Scaling RIFT 1: Extending RIFT to third-generation gravitational-wave analyses
Abstract
Interpretation of compact binary signals observed by third-generation gravitational-wave detectors is complicated by their high signal-to-noise ratios, often reaching hundreds to thousands, and by time- and frequency-dependent detector responses arising from Earth's rotation and the detectors' large physical extent. Building on prior work for LISA, we implement generic, robust extensions of the RIFT parameter estimation pipeline that enable interpretation of these sources using any existing waveform model, without recourse to intermediate pretrained data products like reduced-order approximations or normalizing flows. We demonstrate end-to-end recovery of finite-size binary-neutron-star injections in a three-site next-generation network to SNR=1000, localizing the source's extrinsic parameters to 0.8×10−3 deg2 in minutes on a single GPU.
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BibTeX
@misc{oshaughnessy2026scaling,
title = {{Scaling RIFT 1: Extending RIFT to third-generation gravitational-wave analyses}},
author = {R. O'Shaughnessy and A. Jan and J. Lange and R. Mechum},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.37393},
eprint = {2609.37393},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.37393},
}
RIS
TY - UNPB
TI - Scaling RIFT 1: Extending RIFT to third-generation gravitational-wave analyses
AU - R. O'Shaughnessy
AU - A. Jan
AU - J. Lange
AU - R. Mechum
PY - 2026
DA - 2026/09/29
PB - arXiv
DO - 10.48550/arxiv.2609.37393
UR - https://arxiv.org/abs/2609.37393
AB - Interpretation of compact binary signals observed by third-generation gravitational-wave detectors is complicated by their high signal-to-noise ratios, often reaching hundreds to thousands, and by time- and frequency-dependent detector responses arising from Earth's rotation and the detectors' large physical extent. Building on prior work for LISA, we implement generic, robust extensions of the RIFT parameter estimation pipeline that enable interpretation of these sources using any existing waveform model, without recourse to intermediate pretrained data products like reduced-order approximations or normalizing flows. We demonstrate end-to-end recovery of finite-size binary-neutron-star injections in a three-site next-generation network to SNR=1000, localizing the source's extrinsic parameters to 0.8×10^−3 deg^2 in minutes on a single GPU.
ER -