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Using the EAGLE suite of simulations, we demonstrate that both cold gas stripping {\it and} starvation of gas inflow play an important role in quenching satellite galaxies across a range of stellar and halo masses, $M_{\star}$ and $M_{200}$. By quantifying the balance between gas inflows, outflows, and star formation rates, we show that even at $z=2$, only $\approx30\%$ of satellite galaxies are able to maintain equilibrium or grow their reservoir of cool gas - compared to $\approx50\%$ of central galaxies at this redshift. We find that the number of orbits completed by a satellite is a very good predictor of its quenching, even more so than the time since infall. On average, we show that intermediate-mass satellites with $M_{\star}$ between $10^{9}{\rm M}_{\odot}-10^{10}{\rm M}_{\odot}$ will be quenched at first pericenter in massive group environments, $M_{200}>10^{13.5}{\rm M}_{\odot}$; and will be quenched at second pericenter in less massive group environments, $M_{200}<10^{13.5}{\rm M}_{\odot}$. On average, more massive satellites ($M_{\star}>10^{10}{\rm M}_{\odot}$) experience longer depletion time-scales, being quenched between first and second pericenters in massive groups; while in smaller group environments, just $\approx30\%$ will be quenched even after two orbits. Our results suggest that while starvation alone may be enough to slowly quench satellite galaxies, direct gas stripping, particularly at pericenters, is required to produce the short quenching time-scales exhibited in the simulation., Comment: Accepted for publication in MNRAS

Predicting the merger timescale ($\tau_{\rm merge}$) of merging dark matter halos, based on their orbital parameters and the structural properties of their hosts, is a fundamental problem in gravitational dynamics that has important consequences for our understanding of cosmological structure formation and galaxy formation. Previous models predicting $\tau_{\rm merge}$ have shown varying degrees of success when compared to the results of cosmological $N$-body simulations. We build on this previous work and propose a new model for $\tau_{\rm merge}$ that draws on insights derived from these simulations. We find that published predictions can provide reasonable estimates for $\tau_{\rm merge}$ based on orbital properties at infall, but tend to underpredict $\tau_{\rm merge}$ inside the host virial radius ($R_{200}$) because tidal stripping is neglected, and overpredict it outside $R_{200}$ because the host mass is underestimated. Furthermore, we find that models that account for orbital angular momentum via the circular radius $R_{\rm circ}$ underpredict (overpredict) $\tau_{\rm merge}$ for bound (unbound) systems. By fitting for the dependence of $\tau_{\rm merge}$ on various orbital and host halo properties,we derive an improved model for $\tau_{\rm merge}$ that can be applied to a merging halo at any point in its orbit. Finally, we discuss briefly the implications of our new model for $\tau_{\rm merge}$ for semi-analytical galaxy formation modelling., Comment: 12 pages, 11 figures, accepted for publication in MNRAS

Resolving faint galaxies in large volumes is critical for accurate cosmic reionisation simulations. While less demanding than hydrodynamical simulations, semi-analytic reionisation models still require very large N-body simulations in order to resolve the atomic cooling limit across the whole reionisation history within box sizes $\gtrsim 100 \, h^{-1} {\rm Mpc}$. To facilitate this, we extend the mass resolution of N-body simulations using a Monte Carlo algorithm. We also propose a method to evolve positions of Monte Carlo halos, which can be an input for semi-analytic reionisation models. To illustrate, we present an extended halo catalogue that reaches a mass resolution of $M_\text{halo} = 3.2 \times 10^7 \, h^{-1} \text{M}_\odot$ in a $105 \, h^{-1} {\rm Mpc}$ box, equivalent to an N-body simulation with $\sim 6800^3$ particles. The resulting halo mass function agrees with smaller volume N-body simulations with higher resolution. Our results also produce consistent two-point correlation functions with analytic halo bias predictions. The extended halo catalogues are applied to the \textsc{meraxes} semi-analytic reionisation model, which improves the predictions on stellar mass functions, star formation rate densities and volume-weighted neutral fractions. Comparison of high resolution large volume simulations with both small volume or low resolution simulations confirms that both low resolution and small volume simulations lead to reionisation ending too rapidly. Lingering discrepancies between the star formation rate functions predicted with and without our extensions can be traced to the uncertain contribution of satellite galaxies., Comment: 15 pages, 15 figures. Accepted for publication in MNRAS

Linking the properties of galaxies to the assembly history of their dark matter haloes is a central aim of galaxy evolution theory. This paper introduces a dimensionless parameter $s\in[0,1]$, the "tree entropy", to parametrise the geometry of a halo's entire mass assembly hierarchy, building on a generalisation of Shannon's information entropy. By construction, the minimum entropy ($s=0$) corresponds to smoothly assembled haloes without any mergers. In contrast, the highest entropy ($s=1$) represents haloes grown purely by equal-mass binary mergers. Using simulated merger trees extracted from the cosmological $N$-body simulation SURFS, we compute the natural distribution of $s$, a skewed bell curve peaking near $s=0.4$. This distribution exhibits weak dependences on halo mass $M$ and redshift $z$, which can be reduced to a single dependence on the relative peak height $\delta_{\rm c}/\sigma(M,z)$ in the matter perturbation field. By exploring the correlations between $s$ and global galaxy properties generated by the SHARK semi-analytic model, we find that $s$ contains a significant amount of information on the morphology of galaxies $-$ in fact more information than the spin, concentration and assembly time of the halo. Therefore, the tree entropy provides an information-rich link between galaxies and their dark matter haloes., Comment: 20 pages, 18 figures

