Searching for young stellar groups with machine-learning methods

• Grant number: 23/15776-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: January 01, 2024
• End date: December 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Astronomy - Positional Astronomy and Celestial Mechanics
• Principal Investigator: Phillip Andreas Brenner Galli
• Grantee: Breno Popowicz Pereira
• Host Institution: Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 20/12518-8 - Dynamics and evolution of Young Stellar Clusters (DYSC), AP.JP

Abstract

Astronomy is experiencing a rapid growth in data volume and complexity with the operationof several large-scale astrometric, photometric and spectroscopic surveys. The useof machine-learning methods combining data from different surveys is the key to makenew discoveries. This project aims to identify new young stellar groups in the Solar neighbourhood by searching for over-densities of stars in the space of parameters that definethe spatial distribution, kinematics and age of stellar clusters. The student will combine thephotometric data available from different surveys to select young stellar candidates, anduse the high-precision astrometry delivered by the Gaia satellite to group the young stellarcandidates that share the same kinematic properties using clustering methods. The newyoung stellar groups identified in this study will be later investigated in the DYSC projectand monitored with follow-up observations to better characterise them.