Generalitat Project: CIDEGENT/2020/036
Funding Body: Generalitat Valenciana
Main Researcher: Andrés Moya Bedón
Summary:
The DAFEM project is based in two main goals:
- Stellar characterization using Machine Learning/AI tools.
- Use of 3D atmospheric models to understand pulsations of A-F stars.
To these two goals we have added a third one appeared before the presentation of this project and must be faces before goal (2): The analysis of no-linear pulsations modes in Scuti stars.
Point 1 can be divided into different scientific sub-objectives such as:
- Automate analysis of space light-curves.
- Automate the obtention of asteroseismic observables from these light-curves in the case of pulsating A-F stars.
- Using Machine Learning techniques, mainly hierarchical Bayesian models, for stellar characterization.
1.3) Using Machine Learning techniques for searching for patterns. Point 2 is divided into three sub-objectives:
- To extend 3D atmospheric models to the A-F region
- To patch 1D projections of these 3D models to 1D stellar structure and evolution models.
- To compare these theoretical models with observational data (point 1) for the case of pulsating A-F stars.
On the other hand, the new scientific goal now part of the project and related to no-linear modes in Scuti stars, can be divided into three sub-objectives:
- To extend the no-linear diagnostic diagrams beyond HADS.
- To resolve numerically the no-linear pulsating differential equations using these no-linear diagnostic diagrams.
- To analyze the resulting models comparing their predictions with observations from Kepler and TESS (NASA)
All these goals can be achieved thanks to the pertinence of the PI to the scientific teams of Kepler and TESS, and also to the future ESA space mission Plato2.0
