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相关论文: Generating Dark Matter Halo Merger Trees

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Structure formation provides a strong test of any cosmic acceleration model because a successful dark energy model must not inhibit {\black or overpredict} the development of observed large-scale structures. Traditional approaches to…

宇宙学与河外天体物理 · 物理学 2010-10-28 C. Prescod-Weinstein , N. Afshordi

We present a comprehensive series of dissipationless N-body simulations to investigate the evolution of density distribution in equal-mass mergers between dark matter (DM) halos and multicomponent galaxies. The DM halo models are…

天体物理学 · 物理学 2009-11-13 Stelios Kazantzidis , Andrew R. Zentner , Andrey V. Kravtsov

In two recent papers, we developed a powerful technique to link the distribution of galaxies to that of dark matter haloes by considering halo occupation numbers as function of galaxy luminosity and type. In this paper we use these…

天体物理学 · 物理学 2009-11-07 Xiaohu Yang , H. J. Mo , Y. P. Jing , Frank C. van den Bosch , YaoQuan Chu

It is of fundamental importance to determine if and how hierarchical clustering is involved in large-scale structure formation of the universe. Hierarchical evolution is characterized by rules which specify how dark matter halos are formed…

天体物理学 · 物理学 2009-10-30 J. Pando , P. Lipa , M. Greiner , L. Z. Fang

We use the "Millennium Simulation" to study the mass function of accreted sub-halos during merger events in the dark halo assembly history. Our study includes three kinds of sub-halo mergers: (1) mergers that happen to the main progenitor…

宇宙学与河外天体物理 · 物理学 2009-08-04 Yun Li , Houjun Mo

While Population III stars are typically thought to be massive, pathways towards lower-mass Pop III stars may exist when the cooling of the gas is particularly enhanced. A possible route is enhanced HD cooling during the merging of…

星系天体物理 · 物理学 2015-06-18 S. Bovino , M. A. Latif , T. Grassi , D. R. G. Schleicher

In the context of structure formation with ultralight axion dark matter, we offer an alternative explanation for the mass relation of solitonic cores and their host halos observed in numerical simulations. Our argument is based entirely on…

星系天体物理 · 物理学 2017-02-27 Xiaolong Du , Christoph Behrens , Jens C. Niemeyer , Bodo Schwabe

We investigate machine learning (ML) techniques for predicting the number of galaxies (N_gal) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for…

宇宙学与河外天体物理 · 物理学 2015-06-15 Xiaoying Xu , Shirley Ho , Hy Trac , Jeff Schneider , Barnabas Poczos , Michelle Ntampaka

We present a new model to describe the galaxy-dark matter connection across cosmic time, which unlike the popular subhalo abundance matching technique is self-consistent in that it takes account of the facts that (i) subhalos are accreted…

宇宙学与河外天体物理 · 物理学 2015-05-30 Xiaohu Yang , H. J. Mo , Frank C. van den Bosch , Youcai Zhang , Jiaxin Han

We derive the mass model of the Milky Way (MW) using a cored dark matter (DM) halo profile and recent data. The method used consists in fitting a spherically symmetric model of the Galaxy with a Burkert DM halo profile to available data: MW…

星系天体物理 · 物理学 2015-06-15 Fabrizio Nesti , Paolo Salucci

Theories of structure formation in a cold dark matter dominated Universe predict that massive clusters of galaxies assemble from the hierarchical merging of lower mass subhalos. Exploiting strong and weak gravitational lensing signals…

Current models of galaxy formation applied to understanding the large-scale structure of the universe have two parts. The first is an accurate solution of the equations of motion for the dark matter due to gravitational clustering. The…

天体物理学 · 物理学 2009-11-06 Roman Scoccimarro , Ravi K. Sheth

Dark matter simulations can serve as a basis for creating galaxy histories via the galaxy-dark matter connection. Here, one such model by Becker (2015) is implemented with several variations on three different dark matter simulations.…

星系天体物理 · 物理学 2017-02-02 J. D. Cohn

In this paper we use the ``Millennium Simulation'' to re-examine the mass assembly history of dark matter halos and the age dependence of halo clustering. We use eight different definitions of halo formation times to characterize the…

天体物理学 · 物理学 2009-11-13 Yun Li , H. J. Mo , L. Gao

We make black hole (BH) merger trees from Millennium and Millennium-II simulations to find under what conditions 10^9Msun SMBH can form by redshift z=7. In order to exploit both: large box size in the Millennium simulation; and large mass…

星系天体物理 · 物理学 2015-06-24 Majda Smole , Miroslav Micic , Nemanja Martinovic

We consider non-gravitational heating effects on galaxy clusters on the basis of the Monte-Carlo modeling of merging trees of dark matter halos combined with the thermal evolution of gas inside each halo. Under the assumption of hydrostatic…

天体物理学 · 物理学 2015-06-24 Mamoru Shimizu , Tetsu Kitayama , Shin Sasaki , Yasushi Suto

We derive the halo mass function (HMF) for fuzzy dark matter (FDM) by solving the excursion set problem explicitly with a mass-dependent barrier function, which has not been done before. We find that compared to the naive approach of the…

宇宙学与河外天体物理 · 物理学 2017-02-21 Xiaolong Du , Christoph Behrens , Jens C. Niemeyer

We present a machine learning (ML) approach for the prediction of galaxies' dark matter halo masses that achieves an improved performance over conventional methods. We train three ML algorithms (\texttt{XGBoost}, Random Forests, and neural…

星系天体物理 · 物理学 2019-10-16 Victor F. Calderon , Andreas A. Berlind

After more than five years of development, we present a new version of Dark Sage, a semi-analytic model (SAM) of galaxy formation that breaks the mould for models of its kind. Included among the major changes is an overhauled treatment of…

Halo merger trees are constructed from ELUCID, a constrained $N$-body simulation in the Sloan Digital Sky Survey (SDSS) volume. These merger trees are used to populate dark matter halos with galaxies according to an empirical model of…

星系天体物理 · 物理学 2019-03-06 Yangyao Chen , Houjun Mo , Cheng Li , Huiyuan Wang , Xiaohu Yang , Shuang Zhou , Youcai Zhang
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