Stability and convergence of N-body simulations for galaxy formation

Galaxy formation is still a current topic in astronomy. An important tool to understanding it is through simulation, which allows galaxies to be studied from all angles and across time. It allows us to explore the gap between observation and theory, but only if the results are sufficiently accurate. In this thesis I look at the majority of the simulation pipeline from running through the various stages of analysis, and some of the limits of their accuracy, and the fidelity of the subsequent analysis tools. It starts by looking at running simulations from initial conditions, and what influence changing parameters and simulation engines has on the outcome. Then I look in detail at how successful subhalo detection is by comparing a number of substructure finders, and examining their strengths and weaknesses. Following this I focus on a single parameter recovered for such haloes, the spin, and how well it was recovered, and what it tells us about the spin of substructures. Following this I investigated the building of merger trees, by writing my own merger tree program, and comparing it with some of the established ones. Then I look at using these processes as input to semi-analytic models, and how mass changes could affect the outcome. Finally I used a number of these tools to investigate the fate of some of the larger haloes formed at early times in an attempt to show where ultra-compact dwarf galaxies are formed and their fate

Stability and convergence of N-body simulations for galaxy formation

Galaxy formation is still a current topic in astronomy. An important tool to understanding it is through simulation, which allows galaxies to be studied from all angles and across time. It allows us to explore the gap between observation and theory, but only if the results are sufficiently accurate. In this thesis I look at the majority of the simulation pipeline from running through the various stages of analysis, and some of the limits of their accuracy, and the fidelity of the subsequent analysis tools. It starts by looking at running simulations from initial conditions, and what influence changing parameters and simulation engines has on the outcome. Then I look in detail at how successful subhalo detection is by comparing a number of substructure finders, and examining their strengths and weaknesses. Following this I focus on a single parameter recovered for such haloes, the spin, and how well it was recovered, and what it tells us about the spin of substructures. Following this I investigated the building of merger trees, by writing my own merger tree program, and comparing it with some of the established ones. Then I look at using these processes as input to semi-analytic models, and how mass changes could affect the outcome. Finally I used a number of these tools to investigate the fate of some of the larger haloes formed at early times in an attempt to show where ultra-compact dwarf galaxies are formed and their fate

Streams Going Notts: The tidal debris finder comparison project

While various codes exist to systematically and robustly find haloes and subhaloes in cosmological simulations (Knebe et al., 2011, Onions et al., 2012), this is the first work to introduce and rigorously test codes that find tidal debris (streams and other unbound substructure) in fully cosmological simulations of structure formation. We use one tracking and three non-tracking codes to identify substructure (bound and unbound) in a Milky Way type simulation from the Aquarius suite (Springel et al., 2008) and post-process their output with a common pipeline to determine the properties of these substructures in a uniform way. By using output from a fully cosmological simulation, we also take a step beyond previous studies of tidal debris that have used simple toy models. We find that both tracking and non-tracking codes agree well on the identification of subhaloes and more importantly, the {\em unbound tidal features} associated with them. The distributions of basic properties of the total substructure distribution (mass, velocity dispersion, position) are recovered with a scatter of $\sim20$. Using the tracking code as our reference, we show that the non-tracking codes identify complex tidal debris with purities of $\sim40$. Analysing the results of the substructure finders, we find that the general distribution of {\em substructures} differ significantly from the distribution of bound {\em subhaloes}. Most importantly, both bound and unbound {\em substructures} together constitute $\sim18$ of the host halo mass, which is a factor of $\sim2$ higher than the fraction in self-bound {\em subhaloes}. However, this result is restricted by the remaining challenge to cleanly define when an unbound structure has become part of the host halo. Nevertheless, the more general substructure distribution provides a more complete picture of a halo's accretion history.Comment: 19 pages, 12 figures, accepted for publication in MNRA

Galaxies going MAD: The Galaxy-Finder Comparison Project

With the ever increasing size and complexity of fully self-consistent simulations of galaxy formation within the framework of the cosmic web, the demands upon object finders for these simulations has simultaneously grown. To this extent we initiated the Halo Finder Comparison Project that gathered together all the experts in the field and has so far led to two comparison papers, one for dark matter field haloes (Knebe et al. 2011), and one for dark matter subhaloes (Onions et al. 2012). However, as state-of-the-art simulation codes are perfectly capable of not only following the formation and evolution of dark matter but also account for baryonic physics (e.g. hydrodynamics, star formation, feedback) object finders should also be capable of taking these additional processes into consideration. Here we report on a comparison of codes as applied to the Constrained Local UniversE Simulation (CLUES) of the formation of the Local Group which incorporates much of the physics relevant for galaxy formation. We compare both the properties of the three main galaxies in the simulation (representing the MW, M31, and M33) as well as their satellite populations for a variety of halo finders ranging from phase-space to velocity-space to spherical overdensity based codes, including also a mere baryonic object finder. We obtain agreement amongst codes comparable to (if not better than) our previous comparisons, at least for the total, dark, and stellar components of the objects. However, the diffuse gas content of the haloes shows great disparity, especially for low-mass satellite galaxies. This is primarily due to differences in the treatment of the thermal energy during the unbinding procedure. We acknowledge that the handling of gas in halo finders is something that needs to be dealt with carefully, and the precise treatment may depend sensitively upon the scientific problem being studied.Comment: 14 interesting pages, 17 beautiful figures, and 2 informative tables accepted for publication in MNRAS (matches published version

