An improved prescription for merger time-scales from controlled simulations

TL;DR

This paper evaluates existing analytical models for galaxy merger timescales against simulations, finds they underestimate high-redshift merger durations, and proposes a redshift-dependent correction improving predictions and impacting galaxy population models.

Contribution

It introduces a redshift-dependent modification to merger time prescriptions, enhancing their accuracy at high redshift based on simulation comparisons.

Findings

Existing prescriptions under-predict long merger times at high redshift.

Adding a redshift dependence improves merger time predictions significantly.

Modified prescription increases predicted low-mass galaxy survival by up to 25% at z=0.

Abstract

We compare three analytical prescriptions for merger times available from the literature to simulations of isolated mergers. We probe three different redshifts, and several halo concentrations, mass ratios, orbital circularities and orbital energies of the satellite. We find that prescriptions available in the literature significantly under-predict long timescales for mergers at high redshift. We argue that these results have not been highlighted previously either because the evolution of halo concentration of satellite galaxies has been neglected (in previous isolated merger simulations), or because long merger times and mergers with high initial orbital circularities are under-represented (for prescriptions based on cosmological simulations). Motivated by the evolution of halo concentration at fixed mass, an explicit dependence on redshift added as t_merger,modified(z) = (1+z)^0.44 t_merger to the prescription based on isolated mergers gives a significant improvement in the predicted merger times up to ~20 t_dyn in the redshift range 0<z<2. When this modified prescription is used to compute galaxy stellar mass functions, we find that it leads up to a 25 per cent increase in the number of low mass galaxies surviving at z=0, and a 10 per cent increase for more massive galaxies. This worsen the known over-prediction in the number of low mass galaxies by hierarchical models of galaxy formation.