Physical vs. Data-Driven Approaches in the Era of Multi-Wavelength Astronomical Surveys

Abstract: We are entering the golden age of multi-wavelength astronomical surveys. In the 2020s, a plethora of multi-band surveys (such as Rubin-LSST, DESI, Simons Observatory, CMB-S4, and eROSITA, to name a few) are underway or planned to provide unprecedented insights into the cosmic structure formation and the fundamental physics of the cosmos. One of the key challenges of this cosmic frontier lies in understanding the halo-galaxy-gas connection and the roles of still poorly understood galaxy formation physics and its impact on cosmology. In this talk, I will discuss the roles of simulations and machine learning in advancing the forward modeling of big astronomical datasets, highlighting a few illustrative projects (including the NSF- funded CU-Yale collaborative project).