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. Polarity classification is still indexing.
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Pith papers citing it
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UNVERDICTED 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.
Simulations show LIGO-A# constrains the peak redshift of binary black hole merger rate (tracing star formation) to ±0.1 in one year, improving to ±0.02 with next-generation detectors.
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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Mapping the star formation peak with LIGO A# and Next-Generation detectors
Simulations show LIGO-A# constrains the peak redshift of binary black hole merger rate (tracing star formation) to ±0.1 in one year, improving to ±0.02 with next-generation detectors.