792 citations · 1.9k across the 19 of their papers we have counts for
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Accounting for numerical-relativity calibration uncertainty in gravitational-wave modeling and inference
Lorenzo Pompili, Alessandra Buonanno, Michael Pürrer
The increasing sensitivity of current and upcoming gravitational-wave (GW) detectors poses stringent requirements on the accuracy of the GW models used for data analysis. If these…
Compact binary coalescences: gravitational-wave astronomy with ground-based detectors
K. Chatziioannou, T. Dent, M. Fishbach +4
The era of gravitational wave astronomy began in 2015 with the observation of the signal from the merger of two black holes by the LIGO detectors; by 2021, almost 100 more such tra…
Real-time gravitational-wave inference for binary neutron stars using machine learning
Maximilian Dax, Stephen R. Green, Jonathan Gair +7
Mergers of binary neutron stars (BNSs) emit signals in both the gravitational-wave (GW) and electromagnetic (EM) spectra. Famously, the 2017 multi-messenger observation of GW170817…
Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Nihar Gupte, Antoni Ramos-Buades, Alessandra Buonanno +9
Binary black holes (BBHs) in eccentric orbits produce distinct modulations in gravitational waves (GWs); measuring orbital eccentricity provides evidence for dynamical binary forma…
Formulation Improvements for Critical Collapse Simulations
Daniela Cors, Sarah Renkhoff, Hannes R. Rüter +2
The precise tuning required to observe critical phenomena in gravitational collapse poses a challenge for most numerical codes. First, threshold estimation searches may be obstruct…
Adapting to noise distribution shifts in flow-based gravitational-wave inference
Jonas Wildberger, Maximilian Dax, Stephen R. Green +5
Deep learning techniques for gravitational-wave parameter estimation have emerged as a fast alternative to standard samplers $\unicode{x2013}$ producing results of comparable accur…