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2004 Contini, De Lucia & Borgani 2012) and a substantial part of the host halo has formed from disrupted subhalo material (e.g. We are certain that between 5 and 10 per cent of the material within simulated galactic sized haloes exists within bound substructures (e.g. 2011 Kolchin, Bullock & Kaplinghat 2012), while differences between the simulated and observed internal density profiles of the satellites seem to have been reconciled by taking baryonic effects into account (e.g. The mass and radial position of the most massive Milky Way satellites seem to raise new concerns for our standard Λ cold dark matter cosmology ( Boylan-Kolchin, Bullock & Kaplinghat 2011 di Cintio et al.
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2009 Zavala, Springel & Boylan-Kolchin 2010) and the apparent overabundance of substructure within numerical models when compared to observations ( Klypin et al. The fraction of material that remains undispersed and so survives as separate structures within larger haloes is an important quantity for both studies of dark matter (DM) detection ( Kuhlen, Diemand & Madau 2008 Springel et al. Knowing the properties of substructure created in cosmological N-body simulations allows the most direct comparison between these simulations and observations of the Universe. However, the memory of the existence of these substructures is not immediately erased, either in the observable Universe (where thousands of individual galaxies within a galaxy cluster are obvious markers of this pre-existing structure) or within numerical models, first noted for the latter by Klypin et al. As larger structures grow they subsume small infalling objects.
Group subsume regroup taba series#
The growth of structure via a hierarchical series of mergers is now a well-established paradigm ( White & Rees 1978). Methods: numerical, galaxies: evolution, galaxies: haloes, cosmology: theory, dark matter 1 INTRODUCTION 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. 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. 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. For properties that rely on particles near the outer edge of the subhalo the agreement is at around the 20 per cent level. the maximum value of the rotation curve). 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. We extract quantitative and comparable measures for the subhaloes, primarily focusing on mass and the peak of the rotation curve for this particular study. A common post-processing pipeline was used to uniformly analyse the particle lists provided by each finder. 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. These finders span a wide range of techniques and methodologies to extract and quantify substructures within a larger non-homogeneous background density (e.g.
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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.