First joint population inference on binary black hole eccentricity from GWTC-4 bounds the eccentric branching ratio below 5% at 90% confidence, with results consistent with quasi-circular models but highly model-dependent.
Accounting for Source Uncertainties in Analyses of Astronomical Survey Data
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abstract
I discuss an issue arising in analyzing data from astronomical surveys: accounting for measurement uncertainties in the properties of individual sources detected in a survey when making inferences about the entire population of sources. Source uncertainties require the analyst to introduce unknown ``incidental'' parameters for each source. The number of parameters thus grows with the size of the sample, and standard theorems guaranteeing asymptotic convergence of maximum likelihood estimates fail in such settings. From the Bayesian point of view, the missing ingredient in such analyses is accounting for the volume in the incidental parameter space via marginalization. I use simple simulations, motivated by modeling the distribution of trans-Neptunian objects surveyed in the outer solar system, to study the effects of source uncertainties on inferences. The simulations show that current non-Bayesian methods for handling source uncertainties (ignoring them, or using an ad hoc incidental parameter integration) produce incorrect inferences, with errors that grow more severe with increasing sample size. In contrast, accounting for source uncertainty via marginalization leads to sound inferences for any sample size.
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Using simulated binary black hole mergers and neutral hydrogen maps, the radio sirens method constrains H0 to 8% precision with 3000 high-SNR events, offering a 90% improvement over standard dark siren analyses.
Spin sorting with the default spin model distinguishes spinning and nonspinning binary black hole populations in simulations and shows real data rule out a fully nonspinning population but allow mixed ones with up to 80% nonspinning sources.
No evidence for deviations from general relativity is found in LIGO-Virgo binary black hole events, with improved constraints on waveform parameters, graviton mass, and ringdown properties.
Population-informed hierarchical parameter estimation is required for unbiased astrophysical interpretation of gravitational-wave events rather than using standard individual posteriors with reference priors.
citing papers explorer
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Population Properties of Binary Black Holes with Eccentricity
First joint population inference on binary black hole eccentricity from GWTC-4 bounds the eccentric branching ratio below 5% at 90% confidence, with results consistent with quasi-circular models but highly model-dependent.
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Radio sirens: inferring $H_0$ with binary black holes and neutral hydrogen in the era of the Einstein Telescope and the SKA Observatory
Using simulated binary black hole mergers and neutral hydrogen maps, the radio sirens method constrains H0 to 8% precision with 3000 high-SNR events, offering a 90% improvement over standard dark siren analyses.
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Disentangling spinning and nonspinning binary black hole populations with spin sorting
Spin sorting with the default spin model distinguishes spinning and nonspinning binary black hole populations in simulations and shows real data rule out a fully nonspinning population but allow mixed ones with up to 80% nonspinning sources.
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Tests of General Relativity with Binary Black Holes from the second LIGO-Virgo Gravitational-Wave Transient Catalog
No evidence for deviations from general relativity is found in LIGO-Virgo binary black hole events, with improved constraints on waveform parameters, graviton mass, and ringdown properties.
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Gravitational-wave astronomy requires population-informed parameter estimation
Population-informed hierarchical parameter estimation is required for unbiased astrophysical interpretation of gravitational-wave events rather than using standard individual posteriors with reference priors.