitational Wave Observation Data Using Self-Supervised Learning