pySEOBNR: a software package for the next generation of effective-one-body multipolar waveform models

TL;DR

pySEOBNR is a Python software package that enables advanced gravitational-wave waveform modeling within the effective-one-body formalism, facilitating analysis of black hole and neutron star binaries for current and future GW detectors.

Contribution

It introduces a flexible, efficient Python framework for generating, calibrating, and testing state-of-the-art EOB waveform models, including the SEOBNRv5PHM model.

Findings

Contains the SEOBNRv5PHM model calibrated to numerical relativity.

Provides infrastructure for developing new EOB waveform models.

Enhances GW data analysis capabilities for upcoming detectors.

Abstract

We present pySEOBNR, a Python package for gravitational-wave (GW) modeling developed within the effective-one-body (EOB) formalism. The package contains an extensive framework to generate state-of-the-art inspiral-merger-ringdown waveform models for compact-object binaries composed of black holes and neutron stars. We document and demonstrate how to use the built-in quasi-circular precessing-spin model SEOBNRv5PHM, whose aligned-spin limit (SEOBNRv5HM) has been calibrated to numerical-relativity simulations and the nonspinning sector to gravitational self-force data using pySEOBNR. Furthermore, pySEOBNR contains the infrastructure necessary to construct, calibrate, test, and profile new waveform models in the EOB approach. The efficiency and flexibility of pySEOBNR will be crucial to overcome the data-analysis challenges posed by upcoming and next-generation GW detectors on the ground and in space, which will afford the possibility to observe all compact-object binaries in our Universe.