Incorporating waveform calibration error in gravitational-wave modeling and inference for SEOBNRv4
Ritesh Bachhar, Michael Pürrer, Stephen R. Green
Accounting for Numerical-Relativity Calibration Uncertainty in Gravitational-Wave Modeling and Inference
Lorenzo Pompili, Alessandra Buonanno, Michael Pürrer
Compact binary coalescences: gravitational-wave astronomy with ground-based detectors
K. Chatziioannou, T. Dent, M. Fishbach, F. Ohme, M. Pürrer, V. Raymond, J. Veitch
Real-time gravitational-wave inference for binary neutron stars using machine learning
Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Nihar Gupte, Antoni Ramos-Buades, Alessandra Buonanno, Jonathan Gair, M. Coleman Miller, Maximilian Dax, Stephen R. Green, Michael Pürrer, Jonas Wildberger, Jakob Macke, Isobel M. Romero-Shaw, Bernhard Schölkopf
Optimizing Neural Network Surrogate Models: Application to Black Hole Merger Remnants
Lucy M. Thomas, Katerina Chatziioannou, Vijay Varma, Scott E. Field
Surrogate modeling of gravitational waves microlensed by spherically symmetric potentials
Uddeepta Deka, Gopalkrishna Prabhu, Md Arif Shaikh, Shasvath J. Kapadia, Vijay Varma, Scott E. Field
DeepExtractor: Time-domain reconstruction of signals and glitches in gravitational wave data with deep learning
Tom Dooney, Harsh Narola, Stefano Bromuri, R. Lyana Curier, Chris Van Den Broeck, Sarah Caudill, Daniel Stanley Tan
Robustness of Deep Learning Models to Precession in Gravitational-Wave Searches for Intermediate-Mass Black Hole Binaries
Quirijn Meijer, Marc van der Sluys, Sarah Caudill
Fast Waveform Generation for Gravitational Waves using Evolutionary Algorithms
Adding higher-order spherical harmonics in non-spinning eccentric binary black hole merger waveform models