Effectual gravitational-wave template banks for coalescing compact binaries using a hybrid placement algorithm

Abstract

Recent discoveries of gravitational wave (GW) signals from astrophysical compact binary systems of neutron stars and black holes have firmly established them as prime sources for advanced GW detectors. Theoretical templates of expected signals from such systems have been used to filter the detector data using the \emph{matched filtering} technique. An efficient grid over the parameter space at a fixed minimal match has a direct impact on improving the computational efficiency of these searches. We present the construction of three-dimensional template banks (in component masses and an effective spin parameter) by incorporating several new optimizations to the hybrid geometric-random template placement algorithm that we proposed recently. These optimizations allow us to create more efficient template banks in future compact binary searches by shrinking the hybrid banks by $\sim 34\%$ in comparison to the basic algorithm. Such optimized banks are also found to be $\sim 22\%$ smaller than the optimized stochastic bank constructed over a nominal range of parameters. We also construct an explicit hybrid template bank with parameters identical to the `uber-bank' used in the recently-concluded CBC searches in the second observation run of the Advanced LIGO and Virgo detectors. We demonstrate a reduction of more than 53,000 templates over the stochastic template bank at a near-identical coverage as determined by fitting factor studies. A computationally efficient technique for semi-numerical calculation of the parameter space metric, applicable for aligned-spin waveform family, is also outlined. The resulting hybrid template banks can be generated much faster in comparison to the stochastic banks, and are ready to be used in the upcoming observation runs of Advanced LIGO and Virgo.

The new title: Effectual template banks for upcoming compact binary searches in Advanced-LIGO Virgo data

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Cited by in corpus (46)

• GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
• GW190814: Gravitational Waves from the Coalescence of a 23 M${}_{\odot }$ Black Hole with a 2.6 M${}_{\odot }$ Compact Object
• GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run
• GW190425: Observation of a Compact Binary Coalescence with Total Mass $\sim 3.4M_{\odot }$
• GW190521: A Binary Black Hole Merger with a Total Mass of $150M_{\odot }$
• Observation of gravitational waves from two neutron star-black hole coalescences
• GW190412: Observation of a Binary-Black-Hole Coalescence with Asymmetric Masses
• Observation of Gravitational Waves from the Coalescence of a $2.5\text{-}4.5M_{\odot }$ Compact Object and a Neutron Star
• GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
• The Science of the Einstein Telescope
• Realtime search for compact binary mergers in Advanced LIGO and Virgo's third observing run using PyCBC Live
• Gravitational-wave surrogate models powered by artificial neural networks: The ANN-Sur for waveform generation
• Rapid Parameter Estimation of Gravitational Waves from Binary Neutron Star Coalescence using Focused Reduced Order Quadrature
• Template Bank for Compact Binary Coalescence Searches in Gravitational Wave Data: A General Geometric Placement Algorithm
• Mock data study for next-generation ground-based detectors: The performance loss of matched filtering due to correlated confusion noise
• An optimized PyCBC search for gravitational waves from intermediate-mass black hole mergers
• Characterizing the observation bias in gravitational-wave detections and finding structured population properties
• Simulating Transient Noise Bursts in LIGO with Generative Adversarial Networks
• Searching for General Binary Inspirals with Gravitational Waves
• The MBTA Pipeline for Detecting Compact Binary Coalescences in the Fourth LIGO-Virgo-KAGRA Observing Run
• Systematic bias due to eccentricity in parameter estimation for merging binary neutron stars
• Spherical ansatz for parameter-space metrics
• Efficient Gravitational Wave Template Bank Generation with Differentiable Waveforms
• Establishing significance of gravitational-wave signals from a single observatory in the PyCBC offline search
• Optimized Search for a Binary Black Hole Merger Population in LIGO-Virgo O3 Data
• Hierarchical approach to matched filtering using a reduced basis
• A geometric template bank for the detection of spinning low-mass compact binaries with moderate orbital eccentricity
• Premerger detection of massive black hole binaries using deep learning
• Prompt sky localization of compact binary sources using a meshfree approximation
• Incorporating information from LIGO data quality streams into the PyCBC search for gravitational waves
• The failure of the Fisher Matrix when including tidal terms: Considering construction of template banks of tidally deformed binary neutron stars
• Neural network time-series classifiers for gravitational-wave searches in single-detector periods
• Hierarchical search strategy for the efficient detection of gravitational waves from non-precessing coalescing compact binaries with aligned-spins
• Beyond general relativity: designing a template-based search for exotic gravitational wave signals
• Efficient Stochastic Template Bank using Inner Product Inequalities
• Template bank to search for exotic gravitational wave signals from astrophysical compact binaries
• Sensitivity of spin-aligned searches for neutron star-black hole systems using future detectors
• Search for gravitational waves from eccentric binary black holes with an effective-one-body template
• Probing Particle Physics with Gravitational Waves
• Gravitational-wave searches in the era of Advanced LIGO and Virgo
• Optimizing the low-latency localization of gravitational waves
• Obtaining Statistical Significance of Gravitational Wave Signals in Hierarchical Search
• Constraining the Time of Gravitational Wave Emission from Core-Collapse Supernovae
• labrador: A domain-optimized machine-learning tool for gravitational wave inference
• Enhancing online estimation of CBC parameters with the low-latency MBTA analysis
• Hierarchical search for compact binary coalescences in the Advanced LIGO's first two observing runs