The formation and disruption of globular cluster populations in simulations of present-day $L^{\ast }$ galaxies with controlled assembly histories

Abstract

Globular clusters (GCs) are sensitive tracers of galaxy assembly histories but interpreting the information they encode is challenging because mergers are thought to promote both the formation and disruption of GCs. We use simulations with controlled merger histories to examine the influence of merger mass ratio on the GC population of a present-day $L^{\ast }$ galaxy, using the genetic modification technique to adjust the initial conditions of a galaxy that experiences major mergers at $z=1.7$ and $0.77$ (ORGANIC case), so the later merger has twice its original mass ratio (ENHANCED case), or is prevented from occurring (SUPPRESSED case). We evolve the three realizations with E-MOSAICS (MOdelling Star cluster population Assembly In Cosmological Simulations with EAGLE), which couples subgrid star cluster formation and evolution models to the EAGLE (Evolution and assembly of GaLaxies and their Environments) galaxy formation model. Relative to the ORGANIC case, the mass of surviving GCs is elevated (reduced) in the ENHANCED (SUPPRESSED) case, indicating that major mergers promote a net boost to the GC population. The boost is clearly quantified by the GC specific mass because it is sensitive to the number of the most massive GCs, whose long characteristic disruption time-scales enable them to survive their hostile natal environments. In contrast, the specific frequency is insensitive to assembly history because it primarily traces low-mass GCs that tend to be disrupted soon after their formation. The promotion of GC formation and disruption by major mergers imprints a lasting and potentially observable signature: an elevated mass fraction of field stars in the galaxy's stellar halo that were born in star clusters.

arXiv comment17 pages, 8 figures. Accepted by MNRAS. A repository of reduced data and scripts to reproduce the results in this manuscript is available at https://github.com/Musical-Neutron/gc-gmics and archived at https://doi.org/10.5281/zenodo.16614763

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