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相关论文: MoMaF : The Mock Map Facility

200 篇论文

Simulation-Based Inference of Galaxies (${\rm S{\scriptsize IM}BIG}$) is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work, we present the ${\rm S{\scriptsize IM}BIG}$ forward model,…

Super sample covariance (SSC) is important when estimating covariance matrices using a set of mock catalogues for galaxy surveys. If the underlying cosmological simulations do not include the variation in background parameters appropriate…

宇宙学与河外天体物理 · 物理学 2025-03-05 Greg Schreiner , Alex Krolewski , Shahab Joudaki , Will J. Percival

We present a set of mock redshift catalogs, constructed from N-body simulations, designed to mimic the DEEP2 survey. Galaxies with a range of luminosities are placed within virialized halos in the simulation using a variant of the halo…

天体物理学 · 物理学 2008-11-26 Renbin Yan , Martin White , Alison L. Coil

We present predictions for the two-point correlation function of galaxy clustering as a function of stellar mass, computed using two new versions of the GALFORM semi-analytic galaxy formation model. These models make use of a high…

The work presented in this paper aims at restricting the input parameter values of the semi-analytical model used in GALICS and MOMAF, so as to derive which parameters influence the most the results, e.g., star formation, feedback and halo…

天体物理仪器与方法 · 物理学 2015-05-19 Benjamin Depardon , Eddy Caron , Frédéric Desprez , Jérémy Blaizot , Hélène M. Courtois

We introduce a new set of large N-body runs, the MICE simulations, that provide a unique combination of very large cosmological volumes with good mass resolution. They follow the gravitational evolution of ~ 8.5 billion particles (2048^3)…

宇宙学与河外天体物理 · 物理学 2015-05-13 Martin Crocce , Pablo Fosalba , Francisco J. Castander , Enrique Gaztanaga

Many statistical methods have been proposed in the last years for analyzing the spatial distribution of galaxies. Very few of them, however, can handle properly the border effects of complex observational sample volumes. In this paper, we…

天体物理学 · 物理学 2008-11-26 Enn Saar , Vicent J. Martinez , Jean-Luc Starck , David L. Donoho

Large-scale structure (LSS) surveys will increasingly provide stringent constraints on our cosmological models. Recently, the density-marked correlation function (MCF) has been introduced, offering an easily computable density-correlation…

宇宙学与河外天体物理 · 物理学 2025-03-11 L. M. Lai , J. C. Ding , X. L. Luo , Y. Z. Yang , Z. H. Wang , K. S. Liu , G. F. Liu , X. Wang , Y. Zheng , Z. Y. Li , L. Zhang , X. D. Li

Selected results on estimating cosmological parameters from simulated weak lensing data with noise are presented. Numerical simulations of ray tracing through N-body simulations have been used to generate shear and convergence maps due to…

天体物理学 · 物理学 2007-05-23 Bhuvnesh Jain , Uros Seljak , Simon White

We assess the performance of a perturbation theory inspired method for inferring cosmological parameters from the joint measurements of galaxy-galaxy weak lensing ($\Delta\Sigma$) and the projected galaxy clustering ($w_{\rm p}$). To do…

宇宙学与河外天体物理 · 物理学 2020-10-21 Sunao Sugiyama , Masahiro Takada , Yosuke Kobayashi , Hironao Miyatake , Masato Shirasaki , Takahiro Nishimichi , Youngsoo Park

We present an accurate and fast framework for generating mock catalogues including low-mass halos, based on an implementation of the COmoving Lagrangian Acceleration (COLA) technique. Multiple realisations of mock catalogues are crucial for…

宇宙学与河外天体物理 · 物理学 2016-04-20 Jun Koda , Chris Blake , Florian Beutler , Eyal Kazin , Felipe Marin

We derive analytic covariance matrices for the $N$-Point Correlation Functions (NPCFs) of galaxies in the Gaussian limit. Our results are given for arbitrary $N$ and projected onto the isotropic basis functions of Cahn & Slepian (2020),…

宇宙学与河外天体物理 · 物理学 2022-08-31 Jiamin Hou , Robert N. Cahn , Oliver H. E. Philcox , Zachary Slepian

We use the Millennium Simulation, a 10 billion particle simulation of the growth of cosmic structure, to construct a new model of galaxy clustering. We adopt a methodology that falls midway between the traditional semi-analytic approach and…

天体物理学 · 物理学 2009-11-11 Lan Wang , Cheng Li , Guinevere Kauffmann , Gabriella De Lucia

We study the bias and scatter in mass measurements of galaxy clusters resulting from fitting a spherically-symmetric Navarro, Frenk & White model to the reduced tangential shear profile measured in weak lensing observations. The reduced…

宇宙学与河外天体物理 · 物理学 2011-09-23 Matthew R. Becker , Andrey V. Kravtsov

Large-scale sky surveys require companion large volume simulated mock catalogs. To ensure precision cosmology studies are unbiased, the correlations in these mocks between galaxy properties and their large-scale environments must be…

宇宙学与河外天体物理 · 物理学 2021-02-25 Sujatha Ramakrishnan , Aseem Paranjape , Ravi K. Sheth

We study potential systematic effects of assembly bias on cosmological parameter constraints from redshift space distortion measurements. We use a semi-analytic galaxy formation model applied to the Millennium N-body WMAP-7 simulation to…

宇宙学与河外天体物理 · 物理学 2019-03-27 Nelson Padilla , Sergio Contreras , Idit Zehavi , Carlton Baugh , Peder Norberg

Massive halos hosting groups and clusters of galaxies imprint coherent, arcminute-scale features across the spectrophotometric sky, especially optical-IR clusters of galaxies, distortions in the sub-mm CMB, and extended sources of X-ray…

宇宙学与河外天体物理 · 物理学 2023-08-30 Cameron E. Norton , Fred C. Adams , August E. Evrard

We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. We aim to produce mock…

Cosmological parameters can be measured by comparing peculiar velocities with those predicted from a galaxy density field. Previous work has tested the accuracy of this approach with N-body simulations, but generally on idealised mock…

宇宙学与河外天体物理 · 物理学 2024-03-27 Amber M. Hollinger , Michael J. Hudson