YoVDO

How Supermassive Black Holes Ignite the Intergalactic Medium - Tales from the Low Redshift Lyman-alpha Forest

Offered By: Kavli Institute for Theoretical Physics via YouTube

Tags

Galaxy Formation Courses Data Science Courses Machine Learning Courses Outlier Detection Algorithms Courses Astrostatistics Courses

Course Description

Overview

Explore the impact of supermassive black holes on the intergalactic medium in this 31-minute lecture by Blakesley Burkhart from Rutgers University. Delve into the low redshift Lyman-alpha forest and discover how these cosmic giants influence the vast spaces between galaxies. Learn about the application of astrostatistics and machine learning tools in galaxy formation and evolution studies, and understand the potential of current and future Integral Field Unit surveys in producing extensive spectral data across thousands of galaxies. Gain insights into the use of data science tools for linking observations with theoretical models, including cosmological hydrodynamical simulations and dark matter-only simulations. Examine the role of statistical and machine learning-powered outlier detection algorithms in identifying anomalous galaxies that challenge current paradigms. Understand the significance of this research in the context of upcoming astronomical projects such as Rubin, DESI, Roman, Euclid, and the SKA. This talk is part of a conference organized by the Kavli Institute for Theoretical Physics, aimed at exploring data-driven tools to enhance our understanding of galaxy formation physics.

Syllabus

How Supermassive Black Holes Ignite the Intergalactic Medium... ▸ Blakesley Burkhart (Rutgers)


Taught by

Kavli Institute for Theoretical Physics

Related Courses

Introduction to Anomaly Detection in R
DataCamp
Dust Properties of Galaxies from a Data-Driven Hierarchical Model - John Forbes
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
Learning to Simulate the Universe with Deep Learning - Elena Giusarma
Kavli Institute for Theoretical Physics via YouTube