Hierarchical models of structure formation predict that dark matter halo assembly histories are characterised by episodic mergers and interactions with other haloes. An accurate description of this process will provide insights into the dynamical evolution of haloes and the galaxies that reside in them. Using large cosmological N-body simulations, we characterise halo orbits to study the interactions between substructure haloes and their hosts, and how different evolutionary histories map to different classes of orbits. We use two new software tools - WhereWolf, which uses halo group catalogues and merger trees to ensure that haloes are tracked accurately in dense environments, and OrbWeaver, which quantifies each halo's orbital parameters. We demonstrate how WhereWolf improves the accuracy of halo merger trees, and we use OrbWeaver to quantify orbits of haloes. We assess how well analytical prescriptions for the merger timescale from the literature compare to measured merger timescales from our simulations and find that existing prescriptions perform well, provided the ratio of substructure-to-host mass is not too small. In the limit of small substructure-to-host mass ratio, we find that the prescriptions can overestimate the merger timescales substantially, such that haloes are predicted to survive well beyond the end of the simulation. This work highlights the need for a revised analytical prescription for the merger timescale that more accurately accounts for processes such as catastrophic tidal disruption., Comment: 22 pages, 24 figures, accepted for publication in MNRAS

We present TreeFrog, a massively parallel halo merger tree builder that is capable comparing different halo catalogues and producing halo merger trees. The code is written in c++11, use the MPI and OpenMP API's for parallelisation, and includes python tools to read/manipulate the data products produced. The code correlates binding energy sorted particle ID lists between halo catalogues, determining optimal descendant/progenitor matches using multiple snapshots, a merit function that maximises the number of shared particles using pseudo-radial moments, and a scheme for correcting halo merger tree pathologies. Focusing on VELOCIraptor catalogues for this work, we demonstrate how searching multiple snapshots spanning a dynamical time significantly reduces the number of stranded halos, those lacking a descendant or a progenitor, critically correcting poorly resolved halos. We present a new merit function that improves the distinction between primary and secondary progenitors, reducing tree pathologies. We find FOF accretion rates and merger rates show similar mass ratio dependence. The model merger rates from Poole et al, (2017) agree with the measured net growth of halos through mergers., Comment: 18 pages in main text, 23 pages total, 15 figures, 3 tables. Accepted for publication in PASA. Code is available from https://www.github.com/pelahi/TreeFrog

We present VELOCIraptor, a massively parallel galaxy/(sub)halo finder that is also capable of robustly identifying tidally disrupted objects and separate stellar halos from galaxies. The code is written in c++11, use the MPI and OpenMP API's for parallelisation, and includes python tools to read/manipulate the data products produced. We demonstrate the power of the VELOCIraptor (sub)halo finder, showing how it can identify subhalos deep within the host that have negligible density contrasts to their parent halo. We find a subhalo mass-radial distance dependence: large subhalos with mass ratios of $\gtrsim10^{-2}$ are more common in the central regions that smaller subhalos, a result of dynamical friction and low tidal mass loss rates. This dependence is completely absent in (sub)halo finders in common use, which generally search for substructure in configuration space, yet is present in codes that track particles belonging to halos as they fall into other halos, such as HBT+. VELOCIraptor largely reproduces the dependence seen without tracking, finding a similar radial dependence to HBT+ in well resolved halos from our limited resolution fiducial simulation., Comment: 22 pages in main text, 33 pages total, 15 figures, 4 tables. Accepted for publication in PASA. Code available from https://www.github/pelahi/VELOCIraptor-STF

Merger trees harvested from cosmological $N$-body simulations encode the assembly histories of dark matter halos over cosmic time, and are a fundamental component of semi-analytical models (SAMs) of galaxy formation. The ability to compare the tools used to construct merger trees, namely halo finders and tree building algorithms, in an unbiased and systematic manner is critical to assess the quality of merger trees. In this paper, we present the dendogram, a novel method to visualise merger trees, which provides a comprehensive characterisation of a halo's assembly history - tracking subhalo orbits, halo merger events, and the general evolution of halo properties. We show the usefulness of the dendogram as a diagnostic tool of merger trees by comparing halo assembly histories from a single $N$-Body simulation analysed with three different halo-finders -\textsc{VELOCIraptor}, \textsc{AHF} and \textsc{Rockstar} - and their associated tree-builders. Based on our analysis of the resulting dendograms, we highlight how they have been used to motivate improvements to \textsc{VELOCIraptor}. The dendogram software is publicly available online, at: https://github.com/rhyspoulton/MergerTree-Dendograms ., Comment: 18 pages, 18 figures, accepted for publication in PASA