Efficient Gravitational Wave Template Bank Generation with Differentiable Waveforms

Abstract

The most sensitive search pipelines for gravitational waves from compact binary mergers use matched filters to extract signals from the noisy data stream coming from gravitational wave detectors. Matched-filter searches require banks of template waveforms covering the physical parameter space of the binary system. Unfortunately, template bank construction can be a time-consuming task. Here we present a new method for efficiently generating template banks that utilizes automatic differentiation to calculate the parameter space metric. Principally, we demonstrate that automatic differentiation enables accurate computation of the metric for waveforms currently used in search pipelines, whilst being computationally cheap. Additionally, by combining random template placement and a Monte Carlo method for evaluating the fraction of the parameter space that is currently covered, we show that search-ready template banks for frequency-domain waveforms can be rapidly generated. Finally, we argue that differentiable waveforms offer a pathway to accelerating stochastic placement algorithms. We implement all our methods into an easy-to-use Python package based on the jax framework, diffbank, to allow the community to easily take advantage of differentiable waveforms for future searches.

arXiv comment15 pages, 6 figures. Comments welcome! Code can be found at https://github.com/adam-coogan/diffbank. Updated to match PRD version

References in corpus (39)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Array Programming with NumPy
• Observation of Gravitational Waves from a Binary Black Hole Merger
• GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
• Effective one-body approach to general relativistic two-body dynamics
• Computationally efficient models for the dominant and sub-dominant harmonic modes of precessing binary black holes
• Search templates for gravitational waves from inspiraling binaries: Choice of template spacing
• Matched filtering of gravitational waves from inspiraling compact binaries: Computational cost and template placement
• Improved filters for gravitational waves from inspiralling compact binaries
• Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation
• A Comparison of search templates for gravitational waves from binary inspiral
• Detecting gravitational waves from precessing binaries of spinning compact objects: Adiabatic limit
• Searching for Gravitational Waves from Compact Binaries with Precessing Spins
• A stochastic template placement algorithm for gravitational wave data analysis
• Effective one body multipolar waveform model for spin-aligned, quasi-circular, eccentric, hyperbolic black hole binaries
• Skye: A Differentiable Equation of State
• Observing and measuring the neutron-star equation-of-state in spinning binary neutron star systems
• A template bank to search for gravitational waves from inspiralling compact binaries I: physical models
• An effectual template bank for the detection of gravitational waves from inspiralling compact binaries with generic spins
• Gravitational waves from inspiralling compact binaries: hexagonal template placement and its efficiency in detecting physical signals
• Template-based searches for gravitational waves: efficient lattice covering of flat parameter spaces
• Random template banks and relaxed lattice coverings
• Effectual gravitational-wave template banks for coalescing compact binaries using a hybrid placement algorithm
• Hierarchical search strategy for the detection of gravitational waves from coalescing binaries: Extension to post-Newtonian wave forms
• Cover art: issues in the metric-guided and metric-less placement of random and stochastic template banks
• Hybrid geometric-random template placement algorithm for gravitational wave searches from compact binary coalescences
• Template Bank for Compact Binary Coalescence Searches in Gravitational Wave Data: A General Geometric Placement Algorithm
• Differentiable Strong Lensing: Uniting Gravity and Neural Nets through Differentiable Probabilistic Programming
• Generalized Approach to Matched Filtering using Neural Networks
• A Differentiable Model of the Assembly of Individual and Populations of Dark Matter Halos
• Impact of precession on aligned-spin searches for neutron-star--black-hole binaries
• Searching for General Binary Inspirals with Gravitational Waves
• PyLightcurve-torch: a transit modelling package for deep learning applications in PyTorch
• Kernel Phase and Coronagraphy with Automatic Differentiation
• Efficient generation and optimization of stochastic template banks by a neighboring cell algorithm
• Strong-lensing source reconstruction with variationally optimised Gaussian processes
• Parameter space metric for 3.5 post-Newtonian gravitational-waves from compact binary inspirals
• A stochastic template bank for gravitational wave searches for precessing neutron-star--black-hole coalescence events
• Metric Assisted Stochastic Sampling (MASS) search for gravitational waves from binary black hole mergers

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