Unveil Galaxy Evolution using Big Data

Prof. Huanian Zhang’s main research interest is on the galaxy formation and evolution, specifically on studying the circumgalactic medium, high redshift quasars and the low mass systems to understand the galaxy evolution. Prof. Zhang got his bachelor in Physics from Shandong University in 2011 and the PhD from the University of Arizona in Physics in 2016. After that, he moved to the Steward Observatory at the University of Arizona as a postdoc fellow until 2021. In September 2021, Prof. Zhang joined HUST as an associate professor.The astronomical research has entered the era of big data. New methods to explore big data such as stacking large amount of data and machine learning algorithms are becoming more and more important and urgent. In this talk, I will discuss how we study the galaxy evolution using big data from different physical scales. At the circumgalactic scale (~ 200 kpc), I will discuss how we study the circumgalactic mediun (CGM) using large spectroscopic surveys. The CGM harbors more than 80% of the total baryons in a galaxy and is both the reservoir of gas for subsequent star formation and the depository of chemically processed gas, energy, and angular momentum from feedback. At the galactic scale (~ few kpc), I will present the all-sky search for dwarf galaxies in the local Universe using the DESI Imaging Legacy Survey and WISE data via the machine learning technique. The local dwarf galaxies are key to understand the formation and evolution of galaxies and the dark matter. Soon, large imaging and spectroscopy surveys will help revolutionize our understanding of the galaxy evolution.