Effective-one-body waveforms for extreme-mass-ratio binaries: Consistency with second-order gravitational self-force quasicircular results and extension to nonprecessing spins and eccentricity
Angelica Albertini, Rossella Gamba, Alessandro Nagar, Sebastiano Bernuzzi
Abstract
We present a first complete implementation of an effective-one-body (EOB) model for extreme-mass-ratio inspirals (EMRIs) that incorporates aligned spins (on both the primary and the secondary) as well as orbital eccentricity. The model extends TEOBResumS-Dal\'{\i} for these binaries by (i) recasting conservative first-order gravitational self-force (1GSF) information in the resummed EOB potentials, (ii) employing a post-Newtonian (PN) ${3}^{+19}\mathrm{PN}$-accurate (3PN comparable-mass terms hybridized with test-particle terms up to 22PN relative order) expression for the gravitational-wave flux at infinity, and (iii) using an improved implementation of the horizon flux that better approximates its test-mass representation. With respect to our previous work [A. Albertini et al., Comparing second-order gravitational self-force and effective one body waveforms from inspiralling, quasicircular and nonspinning black hole binaries. II. The large-mass-ratio case, Phys. Rev. D 106, 084062 (2022).], we demonstrate that the inclusion of the ${3}^{+19}\mathrm{PN}$-accurate $\ensuremath{\ell}=9$ and $\ensuremath{\ell}=10$ modes in the flux at infinity significantly improves the model's agreement with second-order accurate GSF (2GSF) circular waveforms. For a standard EMRI with mass ratio $q\ensuremath{\equiv}{m}_{1}/{m}_{2}=5\ifmmode\times\else\texttimes\fi{}{10}^{4}$ and ${m}_{2}=10{M}_{\ensuremath{\bigodot}}$, the accumulated EOB/2GSF dephasing is $\ensuremath{\lesssim}\mathrm{rad}$ for $\ensuremath{\sim}1\text{ }\text{ }\mathrm{yr}$ of evolution, which is consistent with the standard accuracy requirements for EMRIs. We also showcase the generation of eccentric and spinning waveforms and discuss future extensions of our EOB towards a physically complete model for EMRIs.