Published June 17, 2025 | Published
Journal Article Open

Adding higher-order spherical harmonics in nonspinning eccentric binary black hole merger waveform models

  • 1. ROR icon University of California, Santa Barbara
  • 2. ROR icon California Institute of Technology
  • 3. ROR icon University of Rhode Island
  • 4. ROR icon University of Massachusetts Dartmouth

Abstract

gwnrhme is a recently developed framework that seamlessly converts a multimodal (i.e., with several spherical harmonic modes) quasicircular waveform into a multimodal eccentric waveform if the quadrupolar eccentric waveform is known. Here, we employ the gwnrhme framework to combine a multimodal quasicircular numerical relativity surrogate waveform model nrhybsur3dq8 and quadrupolar nonspinning post-Newtonian eccentric waveform model eccentricimr to construct multimodal nonspinning eccentric model nrhybsur3dq8-gwnrhme. Using a total of 35 eccentric numerical relativity (NR) simulations obtained from the SXS and RIT catalogs, we demonstrate that nrhybsur3dq8-gwnrhme model predictions agree well with NR (with typical relative 𝐿2 errors of  ∼0.01 for the dominant quadrupolar mode) for mass ratios 1 ≤𝑞 ≤4 and eccentricities up to  ∼0.2 measured about 10 cycles before the merger. Our frequency-domain mismatches (calculated assuming advanced LIGO design sensitivity curve) are mostly below 0.01. To demonstrate the modularity of the gwnrhme framework, we further combine eccentricimr with the bhptnrsur1dq1e4bhptnrsur1dq1e4 model and develop a nonspinning eccentric model named bhptnrsur1dq1e4-gwnrhme. Finally, we develop a different variant of these models by replacing eccentricimr with eccentrictd. Both the gwnrhme framework and associated models are available through the gwmodels package.

Copyright and License

© 2025 American Physical Society.

Acknowledgement

We thank Chandra Kant Mishra, Frank Ohme, Ajit Kumar Mehta, Harald P. Pfeiffer, and Tejaswi Venumadhav for fruitful discussions. We are also thankful to Lorenzo Pompili for suggestions on our manuscript. This research was supported in part by the National Science Foundation under Grant No. NSF PHY-2309135 and the Simons Foundation (216179, LB). Most of this work was conducted on the UMass-URI UNITY supercomputer supported by the Massachusetts Green High-Performance Computing Center (MGHPCC) and CARNiE at the Center for Scientific Computing and Data Science Research (CSCDR) of UMassD, which is supported by Office of Naval Research (ONR)/Defense University Research Instrumentation Program (DURIP) Grant No. N00014181255.

Files

63d1-hh8k.pdf
Files (2.8 MB)
Name Size Download all
md5:32d7448217e0e35e5f55acd71d4027eb
2.8 MB Preview Download

Additional details

Created:
July 7, 2025
Modified:
July 7, 2025