Abstract

Contributed Talk - Splinter GalaxyEvol

Friday, 13 September 2024, 14:30   (S21)

Identifying Dust/Molecular Structure in Nearby Galaxies using 7.7 micron JWST data

Zein Bazzi, Dario Colombo, Frank Bigiel
Argelander Institute for Astronomy

Molecular cloud identification algorithms have evolved from identifying clouds locally to extragalactically as instrumentation has improved. The James Webb Space Telescope has provided us with high-resolution, sub-GMC scale data for nearby galaxies. The emission of polycyclic aromatic hydrocarbons (PAHs) allows us to trace the structure of dust or molecular clouds. In our work, we use SCIMES (Spectral Clustering for Molecular Emission Segmentation), a machine-learning algorithm dedicated to identifying molecular clouds, to extract dust structures in 19 nearby galaxies from the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS) survey. In this presentation, I will show that the extracted dust structures might represent molecular clouds and emphasize the differences in cloud properties across different galactic environments.