Machine learning applications in neutron star physics
- Date
- November 19 (Tue) at 15:00 - 16:30, 2024 (JST)
- Speaker
-
- Márcio Ferreira (Researcher, Physics Department, University of Coimbra, Portugal)
- Venue
- Language
- English
- Host
- Lingxiao Wang
The equation of state and the internal composition of a neutron star are still unanswered questions in astrophysics. To constrain the different composition scenarios inside neutron stars, we rely on pulsars observations and gravitational waves detections. This seminar shows different applications of supervised/unsupervised machine learning models in neutron stars physics, such as: i) extract the equation of state; ii) infer the proton fraction; iii) detect the possible existence of a second branch in the mass-radius diagram; and iv) detect the presence of hyperons.
Márcio Ferreira is a researcher at the Center for Physics at the University of Coimbra, Portugal, focusing on the application of machine learning to astrophysics and materials science. His work utilizes generative and descriptive models to address key questions in these fields. With a PhD in high energy physics and a Master’s in quantitative methods for finance, Márcio also merges his expertise in physics with an interest in financial market dynamics.
This is a closed event for scientists. Non-scientists are not allowed to attend. If you are not a member or related person and would like to attend, please contact us using the inquiry form. Please note that the event organizer or speaker must authorize your request to attend.