5 papers
Automatic classification pipeline for glitches in the Virgo detector
Tiago Fernandes, Francesco Di Renzo, Antonio Onofre +4
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…
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…
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…
Deep-Learning Classification and Parameter Inference of Rotational Core-Collapse Supernovae
Solange Nunes, Gabriel Escrig, Osvaldo G. Freitas +4
We test deep-learning (DL) techniques for the analysis of rotational core-collapse supernovae (CCSN) gravitational-wave (GW) signals by performing classification and parameter infe…