24 citations · 33 across the 4 of their papers we have counts for
5 papers
Classification of the equation of state of neutron stars via sparse dictionary learning
Miquel Llorens-Monteagudo, Alejandro Torres-Forné, José A. Font
The post-merger phase of binary neutron star (BNS) mergers encodes valuable information about the equation of state (EOS) of supranuclear matter. Extracting this information from t…
CLAWDIA: A dictionary learning framework for gravitational-wave data analysis
Miquel Llorens-Monteagudo, Alejandro Torres-Forné, José A. Font
Deep-learning methods are becoming increasingly important in gravitational-wave data analysis, yet their performance often relies on large training datasets and models whose intern…
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…
Determining the core-collapse supernova explosion mechanism with current and future gravitational-wave observatories
Jade Powell, Alberto Iess, Miquel Llorens-Monteagudo +5
Gravitational waves are emitted from deep within a core-collapse supernova, which may enable us to determine the mechanism of the explosion from a gravitational-wave detection. Pre…
Classification of gravitational-wave glitches via dictionary learning
Miquel Llorens-Monteagudo, Alejandro Torres-Forné, José A. Font +1
We present a new method for the classification of transient noise signals (or glitches) in advanced gravitational-wave interferometers. The method uses learned dictionaries (a supe…