Introduces regression on regression to fit physical parameters (τ_min, α, A, γ, δ) to GWTC-4 B-Spline merger rate posteriors, finding the progenitor formation rate evolves ~5.3 times steeper than the star formation rate at low z and exposing model misspecification.
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3 Pith papers cite this work, alongside 17 external citations. Polarity classification is still indexing.
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Pith papers citing it
17
external citations · OpenAlex
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2026 3representative citing papers
GWTC-4 data reveals three sub-populations of binary black holes with distinct delay-time distributions that depend on mass above 45 solar masses, mass-ratio, and spin, ruling out a single universal merger rate.
Applying the brightest-galaxy method to three well-localized GW events yields 1, 1, and 4 candidate host galaxies and a Hubble constant estimate of ~79 km/s/Mpc, but with 29–36% random-association probability and a selection bias.
citing papers explorer
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Regression on Regression: Mapping Data-Driven Binary Black Hole Merger Rate Fits to Progenitor Histories
Introduces regression on regression to fit physical parameters (τ_min, α, A, γ, δ) to GWTC-4 B-Spline merger rate posteriors, finding the progenitor formation rate evolves ~5.3 times steeper than the star formation rate at low z and exposing model misspecification.
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The First Detection of Sub-Populations in the Delay-Time Distribution of Binary Black Holes in GWTC-4 of LIGO-Virgo-KAGRA
GWTC-4 data reveals three sub-populations of binary black holes with distinct delay-time distributions that depend on mass above 45 solar masses, mass-ratio, and spin, ruling out a single universal merger rate.
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Identifying the host of compact binary mergers
Applying the brightest-galaxy method to three well-localized GW events yields 1, 1, and 4 candidate host galaxies and a Hubble constant estimate of ~79 km/s/Mpc, but with 29–36% random-association probability and a selection bias.