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相关论文: Generating Dark Matter Halo Merger Trees

200 篇论文

We study merger histories of dark-matter haloes in a suite of N-body simulations that span different cosmological models. The simulated cases include the up-to-date WMAP5 cosmology and other test cases based on the Einstein-deSitter…

宇宙学与河外天体物理 · 物理学 2015-05-13 Eyal Neistein , Andrea V. Maccio' , Avishai Dekel

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. (2013) compared a wide range of merger-tree-building codes. Here we…

When following the growth of structure in the Universe, we propose replacing merger trees with merger graphs, in which haloes can both merge and split into separate pieces. We show that this leads to smoother mass growth and eliminates…

星系天体物理 · 物理学 2020-05-11 William J. Roper , Peter A. Thomas , Chaichalit Srisawat

We describe the GALFORM semi-analytic model for calculating the formation and evolution of galaxies in hierarchical models. It improves upon, and extends, the Cole et al 1994 model. The model employs a new Monte-Carlo algorithm to follow…

天体物理学 · 物理学 2009-10-31 Shaun Cole , Cedric Lacey , Carlton Baugh , Carlos Frenk

This article concerns the formation and structure of dark matter halos, including (1) their radial density profiles, (2) their abundance, and (3) their merger rates. The last topic may be relevant to the nature of the small, bright,…

天体物理学 · 物理学 2007-05-23 J. R. Primack , J. S. Bullock , A. A. Klypin , A. V. Kravtsov

The effects of spatial correlations of density fluctuations on merger histories of dark matter haloes (so-called `{\it merger trees}') are analysed. We compare the mass functions of dark haloes derived by a new method for calculating merger…

天体物理学 · 物理学 2015-06-24 Masahiro Nagashima , Naoteru Gouda

We introduce gbpTrees: an algorithm for constructing merger trees from cosmological simulations, designed to identify and correct for pathological cases introduced by errors or ambiguities in the halo finding process. gbpTrees is built upon…

星系天体物理 · 物理学 2017-11-08 Gregory B. Poole , Simon J. Mutch , Darren J. Croton , Stuart Wyithe

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…

We use the extended Press-Schechter formalism to investigate the rate at which cold dark matter haloes accrete mass. We discuss the shortcomings of previous methods that have been used to compute the mass accretion histories of dark matter…

天体物理学 · 物理学 2008-11-26 Frank C. van den Bosch

We model the acquisition of spin by dark-matter halos in semi-analytic merger trees. We explore two different algorithms; one in which halo spin is acquired from the orbital angular momentum of merging satellites, and another in which halo…

天体物理学 · 物理学 2009-11-06 Ariyeh H. Maller , Avishai Dekel , Rachel S. Somerville

We use large volume, high resolution, N-body simulations of 3 different $\Lambda$CDM models, with different clustering strengths, to generate dark matter halo merging histories. Over the reliable range of halo masses, roughly galaxy groups…

天体物理学 · 物理学 2009-08-18 J. D. Cohn , J. S. Bagla , Martin White

The merger and accretion probabilities of dark matter halos have so far only been calculated for an infinitesimal time interval. This means that a Monte-Carlo simulation with very small time steps is necessary to find the merger history of…

天体物理学 · 物理学 2008-10-15 Esfandiar Alizadeh , Benjamin Wandelt

We present an algorithm to extend subhalo merger trees in a low-resolution dark-matter-only simulation by conditionally matching them to those in a high-resolution simulation. The algorithm is general and can be applied to simulation data…

星系天体物理 · 物理学 2025-04-08 Yangyao Chen , H. J. Mo , Cheng Li , Kai Wang , Huiyuan Wang , Xiaohu Yang

Galaxy formation and evolution models, such as semi-analytic models, are powerful theoretical tools for predicting how galaxies evolve across cosmic time. These models follow the evolution of galaxies based on the halo assembly histories…

As galaxy formation and evolution over long cosmic time-scales depends to a large degree on the structure of the universe, the assembly history of galaxies is potentially a powerful approach for learning about the universe itself. In this…

星系天体物理 · 物理学 2015-06-22 Christopher J. Conselice , Asa F. L. Bluck , Alice Mortlock , David Palamara , Andrew J. Benson

We study the ability of PINOCCHIO (PINpointing Orbit-Crossing Collapsed HIerarchical Objects) to predict the merging histories of dark matter (DM) haloes, comparing the PINOCCHIO predictions with the results of two large N-body simulations…

天体物理学 · 物理学 2009-11-07 G. Taffoni , P. Monaco , T. Theuns

We apply the model relating halo concentration to formation history proposed by Ludlow et al. to merger trees generated using an algorithm based on excursion set theory. We find that while the model correctly predicts the median relation…

星系天体物理 · 物理学 2019-03-20 Andrew J. Benson , Aaron Ludlow , Shaun Cole

We model the formation and evolution of galaxy clusters in the framework of an extended dark matter halo merger-tree algorithm that includes baryons and incorporates basic physical considerations. Our modified treatment is employed to…

宇宙学与河外天体物理 · 物理学 2015-05-20 Irina Dvorkin , Yoel Rephaeli

(abridged) We study the mass assembly history (MAH) of dark matter haloes. We compare MAHs obtained using (i) merger trees constructed with the extended Press-Schechter (EPS) formalism, (ii) numerical simulations, and (iii) the Lagrangian…

天体物理学 · 物理学 2008-11-26 Yun Li , H. J. Mo , Frank C. van den Bosch , W. P. Lin

In the $\Lambda$CDM universe, structure formation is generally not a self-similar process, while some self-similarity remains in certain statistics which can greatly simplify our description and understanding of the cosmic structures. In…

宇宙学与河外天体物理 · 物理学 2025-06-12 Wenkang Jiang , Jiaxin Han , Fuyu Dong , Feihong He