Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms

Fuente: arXiv
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Main Authors: Tenorio, Rodrigo, Gerosa, Davide
Format: Preprint
Published: 2025
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author Tenorio, Rodrigo
Gerosa, Davide
author_facet Tenorio, Rodrigo
Gerosa, Davide
contents We introduce a framework based on short Fourier transforms (SFTs) to analyze long-duration gravitational wave signals from compact binaries. Targeted systems include binary neutron stars observed by third-generation ground-based detectors and massive black hole binaries observed by the LISA space mission. In short, ours is an extremely fast, scalable, and parallelizable implementation of the gravitational wave inner product, a core operation of gravitational wave matched filtering. By operating on disjoint data segments, SFTs allow for efficient handling of noise nonstationarities, data gaps, and detector-induced signal modulations. We present a pilot application to early warning problems in both ground- and space-based next-generation detectors. Overall, SFTs reduce the computing cost of evaluating an inner product by three to five orders of magnitude, depending on the specific application, with respect to a nonoptimized approach. We release public tools to operate using the SFT framework, including a vectorized and hardware-accelerated reimplementation of a time-domain waveform. The inner product is the key building block of all gravitational wave data treatments; by speeding up this low-level element so massively, SFTs provide an extremely promising solution for current and future gravitational wave data-analysis problems.
format Preprint
id arxiv_https___arxiv_org_abs_2502_11823
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms
Tenorio, Rodrigo
Gerosa, Davide
General Relativity and Quantum Cosmology
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
We introduce a framework based on short Fourier transforms (SFTs) to analyze long-duration gravitational wave signals from compact binaries. Targeted systems include binary neutron stars observed by third-generation ground-based detectors and massive black hole binaries observed by the LISA space mission. In short, ours is an extremely fast, scalable, and parallelizable implementation of the gravitational wave inner product, a core operation of gravitational wave matched filtering. By operating on disjoint data segments, SFTs allow for efficient handling of noise nonstationarities, data gaps, and detector-induced signal modulations. We present a pilot application to early warning problems in both ground- and space-based next-generation detectors. Overall, SFTs reduce the computing cost of evaluating an inner product by three to five orders of magnitude, depending on the specific application, with respect to a nonoptimized approach. We release public tools to operate using the SFT framework, including a vectorized and hardware-accelerated reimplementation of a time-domain waveform. The inner product is the key building block of all gravitational wave data treatments; by speeding up this low-level element so massively, SFTs provide an extremely promising solution for current and future gravitational wave data-analysis problems.
title Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms
topic General Relativity and Quantum Cosmology
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2502.11823