5 papers
Parameter Estimation Horizon of Core-Collapse Supernovae with a Network of Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Solange Nunes +3
Core-collapse supernovae are among the most promising yet still undetected sources of gravitational waves. A future detection would provide a direct view of the physical processes…
Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Daniil Orel +8
Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova cent…
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…
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…