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Deep Learning Algorithm for Core-Collapse Supernova Detection

Offered By: Institute for Pure & Applied Mathematics (IPAM) via YouTube

Tags

Deep Learning Courses Astronomy Courses Machine Learning Courses Gravitational Waves Courses Multi-messenger Astrophysics Courses

Course Description

Overview

Explore a 37-minute lecture on developing deep learning algorithms for detecting core-collapse supernovae through gravitational waves. Delve into the exciting field of multi-messenger astronomy, focusing on how gravitational waves and neutrinos provide unique insights into extreme cosmic events. Discover the potential of these signals to reveal crucial information about supernova core dynamics, explosion mechanisms, protoneutron star evolution, core rotation rates, and the nuclear equation of state. Learn about the development and application of machine learning techniques to enhance gravitational wave signal detection from core-collapse supernovae, including results obtained from real detector noise data.

Syllabus

Irene Di Palma - Deep learning algorithm for core-collapse supernova detection


Taught by

Institute for Pure & Applied Mathematics (IPAM)

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