The Coyote Universe III: Simulation Suite and Precision Emulator for the Nonlinear Matter Power Spectrum
Earl Lawrence, Katrin Heitmann, Martin White, David Higdon, Christian Wagner, Salman Habib, Brian Williams
备注：
10 pages, 10 figures, minor changes to address referee report, version v1.1 of the power spectrum emulator code can be downloaded at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html, includes now fortran wrapper and choice of any redshift between z=0 and z=1 (note: webpage now maintained at Argonne National Laboratory)
Many of the most exciting questions in astrophysics and cosmology, including the majority of observational probes of dark energy, rely on an understanding of the nonlinear regime of structure formation. In order to fully exploit the information available from this regime and to extract cosmological constraints, accurate theoretical predictions are needed. Currently such predictions can only be obtained from costly, precision numerical simulations. This paper is the third in a series aimed at constructing an accurate calibration of the nonlinear mass power spectrum on Mpc scales for a wide range of currently viable cosmological models, including dark energy. The first two papers addressed the numerical challenges, and the scheme by which an interpolator was built from a carefully chosen set of cosmological models. In this paper we introduce the "Coyote Univers"' simulation suite which comprises nearly 1,000 N-body simulations at different force and mass resolutions, spanning 38 wCDM cosmologies. This large simulation suite enables us to construct a prediction scheme, or emulator, for the nonlinear matter power spectrum accurate at the percent level out to k~1 h/Mpc. We describe the construction of the emulator, explain the tests performed to ensure its accuracy, and discuss how the central ideas may be extended to a wider range of cosmological models and applications. A power spectrum emulator code is released publicly as part of this paper.
暗物质晕的空间分布模型必须达到新的精确度和准确度水平，以满足即将进行的实验的要求。在这项工作中，我们提出了一个晕偏差模拟器，用于模拟大尺度上的晕聚类。它结合了宇宙学的依赖性的偏见超出了晕质量的映射峰高。与广泛使用的Tinker et al.（2010）模型相比，仿真器在准确性方面有了实质性的改进。在这项工作中的晕定义使用相对于平均背景密度为200的过密度标准。Halo目录是为40个N体模拟产生的，作为Aemulus项目的一部分，快照从z=3到z=0。仿真器在质量范围$6\times10^{12}-7\times10^{15}\ h^{-1}M_{\odot}$上进行训练。使用另外一套35个模拟，我们确定，模拟器的精度是红移依赖，实现子百分之水平的大部分红移范围。另外两个模拟套件用于测试仿真器外推到更高和更低质量的能力。我们的高分辨率模拟套件用于开发外推方案，其中模拟器在低质量下渐近线到Tinker et al.（2010）模型，达到约3%的准确度，低至$10^{11}\ h^{-1}M_{\odot}$。最后，我们提出了一种方法来传播仿真建模的不确定性到误差预算。我们的模拟器在\url{https://github.com/AemulusProject/bias_emulator}上公开提供。
Modeling nonlinear scales for dynamical dark energy cosmologies with COLA
CBPF - Brazilian Center for Research in Physics（巴西物理研究中心）；Instituto de Física Teórica da Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；Department of Physics & Astronomy, Stony Brook University（石溪大学物理与天文学系）；C. N. Yang Institute for Theoretical Physics, Stony Brook University（石溪大学陈省身理论物理研究所）
Using Neural Emulators and Hamiltonian Monte Carlo to constrain the Epoch of Reionization's History with the Ly$α$ Forest Power Spectrum
University of California, Santa Barbara（加州大学圣塔芭芭拉分校）；Max-Planck-Institut für Astrophysik（马克斯·普朗克天体物理学研究所）；The Ohio State University（俄亥俄州立大学）；Leiden University（莱顿大学）；University of Washington（华盛顿大学）；University of California, Berkeley（加州大学伯克利分校）
Gaussian-Process Emulation of the Redshift-Space Halo Power Spectrum Monopole in Cosmologies with Massive Neutrinos
National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文与空间科学学院）；Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学天文与前沿科学研究院）；Chinese Academy of Sciences South America Center for Astronomy (CASSACA), National Astronomical Observatories, Chinese Academy of Sciences（中国科学院南美天文中心）
MG-NECOLA: A Field-Level Emulator for $f(R)$ Gravity and Massive Neutrino Cosmologies
Universidad del Valle（谷大学）；Michigan Technological University（密歇根理工大学）；Università di Bologna（博洛尼亚大学）；INAF, Osservatorio di Astrofisica e Scienza dello Spazio di Bologna（意大利国家天体物理研究所博洛尼亚天文与空间科学观测站）
