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Hierarchical models of structure formation predict that dark matter haloassembly histories are characterised by episodic mergers and interactions withother haloes. An accurate description of this process will provide insightsinto the dynamical evolution of haloes and the galaxies that reside in them.Using large cosmological N-body simulations, we characterise halo orbits tostudy the interactions between substructure haloes and their hosts, and howdifferent evolutionary histories map to different classes of orbits. We use twonew software tools - WhereWolf, which uses halo group catalogues and mergertrees to ensure that haloes are tracked accurately in dense environments, andOrbWeaver, which quantifies each halo's orbital parameters. We demonstrate howWhereWolf improves the accuracy of halo merger trees, and we use OrbWeaver toquantify orbits of haloes. We assess how well analytical prescriptions for themerger timescale from the literature compare to measured merger timescales fromour simulations and find that existing prescriptions perform well, provided theratio of substructure-to-host mass is not too small. In the limit of smallsubstructure-to-host mass ratio, we find that the prescriptions canoverestimate the merger timescales substantially, such that haloes arepredicted to survive well beyond the end of the simulation. This workhighlights the need for a revised analytical prescription for the mergertimescale that more accurately accounts for processes such as catastrophictidal disruption.

Extracting galaxy merger timescales I: Tracking haloes with WhereWolf and spinning orbits with OrbWeaver