9 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
DANSur_HM: Modularly incorporating higher modes in a deep learning based gravitational-wave surrogate
Osvaldo Gramaxo Freitas, Anastasios Theodoropoulos, Nino Villanueva +4
Numerical relativity (NR) simulations provide the most faithful representation of the gravitational waves (GWs) emitted by binary black hole (BBH) systems during merger. In the con…
High-speed reconstruction of long-duration gravitational waves from extreme mass ratio inspirals using sparse dictionary learning
Charles Badger, José A. Font, Mairi Sakellariadou +1
Measuring accurate long-duration gravitational waves from extreme mass ratio inspirals (EMRIs) could provide scientifically fruitful knowledge of massive black hole populations and…
Rapid detection of gravitational waves from binary black hole mergers using sparse dictionary learning
Charles Badger, Rahul Srinivasan, Alejandro Torres-Forné +4
Current gravitational wave (GW) detection pipelines for compact binary coalescence based on matched-filtering have reported over 90 confident detections during the first three obse…
Numerical relativity surrogate models for exotic compact objects: the case of head-on mergers of equal-mass Proca stars
Raimon Luna, Miquel Llorens-Monteagudo, Ana Lorenzo-Medina +6
We present several high-accuracy surrogate models for gravitational-wave signals from equal-mass head-on mergers of Proca stars, computed through the Newman-Penrose scalar . W…