#StudentSeminars: Department of Astronomy and Astrophysics Session

Sesión

1 mar. 2024 15:00

Classroom 4104 (Campus Burjassot)

Lista de contribución Cronograma

4. A machine learning based eigenvalue solver for core-collapse supernovae gravitational wave asteroseismology

Dimitra Tseneklidou

1/3/24 15:00

One of the most promising and challenging future gravitational wave (GW) sources are core-collapse supernovae. The oscillation modes of the proto-neutron star (PNS) and the stalled accretion shock will be excited triggering the GW emission. Due to the stochastic nature of these signals, it is not possible to use template matching techniques. An alternative way to analyze the signal is to...

5. Stellar characterization using Hierarchical Bayesian Neural Networks

Víctor Tamames Rodero

1/3/24 15:40

In this study, we present a machine learning model, particularly a Hierarchical Bayesian Neural Network (HBNN), designed to predict stellar parameters such as mass, radius, and age, with a particular focus on the last one. Our goal is to emphasize the advantages of transitioning from classical machine learning predictors to probabilistic models, which usually provide a more realistic...

6. How to unveil the mysteries of the most massive galaxies in the early universe

Andres Laza Ramos

1/3/24 16:20

Thanks to the James Webb Space Telescope (JWST), we are looking at the cosmos as never before, receiving cutting-edge imaging and spectroscopic data, which allows us to investigate the properties of distant, early (z>7) galaxies. However, this process is not simple and a keen knowledge of it is necessary, as it requires the understanding of multiple pipelines and tools, and how to combine them...