Gravitational radiation from Kerr black holes using the Sasaki-Nakamura formalism: waveforms and fluxes at infinity
Yucheng Yin, Rico K. L. Lo, Xian Chen
TL;DR
The paper develops a new integration-by-parts scheme for the Sasaki–Nakamura formalism to compute gravitational waveforms and infinity fluxes from Kerr perturbations, removing the need for an extra radial integration when forming the SN source term. By introducing an auxiliary function $Y(r)$ and decomposing the SN source into tractable components, the method yields a nonoscillatory, source-independent path to $X^{\infty}_{\ell m \omega}$ and thus $h_+ - i h_\times$ for bound and unbound orbits. The approach is validated against established Teukolsky-based codes across generic bound orbits and radial infalls, achieving excellent agreement while maintaining comparable performance and enabling efficient generation of amplitude/flux data for extreme mass ratio inspiral modeling. These developments promise accelerated, cross-validated waveform generation for EMRIs, including eccentric and inclined configurations, with practical impact on space-based GW data analysis.
Abstract
In linear perturbation theory for Kerr black holes, there are two equivalent formalisms, namely the Teukolsky and the Sasaki-Nakamura (SN) formalism. Typically, one defaults to the Teukolsky formalism, especially when calculating extreme mass ratio inspiral waveforms, and uses the SN formalism when dealing with extended sources, as it offers superior convergence when employing the Green's function method for calculating the inhomogeneous solution. In this work, we present a new scheme for solving the inhomogeneous SN equation, based on integration by parts, that eliminates the extra radial integration step required in the standard formulation to construct the source term for convolution with the SN variable. Our approach enables efficient computations of gravitational waveforms within the SN formalism in all cases, from compact to extended sources. We validate our scheme and code implementation against the literature and find excellent agreement, achieving comparable performance without employing any special optimization techniques.
