69 citations · 93 across the 5 of their papers we have counts for
6 papers · 1 filter
Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms
Michael Pürrer, Ashwin Girish, Lucy M. Thomas +2
We present a neural network surrogate model that emulates the NRSur7dq4 gravitational waveform model for precessing binary black hole mergers. The surrogate decomposes the waveform…
Revisiting the Coprecessing Frame in the Presence of Orbital Eccentricity
Lucy M. Thomas, Katerina Chatziioannou, Sam Johar +2
Accurate inclusion of both spin precession and orbital eccentricity effects in gravitational waveform models represents a key hurdle in our ability to fully characterize the proper…
Optimizing Neural Network Surrogate Models: Application to Black Hole Merger Remnants
Lucy M. Thomas, Katerina Chatziioannou, Vijay Varma +1
Surrogate models of numerical relativity simulations of merging black holes provide the most accurate tools for gravitational-wave data analysis. Neural network-based surrogates pr…
New effective precession spin for modeling multimodal gravitational waveforms in the strong-field regime
Lucy M. Thomas, Patricia Schmidt, Geraint Pratten
Accurately modelling the complete gravitational-wave signal from precessing binary black holes through the late inspiral, merger and ringdown remains a challenging problem. The lac…
A generalized precession parameter to interpret gravitational-wave data
Davide Gerosa, Matthew Mould, Daria Gangardt +3
Originally designed for waveform approximants, the effective precession parameter is the most commonly used quantity to characterize spin-precession effects in gravi…
Measuring precession in asymmetric compact binaries
Geraint Pratten, Patricia Schmidt, Riccardo Buscicchio +1
Gravitational-wave observations of merging compact binaries hold the key to precision measurements of the objects' masses and spins. General-relativistic precession, caused by spin…