演講資訊

摘要：

The so-called galaxy--halo connection is a vast topic concerning how galaxies populate their host dark matter halos. I will present some progresses we have made under this grand theme, including (1) the detection of assembly bias signal with the help of constrained simulation Elucid, (2) a subhalo abundance matching scheme that utilizes a new dark matter halo property, which is shown to perform better than the popular V_peak model, (3) a graphic neural network model that can accurately predict the stellar mass and color of galaxies at redshift z=0-5 based purely on dark matter subhalo properties along the whole merger tree, and (4) a novel way of studying cluster galaxy population evolution that fully takes into account the scatter in the mass--observable relation.