Dingo-Pop uses a transformer to perform amortized, end-to-end population inference from GW strain data in seconds, bypassing per-event Monte Carlo sampling.
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The spectral siren technique requires independent knowledge of binary black hole mass distributions at all redshifts to an accuracy better than the statistical uncertainty, or else the Hubble constant measurement is biased.
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End-to-End Population Inference from Gravitational-Wave Strain using Transformers
Dingo-Pop uses a transformer to perform amortized, end-to-end population inference from GW strain data in seconds, bypassing per-event Monte Carlo sampling.
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Blinded Mock Data Challenge: Is the Spectral Siren Technique Robust for Measuring the Hubble Constant?
The spectral siren technique requires independent knowledge of binary black hole mass distributions at all redshifts to an accuracy better than the statistical uncertainty, or else the Hubble constant measurement is biased.