Abstract: Globular clusters are the relics of extreme star formation in high-redshift galaxies. Their enormous potential as tracers of high-redshift galaxy formation is broadly recognised, but concrete applications of this link have remained out of reach. The key missing ingredient has been to construct an end-to-end model for star cluster formation and evolution in a cosmological context. I will present results from the E-MOSAICS project, in which we carry out fully self-consistent, cosmological hydrodynamical simulations of the co-formation and evolution of globular clusters and their host galaxies. This work has led to two crucial insights. The first is that the formation of young massive clusters and old globular clusters can be described by a single modelling framework, showing that globular clusters are the relics of regular star formation in high-redshift environments. The second is that the high-pressure formation environment of globular clusters has shaped a wide range of their present-day properties, enabling their direct use as tracers of high-redshift galaxy growth. I will show how globular cluster metallicities, masses, ages, kinematics, and spatial distributions provide a new and exciting window for reconstructing the host galaxy merger history, distinguishing between in-situ and ex-situ galaxy growth, and probing the conditions of cloud-scale star formation and feedback at high redshift. Specifically, I will demonstrate the power of unifying cluster formation and destruction processes across cosmic time by using the E-MOSAICS simulations to derive the formation and assembly history of the Milky Way, culminating in the reconstruction of its merger tree. I will conclude with a discussion of current shortcomings of these simulations, and how we are combining observational, theoretical, and numerical work to remedy these through improved subgrid models for star formation, feedback, and globular cluster formation and evolution in the successor of E-MOSAICS named EMP-MOSAICS, using the moving-mesh code Arepo.
Host: Hui Li