Improving performance of SEOBNRv3 by $\sim$300x
Tyler D. Knowles, Caleb Devine, David A. Buch, Serdar A. Bilgili,, Thomas R. Adams, Zachariah B. Etienne, Sean T. McWilliams

TL;DR
This paper significantly enhances the computational efficiency of the SEOBNRv3 gravitational waveform approximant, making it approximately 340 times faster while maintaining accuracy, thereby enabling more practical and timely gravitational wave data analysis.
Contribution
The authors developed and implemented a series of optimizations for SEOBNRv3, resulting in a highly accelerated version suitable for advanced gravitational wave parameter estimation.
Findings
SEOBNRv3 optimized to be 340x faster
Waveforms remain numerically indistinguishable from original
Enables faster, more efficient gravitational wave analysis
Abstract
When a gravitational wave is detected by Advanced LIGO/Virgo, sophisticated parameter estimation (PE) pipelines spring into action. These pipelines leverage approximants to generate large numbers of theoretical gravitational waveform predictions to characterize the detected signal. One of the most accurate and physically comprehensive classes of approximants in wide use is the "Spinning Effective One Body--Numerical Relativity" (SEOBNR) family. Waveform generation with these approximants can be computationally expensive, which has limited their usefulness in multiple data analysis contexts. In prior work we improved the performance of the aligned-spin approximant SEOBNR version 2 (v2) by nearly 300x. In this work we focus on optimizing the full eight-dimensional, precessing approximant SEOBNR version 3 (v3). While several v2 optimizations were implemented during its development, v3 is…
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