Identifying Key Drivers of High-Redshift Brightest Cluster Galaxy Evolution Using Machine Learning Techniques

Overview

The assembly of Brightest Cluster Galaxies (BCGs) is commonly attributed to hierarchical mergers at low redshift, yet the mechanisms governing their early-universe growth remain poorly quantified. This study examines the relative influence of internal baryonic processes and environmental accretion at high redshift Brightest Cluster Galaxies using the IllustrisTNG-Cluster simulation. BCG progenitors were tracked from z = 4 to z = 1.5, with a focused analysis of 501 galaxies at z = 3, a physically motivated epoch preceding merger-dominated assembly. A Random Forest regression framework was then developed to identify the drivers of BCG growth across five fundamental indicators: stellar mass, star formation rate, half-mass radius, metallicity, and gas fraction. Model performance was optimized in two stages using R^2 metrics, first by evaluating temporal subsets and then by integrating satellite-based features to isolate environmental effects. Feature importance rankings were then used to interpret the physical pathways through which internal processes regulate stellar mass assembly. Results show that at z = 3, In-situ stellar mass emerges as the primary predictor of mass buildup(Spearman ? = 0.968) and strongly correlates with metallicity(? = 0.886) and gas fraction(? = -0.552), indicating an established gas–star formation–enrichment feedback cycle. Moreover, elevated metallicity is consistent with cooling efficiency and promotes compact structure formation(? = -0.531). Satellite galaxy and external merger contributions remain subdominant at this epoch. These results provide quantitative evidence that high-redshift BCGs evolve primarily as internally regulated systems, refining the merger-centric framework of massive galaxy formation.

Awards (1)

• Fourth Award of $600 $600

Competition history

• ISEF 2026 Physics and Astronomy · Entry PHYS009

Resources

• ISEF abstract page ↗

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