Summary
gwharmone is the first data-driven surrogate model for eccentric harmonics in binary black hole mergers, trained on 173 effective-one-body waveforms spanning mass ratios 1–3.5 and eccentricities 0–0.2. It uses SVD and Gaussian Process Regression for accurate, efficient waveform prediction.
Highlights
- Introduces gwharmone, a data-driven surrogate for eccentric harmonic modes
- Trained on 173 long effective-one-body waveforms (up to 100,000M)
- Covers mass ratios 1 to 3.5 and eccentricities up to 0.2
- Uses singular value decomposition to reduce data dimensionality
- Employs Gaussian Process Regression to interpolate waveform coefficients
- Accurately models eccentricity in dominant quadrupolar gravitational wave modes
- Enhances gravitational wave data analysis for LIGO-Virgo-KAGRA and future detectors
Key Insights
- Data-Driven Model Innovation: gwharmone is pioneering as a surrogate focused on eccentric harmonics, addressing the complexity of waveforms from binary black holes with non-circular orbits.
- Extensive Training Dataset: The model benefits from a large, diverse training set of 173 waveforms generated by TEOBResumS simulations, ensuring robust performance across parameter space.
- Dimensionality Reduction Technique: The application of singular value decomposition efficiently captures essential waveform features, reducing computational load without sacrificing accuracy.
- Advanced Interpolation Methodology: Utilizing Gaussian Process Regression allows smooth and reliable interpolation of waveform coefficients across different mass ratios and eccentricities.
- Eccentricity Treatment: The model integrates eccentricity explicitly, a challenging but critical parameter for interpreting gravitational wave signals from astrophysical sources.
- Validation and Accuracy: Validation on 1751 points demonstrates strong agreement with full effective-one-body models, supporting its use in gravitational wave data analysis.
- Broader Impact for GW Astronomy: gwharmone facilitates faster, more precise waveform generation, critical for parameter estimation and discovery in current and next-generation gravitational wave observatories.
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Citation
Islam, T., Venumadhav, T., Mehta, A. K., Anantpurkar, I., Wadekar, D., Roulet, J., … Zaldarriaga, M. (2025). gwharmone: first data-driven surrogate for eccentric harmonics in binary black hole merger waveforms (Version 1). arXiv. http://doi.org/10.48550/ARXIV.2504.12420