Polycyclic Aromatic Hydrocarbons in Seyfert and star-forming galaxies
I. Garc\'ia-Bernete (1), D. Rigopoulou (1), A. Alonso-Herrero (2), M., Pereira-Santaella (3), P. F. Roche (1), and B. Kerkeni (1,4,5) ((1), Department of Physics, University of Oxford, (2) Centro de Astrobiolog\'ia,, CSIC-INTA, Madrid, Spain, (3) Centro de Astrobiolog\'ia

TL;DR
This study compares PAH emission features in Seyfert and star-forming galaxies, revealing differences in molecular size, charge, and radiation environment, with implications for understanding galaxy nuclear activity and star formation.
Contribution
It introduces a new diagnostic model grid for PAH molecules based on theoretical spectra, enabling better differentiation of PAH properties in various galactic environments.
Findings
Star-forming and AGN galaxies occupy distinct regions in PAH diagnostic diagrams.
AGN-dominated systems show PAH ratios indicating larger, neutral PAH molecules.
Extended PAH emission in Seyfert galaxies resembles that of star-forming regions.
Abstract
Polycyclic Aromatic Hydrocarbons (PAHs) are carbon-based molecules resulting from the union of aromatic rings and related species, which are likely responsible for strong infrared emission features (3.3, 6.2, 7.7, 8.6, 11.3 and 12.7 microns). In this work, using a sample of 50 Seyfert galaxies (DL<100 Mpc) we compare the circumnuclear (inner kpc) PAH emission of AGN to that of a control sample of star-forming galaxies (22 luminous infrared galaxies and 30 HII galaxies), and investigate the differences between central and extended PAH emission. Using Spitzer/InfraRed Spectrograph spectral data of Seyfert and star-forming galaxies and newly developed PAH diagnostic model grids, derived from theoretical spectra, we compare the predicted and observed PAH ratios. We find that star-forming galaxies and AGN-dominated systems are located in different regions of the PAH diagnostic diagrams. This…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
