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Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids

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arxiv 2001.10897 v1 pith:WRA6E55G submitted 2020-01-29 gr-qc

Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids

classification gr-qc
keywords domainfrequencyalgorithmanalysisdataevaluationwaveformsaccelerate
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper presents an algorithm to accelerate the evaluation of inspiral-merger-ringdown waveform models for gravitational wave data analysis. While the idea can also be applied in the time domain, here we focus on the frequency domain, which is most typically used to reduced computational cost in gravitational wave data analysis. Our work extends the idea of multibanding, which has been developed to accelerate frequency domain waveforms, to include the merger and ringdown and spherical harmonics beyond the dominant quadrupole spherical harmonic. The original method is based on a heuristic algorithm based on the inspiral to de-refine the equi-spaced frequency grid used for data analysis where a coarser grid is sufficient for accurate evaluation of a waveform model. Here we use a different criterion, based on the local interpolation error, which is more flexible and can easily be adapted to general waveforms, if their phenomenology is understood. We discuss our implementation in the LIGO Algorithm Library for the PhenomXHM frequency domain model, and report the acceleration in different parts of the parameter space of compact binary systems.

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Cited by 5 Pith papers

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  2. Learning Post-Newtonian Corrections from Numerical Relativity

    gr-qc 2025-11 conditional novelty 6.0

    A PINN learns higher-order corrections to the TaylorT4 PN model from eight NR surrogate waveforms, reducing phase and amplitude errors in the inspiral while enforcing physical symmetries.

  3. Computationally efficient models for the dominant and sub-dominant harmonic modes of precessing binary black holes

    gr-qc 2020-04 conditional novelty 6.0

    IMRPhenomXPHM is a new computationally efficient phenomenological model for precessing binary black hole gravitational-wave signals that incorporates higher-order modes via twisting-up maps from non-precessing waveforms.

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    Simulations of ET and CE networks show delays degrade localization metrics far more than SNR, with LIGO India greatly reducing the impact for multi-messenger and stochastic searches.

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    GWTC-2.1 adds eight new high-significance compact binary coalescence events to the prior catalog, extending the observed black hole mass range and including candidates inside the pair-instability mass gap.