A new model emphasizing secondary mass features and pairing transitions improves spectral siren H0 constraints by ~30% using 142 GW events from GWTC-4.0.
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Determining the Hubble Constant from Gravitational Wave Observations
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A new Bayesian analysis of VLBI observations of GW170817's jet afterglow constrains the viewing angle to 16.8-19.2 degrees and measures H0 = 65.5 ± 4.4 km s^{-1} Mpc^{-1}, closer to Planck than SH0ES values.
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.
Hierarchical Bayesian inference allows accurate recovery of intrinsic astrophysical source populations even when follow-up selection is unknown and correlated with parameters of interest.
FluxMC integrates flow matching with parallel tempering MCMC to converge in under five hours on high-fidelity IMRPhenomHM waveforms for massive black hole binaries, where standard methods fail after hundreds of hours and produce two to three orders of magnitude higher distributional error.
Restricting analysis to the top 1% most luminous galaxies in GW localization volumes yields 1-4 candidate hosts for three specific events, with 29-36% probability of random association.
MUST is a new 6.5 m telescope designed to deliver simultaneous optical spectra for over 20,000 targets across a 5 deg² field, enabling the largest 3D spectroscopic map of the Universe with redshifts for more than 100 million objects over an 8-year survey.
Methodological choices in dark siren cross-correlations can mitigate biases in H0 inference when selection effects are built into the model and samples of precise events are sufficiently large.
citing papers explorer
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Secondary-Mass Features improve Spectral-Siren $H_0$ Constraints
A new model emphasizing secondary mass features and pairing transitions improves spectral siren H0 constraints by ~30% using 142 GW events from GWTC-4.0.
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Revisiting GW170817 at milliarcsecond scale: high-precision constraints on jet geometry and $H_0$
A new Bayesian analysis of VLBI observations of GW170817's jet afterglow constrains the viewing angle to 16.8-19.2 degrees and measures H0 = 65.5 ± 4.4 km s^{-1} Mpc^{-1}, closer to Planck than SH0ES values.
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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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What You Don't Know Won't Hurt You: Self-Consistent Hierarchical Inference with Unknown Follow-up Selection Strategies
Hierarchical Bayesian inference allows accurate recovery of intrinsic astrophysical source populations even when follow-up selection is unknown and correlated with parameters of interest.
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FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations
FluxMC integrates flow matching with parallel tempering MCMC to converge in under five hours on high-fidelity IMRPhenomHM waveforms for massive black hole binaries, where standard methods fail after hundreds of hours and produce two to three orders of magnitude higher distributional error.
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Finding the one: identifying the host of compact binary mergers
Restricting analysis to the top 1% most luminous galaxies in GW localization volumes yields 1-4 candidate hosts for three specific events, with 29-36% probability of random association.
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From Large Telescopes to the MUltiplexed Survey Telescope (MUST)
MUST is a new 6.5 m telescope designed to deliver simultaneous optical spectra for over 20,000 targets across a 5 deg² field, enabling the largest 3D spectroscopic map of the Universe with redshifts for more than 100 million objects over an 8-year survey.
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Dark siren cross-correlations and the sensitivity of $H_0$ to methodological choices
Methodological choices in dark siren cross-correlations can mitigate biases in H0 inference when selection effects are built into the model and samples of precise events are sufficiently large.