What is Important? Morphological Asymmetries are Useful Predictors of Star Formation Rates of Star-forming Galaxies in SDSS Stripe 82
Hassen M. Yesuf, Luis C. Ho, and S.M. Faber

TL;DR
This study uses mutual information to identify key structural features like asymmetry and bulge prominence that predict star formation rates in galaxies, revealing complex dependencies beyond stellar mass.
Contribution
It introduces a mutual information framework to quantify and rank galaxy structural variables' relevance for star formation, highlighting asymmetry as a crucial predictor.
Findings
Asymmetry is the most powerful predictor of SSFR after stellar mass.
Galaxies with higher asymmetry and bulge prominence have higher SSFR.
Structural perturbations and irregularities are linked to increased star formation.
Abstract
Morphology and structure of galaxies reflect their star formation and assembly histories. We use the framework of mutual information () to quantify interdependence among several structural variables and to rank them according to their relevance for predicting specific star formation rate (SSFR) by comparing the of the predictor variables with SSFR and penalizing variables that are redundant. We apply this framework to study face-on star-forming galaxies (SFGs) with varying degrees of bulge dominance and central concentration and with stellar mass at redshift . We use the Sloan Digital Sky Survey (SDSS) Stripe 82 deep -band imaging data, which improve measurements of asymmetry and bulge dominance indicators. We find that star-forming galaxies are a multi-parameter family.…
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