{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rapid-generation-of-fully-relativistic","title":"Rapid generation of fully relativistic extreme-mass-ratio-inspiral waveform templates for LISA data analysis","arxiv_id":"2008.06071","date":"2020-08-13","proceeding":null,"authors":["Alvin J. K. Chua","Michael L. Katz","Niels Warburton","Scott A. Hughes"],"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 $\\sim10^3$-$10^5$ 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 $1\\,\\mathrm{s}$, and achieve a mismatch of $\\lesssim 5\\times 10^{-4}$ against reference waveforms that take $\\gtrsim 10^4$ 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.","url_abs":"https://arxiv.org/abs/2008.06071v1","url_pdf":"https://arxiv.org/pdf/2008.06071v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"rapid-generation-of-fully-relativistic","repo_url":"https://github.com/BlackHolePerturbationToolkit/FastEMRIWaveforms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"rapid-generation-of-fully-relativistic","repo_url":"https://github.com/Hassankh92/FastEMRIWaveforms_KerrCircNonvac","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"rapid-generation-of-fully-relativistic","repo_url":"https://github.com/lorenzsp/emri_frequencydomainwaveforms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"rapid-generation-of-fully-relativistic","repo_url":"https://github.com/mikekatz04/FastEMRIWaveforms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}