中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
BAM: bias assignment method to generate mock catalogues

文献类型:期刊论文

作者Balaguera-Antolinez, A.1,3; Kitaura, Francisco-Shu1,3; Pellejero-Ibanez, Marcos1,3; Zhao, Cheng2; Abel, Tom4
刊名MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
出版日期2019-02-01
卷号483期号:1页码:L58-L63
关键词cosmology: theory large-scale structure of Universe
ISSN号0035-8711
DOI10.1093/mnrasl/sly220
英文摘要We present BAM: a novel Bias Assignment Method envisaged to generate mock catalogues. Combining the statistics of dark matter tracers from a high-resolution cosmological N-body simulation and the dark matter density field calculated from down-sampled initial conditions using efficient structure formation solvers, we extract the halo-bias relation on a mesh of a 3 h(-1) Mpc cell side resolution as a function of properties of the dark matter density field ( e.g. local density, cosmic web type), automatically including stochastic, deterministic, local and non-local components. We use this information to sample the halo density field, accounting for ignored dependencies through an iterative process. By construction, our approach reaches similar to 1 per cent accuracy in the majority of the k-range up to the Nyquist frequency without systematic deviations for power spectra ( about k similar to 1 h Mpc(-1)) using either particle mesh or Lagrangian perturbation theory based solvers. When using phase-space mapping to compensate the low resolution of the approximate gravity solvers, our method reproduces the bispectra of the reference within 10 per cent precision studying configurations tracing the quasi-non-linear regime. BAM has the potential to become a standard technique to produce mock halo and galaxy catalogues for future galaxy surveys and cosmological studies being highly accurate, efficient and parameter free.
WOS关键词OSCILLATION SPECTROSCOPIC SURVEY ; DARK-MATTER ; GALAXY CATALOGS ; HALO BIAS ; PERTURBATION-THEORY ; ASSEMBLY BIAS ; MASS ; ACCURATE ; DEPENDENCE ; COSMOLOGY
资助项目Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program[SEV-2015-0548] ; MINECO[AYA2012-39702-C02-01] ; [RYC2015-18693] ; [AYA2017-89891-P]
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:000482178200012
出版者OXFORD UNIV PRESS
资助机构Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; MINECO ; MINECO ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; MINECO ; MINECO ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; MINECO ; MINECO ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; Spanish Ministry of Economy and Competitiveness (MINECO) under the Severo Ochoa program ; MINECO ; MINECO
源URL[http://ir.bao.ac.cn/handle/114a11/27357]  
专题中国科学院国家天文台
通讯作者Balaguera-Antolinez, A.; Kitaura, Francisco-Shu
作者单位1.Univ La Laguna, Dept Astrofis, E-38206 Tenerife, Spain
2.Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China
3.Inst Astrofis Canarias, E-38205 Tenerife, Spain
4.Stanford Univ, SLAC Natl Accelerator Lab, Kavli Inst Particle Astrophys & Cosmol, Menlo Pk, CA 94025 USA
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Balaguera-Antolinez, A.,Kitaura, Francisco-Shu,Pellejero-Ibanez, Marcos,et al. BAM: bias assignment method to generate mock catalogues[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2019,483(1):L58-L63.
APA Balaguera-Antolinez, A.,Kitaura, Francisco-Shu,Pellejero-Ibanez, Marcos,Zhao, Cheng,&Abel, Tom.(2019).BAM: bias assignment method to generate mock catalogues.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,483(1),L58-L63.
MLA Balaguera-Antolinez, A.,et al."BAM: bias assignment method to generate mock catalogues".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 483.1(2019):L58-L63.

入库方式: OAI收割

来源:国家天文台

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