Sym-EFT: Accelerating Effective Field Theory of Large Scale Structure with Symbolic Regression
CEICO—FZU, Institute of Physics of the Czech Academy of Sciences（捷克科学院物理研究所）；Institute of Theoretical Physics, Faculty of Mathematics and Physics, Charles University（查理大学数学物理学院理论物理研究所）；Department of Physics, University of Oxford（牛津大学物理系）
Ten-dimensional neural network emulator for the nonlinear matter power spectrum
Department of Physics & Astronomy, University of California, Riverside（加州大学河滨分校物理与天文系）；Department of Physics, University of Michigan（密歇根大学物理系）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）
Aletheia: Emulating the non-linear matter power spectrum in the context of evolution mapping
Max-Planck-Institut für extraterrestrische Physik（马克斯·普朗克地外物理研究所）；Instituto de Astronomía Teórica y Experimental, CONICET-UNC（理论与实验天文学研究所，阿根廷国家科学研究委员会-科尔多瓦大学）；Observatorio Astronómico, Universidad Nacional de Córdoba（科尔多瓦国立大学天文台）；Pontificia Universidad Católica de Chile（智利天主教 Pontificia 大学）
Dark Quest II: A Wide-Coverage Neural Network Emulator of the Nonlinear Matter Power Spectrum Across Extended Cosmologies
Graduate School of Social Data Science, Hitotsubashi University（立命馆大学社会科学数据科学研究生院）；Center for Gravitational Physics and Quantum Information, Yukawa Institute for Theoretical Physics, Kyoto University（京都大学重力物理与量子信息中心，山梨大学理论物理研究所）；Department of Astrophysics and Atmospheric Sciences, Faculty of Science, Kyoto Sangyo University（京都 Sangyo 大学科学系天文学与大气科学系）；Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo（物理学与数学宇宙研究所（WPI），东京大学先进研究所（UTIAS），东京大学）；RIKEN Center for Advanced Intelligence Project（理化学研究院先进智能项目中心）
Euclid: An emulator for baryonic effects on the matter bispectrum
University of Waterloo（滑铁卢大学）；INFN-Sezione di Bologna（博洛尼亚意大利国家核物理研究所分部）；University of Zurich（苏黎世大学）；Universität Innsbruck（因斯布鲁克大学）；Donostia International Physics Center (DIPC)（多诺斯蒂亚国际物理中心）；IKERBASQUE, Basque Foundation for Science（伊克尔巴斯基克，巴斯克科学基金会）；Leiden University（莱顿大学）；Oxford University（牛津大学）；University of Cambridge（剑桥大学）
Design and optimization of neural networks for multifidelity cosmological emulation
University of California, Riverside（加州大学河滨分校）；Department of Physics & Astronomy, University of California, Riverside（加州大学河滨分校物理与天文系）；Department of Physics, University of Michigan（密歇根大学物理系）；Leinweber Center for Theoretical Physics（莱因韦伯理论物理中心）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）
Cosmological Constraints from Bias-Robust Wavelet Scattering Statistics for Stage-IV Galaxy Surveys
School of Physics and Astronomy, Sun Yat-sen University（中山大学物理学院）；Tsung-Dao Lee Institute, Shanghai Jiao Tong University（上海交通大学李政道研究所）；Department of Astronomy, School of Physics and Astronomy, Shanghai Jiao Tong University（上海交通大学物理学院天文学系）；State Key Laboratory of Dark Matter Physics, School of Physics and Astronomy, Shanghai Jiao Tong University（上海交通大学物理学院暗物质物理全国重点实验室）；Key Laboratory for Particle Astrophysics and Cosmology (MOE)/Shanghai Key Laboratory for Particle Physics and Cosmology（粒子天体物理教育部重点实验室/上海粒子物理与天体物理重点实验室）；Department of Physics and Electronic Engineering, Tongren University（铜仁学院物理与电子工程学院）
Improved Cosmological Constraints from Morphology-Based Marked Correlation Functions
School of Physics and Astronomy, Sun Yat-Sen University（中山大学物理学院）；Tsung-Dao Lee Institute, Shanghai Jiao Tong University（上海交通大学李政道研究所）；Department of Astronomy, School of Physics and Astronomy, Shanghai Jiao Tong University（上海交通大学物理学院天文学系）；State Key Laboratory of Dark Matter Physics, School of Physics and Astronomy, Shanghai Jiao Tong University（上海交通大学物理学院暗物质物理全国重点实验室）；Key Laboratory for Particle Astrophysics and Cosmology (MOE)/Shanghai Key Laboratory for Particle Physics and Cosmology（粒子天体物理教育部重点实验室/上海粒子物理与宇宙学重点实验室）；Peng Cheng Laboratory（鹏城实验室）；CSST Science Center for the Guangdong–Hong Kong–Macau Greater Bay Area, SYSU（中山大学粤港澳大湾区空间望远镜科学中心）
