3 papers
astro-ph.SR2024
Variable Star Light Curves in Koopman Space
Nicolas Mekhaël, Mario Pasquato, Gaia Carenini +4
We present the first application of data-driven techniques for dynamical system analysis based on Koopman theory to variable stars. We focus on light curves of RRLyrae type variabl…
astro-ph.GA2023
Interpretable machine learning for finding intermediate-mass black holes
Mario Pasquato, Piero Trevisan, Abbas Askar +4
Definitive evidence that globular clusters (GCs) host intermediate-mass black holes (IMBHs) is elusive. Machine learning (ML) models trained on GC simulations can in principle pred…
astro-ph.GA2020
Measuring the spectral index of turbulent gas with deep learning from projected density maps
Piero Trevisan, Mario Pasquato, Alessandro Ballone +1
Turbulence plays a key role in star formation in molecular clouds, affecting star cluster primordial properties. As modelling present-day objects hinges on our understanding of the…