25 citations · 31 across the 7 of their papers we have counts for
7 papers
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…
Automatic classification pipeline for glitches in the Virgo detector
Tiago Fernandes, Francesco Di Renzo, Antonio Onofre +2
Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work introduces VIGILant, an automati…
An autoencoder-based surrogate waveform model for quasi-circular binary-black-hole mergers
Anastasios Theodoropoulos, Nino Villanueva, Osvaldo Gramaxo Freitas +6
The generation of accurate waveforms from binary black hole (BBH) mergers is a major effort in Gravitational-Wave Astronomy. In recent years, machine-learning-based surrogate model…
Observing boson stars in binary systems: The case of Gaia BH1
Pedro Passos, Héctor R. Olivares-Sánchez, José A. Font +1
The Gaia experiment recently reported the observation of a binary system composed of a Sun-like star orbiting a dark compact object, known as Gaia BH1. The nature of the compact ob…
A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms
Osvaldo Gramaxo Freitas, Anastasios Theodoropoulos, Nino Villanueva +6
Gravitational-wave approximants are essential for gravitational-wave astronomy, allowing the coverage binary black hole parameter space for inference or match filtering without cos…
Machine-Learning Love: classifying the equation of state of neutron stars with Transformers
Gonçalo Gonçalves, Márcio Ferreira, João Aveiro +4
The use of the Audio Spectrogram Transformer (AST) model for gravitational-wave data analysis is investigated. The AST machine-learning model is a convolution-free classifier that…
Identification of Binary Neutron Star Mergers in Gravitational-Wave Data Using YOLO One-Shot Object Detection
João Aveiro, Felipe F. Freitas, Márcio Ferreira +4
We demonstrate the application of the YOLOv5 model, a general purpose convolution-based single-shot object detection model, in the task of detecting binary neutron star (BNS) coale…