Star Formation Histories of Galaxies Near and Far
Offered By: Kavli Institute for Theoretical Physics via YouTube
Course Description
Overview
Explore the intricacies of star formation histories in galaxies both nearby and distant in this 25-minute conference talk by Eric Gawiser from Rutgers University. Delve into the application of astrostatistics and machine learning tools to galaxy formation and evolution. Discover how Integral Field Unit surveys are revolutionizing our understanding by producing hundreds of spectra per galaxy across tens of thousands of galaxies. Learn about the wealth of information contained in galaxy morphology through imaging data, down to the pixel level and across various wavelengths. Examine how statistical and machine learning-powered outlier detection algorithms are uncovering anomalous galaxies that challenge current paradigms, and how this trend will accelerate with upcoming projects like Rubin, DESI, Roman, Euclid, and the SKA. Gain insights into the crucial role of data science tools in linking observations with theoretical models, including cosmological hydrodynamical simulations and semi-analytic or empirical models built on dark matter-only simulations.
Syllabus
Star Formation Histories of Galaxies Near and Far ▸ Eric Gawiser (Rutgers)
Taught by
Kavli Institute for Theoretical Physics
Related Courses
Dust Properties of Galaxies from a Data-Driven Hierarchical Model - John ForbesKavli Institute for Theoretical Physics via YouTube Computational and AI Funding Opportunities - Andreas Berlind (NSF)
Kavli Institute for Theoretical Physics via YouTube Galaxy Zoo in the Deep Learning Era - Mike Walmsley
Kavli Institute for Theoretical Physics via YouTube Galaxy Merger Reconstruction with Generative Graph Neural Networks - Yuan Sen Ting
Kavli Institute for Theoretical Physics via YouTube Finding Environmental Measures Sensitive to Halo Properties Using Neural Networks
Kavli Institute for Theoretical Physics via YouTube