Subhaloes going Notts: the subhalo‐finder comparison project

By Julian Onions, A. Knebe, Frazer R. Pearce, S. I. Muldrew, H. Lux, S. Knollmann, Y. Ascasibar, P. Behroozi, P. Elahi, Jiaxin Han and 7 more. 2012

141 citations recorded by the source corpus.

We present a detailed comparison of the substructure properties of a single Milky Way sized dark matter halo from the Aquarius suite at five different resolutions, as identified by a variety of different (sub)halo finders for simulations of cosmic structure formation. These finders span a wide range of techniques and methodologies to extract and quantify substructures within a larger non-homogeneous background density (e.g. a host halo). This includes real-space-, phase-space-, velocity-space- and time-space-based finders, as well as finders employing a Voronoi tessellation, Friends-of-Friends techniques or refined meshes as the starting point for locating substructure. A common post-processing pipeline was used to uniformly analyse the particle lists provided by each finder. We extract quantitative and comparable measures for the subhaloes, primarily focusing on mass and the peak of the rotation curve for this particular study. We find that all of the finders agree extremely well in the presence and location of substructure and even for properties relating to the inner part of the subhalo (e.g. the maximum value of the rotation curve). For properties that rely on particles near the outer edge of the subhalo the agreement is at around the 20 per cent level. We find that the basic properties (mass and maximum circular velocity) of a subhalo can be reliably recovered if the subhalo contains more than 100 particles although its presence can be reliably inferred for a lower particle number limit of 20. We finally note that the logarithmic slope of the subhalo cumulative number count is remarkably consistent and <1 for all the finders that reached high resolution. If correct, this would indicate that the larger and more massive, respectively, substructures are the most dynamically interesting and that higher levels of the (sub)subhalo hierarchy become progressively less important.

Subfields: Astronomy and Astrophysics, Ecology, Instrumentation

View Paper: https://www.semanticscholar.org/paper/5907559a1dec7b63d0ba98bf0fe374e82b0656c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

In Ecology

In Instrumentation

Citations in the corpus

THE CONNECTION BETWEEN GALAXIES AND DARK MATTER STRUCTURES IN THE LOCAL UNIVERSE (2012, background): “This halo finder produces results that are comparable to other modern halo finders (e.g. BDM and AHF) on small scales; the use of phase space information allows it to track subhalos better in the inner regions of their hosts (Knebe et al. 2011; Onions et al. 2012; Behroozi et al. 2013a).”
Dark Matter Substructure in Numerical Simulations: A Tale of Discreteness Noise, Runaway Instabilities, and Artificial Disruption (2018, background): “In particular, a number of resolution and comparison studies (e.g., Springel et al. 2008; Onions et al. 2012; Knebe et al. 2013; van den Bosch & Jiang 2016; Griffen et al. 2016) have c© 2013 The Authors shown that subhalo mass functions are converged1 down to 50-100 particles per subhalo.”
Disruption of Dark Matter Substructure: Fact or Fiction? (2017, background): “This notion is based on the fact that simulations seem to yield consistent, converged results for the mass function of subhaloes above this mass resolution limit (e.g., Springel et al. 2008; Onions et al. 2012; Knebe et al. 2013; Cautun et al. 2014; van den Bosch & Jiang 2016; Griffen et al. 2016).”
The current status of galaxy formation (2012, background): “Cosmological simulations, with up to 108 particles, are becoming increasingly common, but are intensive to process, in particular to detect halos (Knebe et al., 2011 and references therein) and subhalos (Onions et al., 2012 and references therein) and build halo merger trees.”
UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10 (2018, methodology): “Satellites are problematic for both approaches, as neither satellite mass accretion nor concentration are robustly measured by halo finders (Onions et al. 2012; Behroozi et al. 2015b), and most solutions (e.g., using the time since accretion; Moster et al. 2018) cannot capture orbit-dependent…”
Structure finding in cosmological simulations: the state of affairs (2013, methodology): “Most of the codes discussed in Onions et al. (2012) calculate φ using a tree, whereas others make simplifying assumptions such as spherical symmetry (AHF) or detailed Downloaded from https://academic.oup.com/mnras/article-abstract/435/2/1618/1043579 by guest on 29 November 2017 surmises about the…”