Rapid generation of fully relativistic extreme-mass-ratio-inspiral waveform templates for LISA data analysis
Abstract
The future space mission LISA will observe a wealth of gravitational-wave sources at millihertz frequencies. Of these, the extreme-mass-ratio inspirals of compact objects into massive black holes are the only sources that combine the challenges of strong-field complexity with that of long-lived signals. Such signals are found and characterized by comparing them against a large number of accurate waveform templates during data analysis, but the rapid generation of such templates is hindered by computing the 103-105 harmonic modes in a fully relativistic waveform. We use order-reduction and deep-learning techniques to derive a global fit for these modes, and implement it in a complete waveform framework with hardware acceleration. Our high-fidelity waveforms can be generated in under 1\,s, and achieve a mismatch of 5× 10-4 against reference waveforms that take 104 times longer. This marks the first time that analysis-length waveforms with full harmonic content can be produced on timescales useful for direct implementation in LISA analysis algorithms.