Sussing merger trees: a proposed merger tree data format

We propose a common terminology for use in describing both temporal merger trees and spatial structure trees for dark-matter halos. We specify a unified data format in HDF5 and provide example I/O routines in C, FORTRAN and PYTHON

Sussing merger trees: the Merger Trees Comparison Project

Merger trees follow the growth and merger of dark-matter haloes over cosmic history. As well as giving important insights into the growth of cosmic structure in their own right, they provide an essential backbone to semi-analytic models of galaxy formation. This paper is the first in a series to arise from the Sussing Merger Trees Workshop in which 10 different tree-building algorithms were applied to the same set of halo catalogues and their results compared. Although many of these codes were similar in nature, all algorithms produced distinct results. Our main conclusions are that a useful merger-tree code should possess the following features: (i) the use of particle IDs to match haloes between snapshots; (ii) the ability to skip at least one, and preferably more, snapshots in order to recover subhaloes that are temporarily lost during merging; (iii) the ability to cope with (and ideally smooth out) large, temporary fluctuations in halo mass. Finally, to enable different groups to communicate effectively, we defined a common terminology that we used when discussing merger trees and we encourage others to adopt the same language. We also specified a minimal output format to record the results

Sussing merger trees: the influence of the halo finder

Merger tree codes are routinely used to follow the growth and merger of dark matter haloes in simulations of cosmic structure formation. Whereas in Srisawat et. al. we compared the trees built using a wide variety of such codes, here we study the influence of the underlying halo catalogue upon the resulting trees. We observe that the specifics of halo finding itself greatly influences the constructed merger trees. We find that the choices made to define the halo mass are of prime importance. For instance, amongst many potential options different finders select self-bound objects or spherical regions of defined overdensity, decide whether or not to include substructures within the mass returned and vary in their initial particle selection. The impact of these decisions is seen in tree length (the period of time a particularly halo can be traced back through the simulation), branching ratio (essentially the merger rate of subhaloes) and mass evolution. We therefore conclude that the choice of the underlying halo finder is more relevant to the process of building merger trees than the tree builder itself. We also report on some built-in features of specific merger tree codes that (sometimes) help to improve the quality of the merger trees produced

Subhaloes gone Notts: the clustering properties of subhaloes

We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and study their differences in the density profile, mass fraction and two-point correlation function of subhaloes in haloes. We also study the mass and vmax dependence of subhalo clustering. As the Aquarius Simulation has been run at different resolutions, we study the convergence with higher resolutions. We find that the agreement between finders is at around the 10 per cent level inside R200 and at intermediate resolutions when a mass threshold is applied, and better than 5 per cent when vmax is restricted instead of mass. However, some discrepancies appear in the highest resolution, underlined by an observed resolution dependence of subhalo clustering. This dependence is stronger for the smallest subhaloes, which are more clustered in the highest resolution, due to the detection of subhaloes within subhaloes (the sub-subhalo term). This effect modifies the mass dependence of clustering in the highest resolutions. We discuss implications of our results for models of subhalo clustering and their relation with galaxy clustering

Sussing merger trees: stability and convergence

Merger trees are routinely used to follow the growth and merging history of dark matter haloes and subhaloes in simulations of cosmic structure formation. Srisawat et al. compared a wide range of merger-tree-building codes. Here we test the influence of output strategies and mass resolution on tree-building. We find that, somewhat surprisingly, building the tree from more snapshots does not generally produce more complete trees; instead, it tends to shorten them. Significant improvements are seen for patching schemes that attempt to bridge over occasional dropouts in the underlying halo catalogues or schemes that combine the halo-finding and tree-building steps seamlessly. The adopted output strategy does not affect the average number of branches (bushiness) of the resultant merger trees. However, mass resolution has an influence on both main branch length and the bushiness. As the resolution increases, a halo with the same mass can be traced back further in time and will encounter more small progenitors during its evolutionary history. Given these results, we recommend that, for simulations intended as precursors for galaxy formation models where of the order of 100 or more snapshots are analysed, the tree-building routine should be integrated with the halo finder, or at the very least be able to patch over multiple adjacent snapshots

Solving the puzzle of subhalo spins

Investigating the spin parameter distribution of subhalos in two high-resolution isolated halo simulations, recent work by Onions et al. suggested that typical subhalo spins are consistently lower than the spin distribution found for field halos. To further examine this puzzle, we have analyzed simulations of a cosmological volume with sufficient resolution to resolve a significant subhalo population. We confirm the result of Onions et al. and show that the typical spin of a subhalo decreases with decreasing mass and increasing proximity to the host halo center. We interpret this as the growing influence of tidal stripping in removing the outer layers, and hence the higher angular momentum particles, of the subhalos as they move within the host potential. Investigating the redshift dependence of this effect, we find that the typical subhalo spin is smaller with decreasing redshift. This indicates a temporal evolution, as expected in the tidal stripping scenario