Abstract

Contributed Talk - Splinter Computation

Friday, 25 September 2020, 16:15   (virtual room B)

Constraining the merging timescales of close galaxy pairs through empirical modelling

Joseph O'Leary^1, Benjamin Moster^1, Eva Krämer^2
1: USM/LMU, 2: FAU

In the hierarchical picture of galaxy formation, mergers play a critical role in the formation and continued evolution of galaxies. Consequently, the galaxy-galaxy merger rate and its dependence on stellar mass, mass ratio, and redshift are of fundamental interest. Theoretical models are a vital component to exploring the galaxy merger process, and recent advances in modelling have placed tight constraints on buildup of stellar material in galaxies across cosmic time. Despite these successes, extracting the merger rates from observables remains a challenge. Differences in modelling techniques combined with limited observational data drive conflicting conclusions on the merging timescales of close pairs. We employ classical and machine learning techniques to probe the dependencies of pair merging probabilities and merging timescales. Further, we provide formulations useful to observers for extracting merger rates under a broad range of pair selection criteria.