I work with the PHANGS-HST Multiscale Stellar Associations, as outlined in Larson et al. (2023). They are loosely bound stellar structures traced by resolved bright stars.
Traditional SED fitting with stellar population synthethis models has two problems:
- Age-reddening degeneracy;
- IMF sampling stochasticity—especially for lower mass stellar associations, a fully sampled IMF is not an accurate estimate. Stellar associations with the same mass can have different colors, if they have different fraction of red and blue stars.
Combined together (plus metallicity variations), they form a unsolvable three-way degeneracy. Advised by my mentors Dr. Kirsten Larson, Dr. David Thilker, and Dr. Janice Lee, I tackle this problem with:
- Independent extinction measure mesurement from the H-alpha to Paschen-alpha ratio, simialr to the Balmer decrement;
- Stellar population synthethis models with a stochastically sampled IMF by Dr. Stephane Charlot and Dr. Gustavo Bruzual (priv. comm.), based on their Bruzual & Charlot (2003) work.
I use NGC 4826 (Messier 64, the Black Eye Galaxy, Evil Eye Galaxy) as a pilot. The H-alpha image comes from HST WFC3/UVIS F675N, and Pa-a from JWST NIRCam F187N.
I then firmly fit the stellar assocations' SEDs with the extinction prior, using CIGALE. This part is still ongoing, and we hope to publish our result in early 2025. Below are some direct comparisons between tranditional SED fitting with deterministic models and with stochastic models.
I am exploring the possibility of a statistical/Bayesian approach of the stochastic SED modeling. More ongoing work: a corner plot visualizing a 3D PDF in mass, age, and reddening.
I will present my work at AAS 245 in National Harbor, MD, on Tuesday, January 14, 2025. I will be the first presenter in Session 222: Star Clusters II, from 10:00–10:10 AM in Gaylord 11.
I would love to hear your questions, comments, and suggestions! My email address is: qtian [at] jhu.edu.
I would love to hear your questions, comments, and suggestions! My email address is: qtian [at] jhu.edu.