Speaker: Randa Asad (American University of Sharjah)

Abstract: I will present the different techniques our group used to obtain the age, metallicity and detailed abundances of star clusters in the Milky Way and the Magellanic Cloud. The first part of my talk will focus on using XShooter/VLT IR spectra of RSG to obtain the metallicity of newly discovered young star clusters in the inner Milky Way. The second part will discuss the first detailed chemical abundances of three star clusters in the Large Magellanic Cloud (LMC), NGC1831 , NGC1856  and [SL63]268  using integrated-light spectroscopic observations obtained with the Magellan Echelle spectrograph on Magellan Baade telescope. And finally I will present the first application of the novel approach based on data-driven machine learning methods applied to MUSE field data to derive stellar abundances of star clusters. MUSE has been used to target more than 10,000 fields, and it is unique in its ability to study dense stellar fields such as stellar clusters providing spectra for each individual star. The revolutionary combination of integral-field spectroscopy and data-driven modeling will allow us to understand the chemical enrichment of star clusters and their host galaxies in greater detail expanding our understanding of galaxy evolution.