Fast and faithful interpolation of numerical relativity surrogate waveforms using meshfree approximation

Abstract

Several theoretical waveform models have been developed over the years to capture the gravitational wave emission from the dynamical evolution of compact binary systems of neutron stars and black holes. As ground-based detectors improve their sensitivity at low frequencies, the real-time computation of these waveforms can become computationally expensive, exacerbating the steep cost of rapidly reconstructing source parameters using Bayesian methods. This paper describes an efficient numerical algorithm for generating high-fidelity interpolated compact binary waveforms at an arbitrary point in the signal manifold by leveraging computational linear algebra techniques such as singular value decomposition and meshfree approximation. The results are presented for the time-domain \texttt{NRHybSur3dq8} inspiral-merger-ringdown (IMR) waveform model that is fine tuned to numerical relativity simulations and parameterized by the two component-masses and two aligned spins. For demonstration, we target a specific region of the intrinsic parameter space inspired by the previously inferred parameters of the \texttt{GW200311\_115853} event -- a binary black hole system whose merger was recorded by the network of advanced-LIGO and Virgo detectors during the third observation run. We show that the meshfree interpolated waveforms can be evaluated in $\sim 2.3$ ms, which is about $\times 38$ faster than its brute-force (frequency-domain tapered) implementation in the \textsc{PyCBC} software package at a median accuracy of $\sim \mathcal{O}(10^{-5})$. The algorithm is computationally efficient and scales favourably with an increasing number of dimensions of the parameter space. This technique may find use in rapid parameter estimation and source reconstruction studies.

arXiv comment15 pages, 9 figures

References in corpus (33)

• dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
• Frequency-domain gravitational waves from non-precessing black-hole binaries. II. A phenomenological model for the advanced detector era
• Frequency-domain gravitational waves from non-precessing black-hole binaries. I. New numerical waveforms and anatomy of the signal
• The PyCBC search for gravitational waves from compact binary coalescence
• Inspiral-merger-ringdown waveforms for black-hole binaries with non-precessing spins
• An improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors
• Computationally efficient models for the dominant and sub-dominant harmonic modes of precessing binary black holes
• Gravitational-Radiation Damping of Compact Binary Systems to Second Post-Newtonian order
• Surrogate models for precessing binary black hole simulations with unequal masses
• Higher-order spin effects in the amplitude and phase of gravitational waveforms emitted by inspiraling compact binaries: Ready-to-use gravitational waveforms
• IMRPhenomXHM: A multi-mode frequency-domain model for the gravitational wave signal from non-precessing black-hole binaries
• Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation
• 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
• Surrogate model of hybridized numerical relativity binary black hole waveforms
• Real-time gravitational-wave science with neural posterior estimation
• Phenomenological model for the gravitational-wave signal from precessing binary black holes with two-spin effects
• A Numerical Relativity Waveform Surrogate Model for Generically Precessing Binary Black Hole Mergers
• Frequency domain reduced order models for gravitational waves from aligned-spin compact binaries
• Gravitational waves from inspiraling compact binaries: Validity of the stationary-phase approximation to the Fourier transform
• The third and a half post-Newtonian gravitational wave quadrupole mode for quasi-circular inspiralling compact binaries
• Nested Sampling with Normalising Flows for Gravitational-Wave Inference
• Accelerated gravitational-wave parameter estimation with reduced order modeling
• Frequency domain reduced order model of aligned-spin effective-one-body waveforms with higher-order modes
• Reduced-order modeling with artificial neurons for gravitational-wave inference
• Gravitational wave parameter estimation with compressed likelihood evaluations
• Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions
• 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
• A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach
• Interpolating compact binary waveforms using the singular value decomposition
• Fast likelihood evaluation using meshfree approximations for reconstructing compact binary sources
• Efficient Reduced Order Quadrature Construction Algorithms for Fast Gravitational Wave Inference
• Deep Learning Model on Gravitational Waveforms in Merging and Ringdown Phases of Binary Black Hole Coalescences

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