Open clusters (OCs) are cradles of stars and building blocks of galaxies, offering insights into how stars and galaxies form. It is essential to precisely measure the parameters of OCs, such as age, metallicity, distance, dust extinction, stellar mass function (MF), and binary fraction. I propose a novel Bayesian framework that can identify OC candidates and simultaneously estimate these parameters with unprecedented precision, even for highly contaminated samples. Applied to Gaia photometric data, this method yields a comprehensive catalog of OC parameters, including the MF and binary properties, previously unattainable with conventional methods. I will discuss the progress in understanding OC dynamics as reflected by the temporal and radial dependence of MF and binary properties, and the influence of the Galactic environment. This framework can also be extended to incorporate stellar rotation, blue stragglers, and multi-stellar populations.
https://ui.adsabs.harvard.edu/public-libraries/51HATpbMQnS7c7aTOCUzsQ
BIO
Dr. Lu Li (李璐) is an assistant researcher at Shanghai Astronomical Observatory since 2023. She received her Ph.D. from SHAO in 2022. Her research focuses on various aspects of open clusters and data mining in sky surveys, especially Gaia data. Dr. Li has received multiple prestigious awards, including the Special Prize of President's Award from the Chinese Academy of Sciences (中科院院长特别奖) and the title of Young Data Scientist at the Chinese National Astronomical Data Center.
