Reconstructing chemical enrichment pathways in disc galaxies. A phylogenetic approach

Phylogenetic methods, traditionally used in biology to trace the evolutionary relationships among species, are emerging as a powerful framework to reconstruct evolutionary processes in galaxies from chemical information. We apply galactic phylogenetics to study the chemical evolution of stellar populations in distinct regions of a simulated disc galaxy, assessing its capability to unveil assembly histories. We used a high-resolution simulation that followed the chemical enrichment of an isolated disc galaxy by different stellar progenitors. We tracked gas particles as they turned into stars and inherited their parent gas chemical composition. Target particles were selected to store the chemical history of each chemical element considered in the simulation. Two regions were analysed: an inner ring, influenced by early bar-driven inflows, and an outer ring, shaped by spiral arms. We built phylogenetic trees for stellar populations in each region and quantified their structure using the Corrected Colless index, a standard metric of tree balance used in biology. The inner ring tree reveals a compact clade of old stars enriched by rapid Type II supernova (SNII) feedback, followed by a hierarchical sequence with increasing Type Ia supernova (SNIa) and asymptotic giant branch (AGB) contributions. In contrast, the outer ring exhibits more symmetric, caterpillar-like trees with smoother abundance gradients, consistent with more prolonged star formation and efficient local mixing. Chemical enrichment rates corroborate these trends, showing fast early enrichment in the inner ring and gradual, spatially extended enrichment in the outer disc. The structural indices differ significantly between the two regions and converge robustly even for modest stellar samples (N_ SSP = 100). Galactic phylogenetics provides a novel and complementary tool to decode the fossil record of galaxies. It captures distinct chemical pathways across galactic environments and offers quantitative metrics for comparing assembly histories purely from chemical abundances.