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Bayesian statistical framework for identifying strongly lensed gravitational-wave signals

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arxiv 2104.09339 v2 pith:OQ7GHMD5 submitted 2021-04-19 gr-qc astro-ph.IM

Bayesian statistical framework for identifying strongly lensed gravitational-wave signals

classification gr-qc astro-ph.IM
keywords lensedwavessignalsdifferentgravitationallensingastrophysicalbayesian
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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It is expected that gravitational waves, similar to electromagnetic waves, can be gravitationally lensed by intervening matters, producing multiple instances of the same signal arriving at different times from different apparent luminosity distances with different phase shifts compared to the un-lensed signal due to lensing. If unaccounted for, these lensed signals will masquerade as separate systems with higher mass and lower redshift. Here we present a Bayesian statistical framework for identifying strongly-lensed gravitational-wave signals that incorporates astrophysical information and accounts for selection effects. We also propose a two-step hierarchical analysis for more efficient computations of the probabilities and inferences of source parameters free from bias introduced by lensing. We show with examples on how changing the astrophysical models could shift one's interpretation on the origin of the observed gravitational waves, and possibly lead to indisputable evidence of strong lensing of the observed waves. In addition, we demonstrate the improvement in the sky localization of the source of the lensed signals, and in some cases the identification of the Morse indices of the lensed signals. If confirmed, lensed gravitational waves will allow us to probe the Universe at higher redshift, and to constrain the polarization contents of the waves with fewer detectors.

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Cited by 7 Pith papers

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    Fusing a simulation-trained common-source mass posterior with waveform features raises lensed-event detection efficiency from 20.8% to 35.2% at 1% false-positive rate and lowers the SNR for 50% efficiency from 45.3 to 33.5.

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    A two-step Bayesian reweighting scheme using Euclid galaxy locations boosts the Bayes factor for true lensed GW pairs by a factor of about 10 while lowering it for unlensed coincidences.

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