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Rapid Parameter Estimation of Gravitational Waves from Binary Neutron Star Coalescence using Focused Reduced Order Quadrature

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arxiv 2007.09108 v2 pith:EAVG5LQZ submitted 2020-07-17 gr-qc astro-ph.IM

classification gr-qcastro-ph.IM
keywords estimationparameterorderdetectionquadraturereducedaccuratebinary
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abstract

Rapid parameter estimation of gravitational waves from binary neutron star coalescence, in particular accurate sky localisation in minutes after the initial detection stage, is crucial for the success of multi-messenger observations. One of the techniques to speed up the parameter estimation, which has been applied for the production analysis of the LIGO-Virgo collaboration, is reduced order quadrature (ROQ). While it speeds up parameter estimation significantly, the time required is still on the order of hours. Focusing on the fact that the parameter-estimation follow-up can be tuned with the information available at the detection stage, we improve the ROQ technique and develop a new technique, which we designate focused reduced order quadrature (FROQ). We find that FROQ speeds up the parameter estimation by a factor of $\mathcal{O}(10^3)$ to $\mathcal{O}(10^4)$ and enables providing accurate source properties such as the location of a source in several tens of minutes after detection.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Ab Initio Real-Time Gravitational-Wave Parameter Estimation

    gr-qc 2026-07 accept novelty 6.0 of 10

    Slice-within-Gibbs nested sampling on modern GPUs delivers well-calibrated BNS parameter estimation in ~12 minutes uncompressed and ~89 seconds with heterodyning, from cold priors.

  2. The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference

    gr-qc 2026-01 conditional novelty 6.0 of 10

    SHARPy uses Sequential Monte Carlo with a No-U-Turn sampler in JAX to estimate gravitational-wave posteriors and evidence for binary black holes in about ten minutes.

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