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BPT Diagrams and LINER Emission Origins Using Machine Learning

MonashPhysicsAndAstronomy via YouTube

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Overview

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Watch an in-depth astronomy lecture exploring the analysis of SDSS-IV MaNGA database containing spatially resolved spectra from approximately 10,000 galaxies to understand emission properties of ionizing sources. Learn how BPT diagram classification schemes and machine learning tool Spender are used to identify dominant ionization mechanisms by analyzing spectral information beyond strong emission lines. Discover findings that reveal LINER-like emission spectra can be distinguished through stellar absorption features connected to old, metal-rich stellar components, supporting previous research suggesting LINER emission may be driven by populations of old low-mass evolved stars.

Syllabus

Deeper dive into BPT diagrams and the origin of LINER emission with machine learning - Ahmad Nemer

Taught by

MonashPhysicsAndAstronomy

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