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Towards inference of overlapping gravitational wave signals

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arxiv 2102.07692 v2 pith:ZZURA7CW submitted 2021-02-15 gr-qc astro-ph.HE

classification gr-qcastro-ph.HE
keywords mathrmcoalescencesignalsinferenceoverlappingtimebiasesbinaries
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

Merger rates of binary black holes, binary neutron stars, and neutron star-black hole binaries in the local Universe (i.e., redshift $z=0$), inferred from the Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo, are $16-130\, \mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$, $13-1900\, \mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$, and $7.4-320\,\mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$, respectively. These rates suggest that there is a significant chance that two or more of these signals will overlap with each other during their lifetime in the sensitivity-band of future gravitational-wave detectors such as the Cosmic Explorer and Einstein Telescope. The detection pipelines provide the coalescence time of each signal with an accuracy $\mathcal{O}(10\,\rm ms)$. We show that using a prior on the coalescence time from a detection pipeline, it is possible to correctly infer the properties of these overlapping signals with the current data-analysis infrastructure. We study different configurations of two overlapping signals created by non-spinning binaries, varying their time and phase at coalescence, as well as their signal-to-noise ratios. We conclude that, for the scenarios considered in this work, parameter inference is robust provided that their coalescence times in the detector frame are more than $\sim 1-2 \,\mathrm{s}$. Signals whose coalescence epochs lie within $\sim 0.5\,\mathrm{s}$ of each other suffer from significant biases in parameter inference, and new strategies and algorithms would be required to overcome such biases.

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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. Hierarchical Subtraction with Neural Density Estimators as a General Solution to Overlapping Gravitational Wave Signals

    gr-qc 2025-07 conditional novelty 7.0 of 10

    The paper introduces an iterative, ensemble-based hierarchical subtraction scheme powered by neural density estimators that recovers overlapping gravitational wave signals accurately and fast.

  2. Prospects for Neutrino Observation and Mass Measurement from Binary Neutron Star Mergers

    hep-ph 2025-11 conditional novelty 6.0 of 10

    Binary neutron star merger neutrinos will require a megaton-scale detector and decades of operation to detect, but a single detected neutrino could set a sub-eV (~0.1 eV) limit on the lightest neutrino mass via gravit...

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