From the 1 of 8 linked papers with an AI index.
8 papers
Ab Initio Real-Time Gravitational-Wave Parameter Estimation
David Yallup, Metha Prathaban, James Alvey +4
The paper introduces a GPU‑optimized nested sampling algorithm that can perform rapid, full‑waveform gravitational‑wave parameter estimation for binary neutron star events, achievi…
Rapid Hubble constant inference from GW170817 using GPU-accelerated nested sampling: prior sensitivity and the limits of post-hoc reweighting
Ming Han Yang, Metha Prathaban, David Yallup +1
The bright-siren measurement of the Hubble constant from GW170817 (Abbott et al. 2017) assumes that switching from a volumetric to a uniform-in- luminosity-distance prior can…
The Early Career Workshop of GR-Amaldi 2025
S Al-Shammari, C P L Berry, C E A Chapman-Bird +18
Gravitational physics and astronomy have developed rapidly over the last decade, driven by new observations and theoretical breakthroughs. As new as the science and technology of t…
Leveraging rapid parameter estimates for efficient gravitational-wave Bayesian inference via posterior repartitioning
Metha Prathaban, Charlie Hoy, Michael J. Williams
Gravitational-wave astronomy typically relies on rigorous, computationally expensive Bayesian analyses. Several methods have also been developed to perform rapid, approximate Bayes…
Accelerated nested sampling with posterior repartitioning and -flows for gravitational waves
Metha Prathaban, Harry Bevins, Will Handley
There is an ever-growing need in the gravitational wave community for fast and reliable inference methods, accompanied by an informative error bar. Nested sampling satisfies the la…
Costless correction of chain based nested sampling parameter estimation in gravitational wave data and beyond
Metha Prathaban, Will Handley
Nested sampling parameter estimation differs from evidence estimation, in that it incurs an additional source of uncertainty. This uncertainty affects estimates of parameter means…