Abstract Details
| Name: BharatKumar Yerra Affiliation: National Astronomical Observatories of China Conference ID: ASI2019_407 Title : Identifying Li-rich giants from LAMOST low resolution spectra using machine learning Authors and Co-Authors : Y. Bharat Kumar, G. Vigeesh, Raghubar Singh Abstract Type : Oral Abstract Category : Stars, ISM and Galaxy Abstract : Less than 200 giants are known to show anomalous high Li abundances in their photospheres, indicating the rarity of Li-rich giants in the universe. LAMOST survey provides millions of low resolution (R$\sim$1800) spectra of stars in the Milky Way, which enables to perform systematic search for these rare class of giants. Based on Li abundances derived from line ratio method (Kumar et al. 2018) we selected 1000 good quality spectra of Li-rich giants with Li abundances ranging from 1.7 to 4.5 dex. We use this as a training set to fit a supervised classification model and estimate Li abundances for 1 million spectra of giants from LAMOST. Results increased the Li-rich giant candidates to 10 fold to the existing catalog of Li-rich stars, which puts strong constraints on statistical distribution of Li in giants. The candidates present in this new catalog would be worthwhile exploring for detail abundance analysis of various elements based on high resolution spectra, which will put constraints on Li origin in giants and Galactic Li evolution. |