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AI-assisted superresolution cosmological simulations – II. Halo substructures, velocities, and higher order statistics
Monthly Notices of the Royal Astronomical Society ( IF 4.8 ) Pub Date : 2021-07-22 , DOI: 10.1093/mnras/stab2113
Yueying Ni 1, 2 , Yin Li 3 , Patrick Lachance 1, 2 , Rupert A C Croft 1, 2 , Tiziana Di Matteo 1, 2 , Simeon Bird 4 , Yu Feng 5
Affiliation  

In this work, we expand and test the capabilities of our recently developed superresolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity, from computationally cheap low-resolution (LR) cosmological N-body simulations. The SR model enhances the simulation resolution by generating 512 times more tracer particles, extending into the deeply nonlinear regime where complex structure formation processes take place. We validate the SR model by deploying the model in 10 test simulations of box size 100 h−1 Mpc, and examine the matter power spectra, bispectra, and two-dimensional power spectra in redshift space. We find the generated SR field matches the true HR result at per cent level down to scales of k ∼ 10 h Mpc−1. We also identify and inspect dark matter haloes and their substructures. Our SR model generates visually authentic small-scale structures that cannot be resolved by the LR input, and are in good statistical agreement with the real HR results. The SR model performs satisfactorily on the halo occupation distribution, halo correlations in both real and redshift space, and the pairwise velocity distribution, matching the HR results with comparable scatter, thus demonstrating its potential in making mock halo catalogues. The SR technique can be a powerful and promising tool for modelling small-scale galaxy formation physics in large cosmological volumes.

中文翻译:

人工智能辅助的超分辨率宇宙学模拟——II。晕子结构、速度和高阶统计

在这项工作中,我们扩展并测试了我们最近开发的超分辨率 (SR) 模型的能力,以从计算成本低的低分辨率生成全相空间物质分布的高分辨率 (HR) 实现,包括位移和速度。 LR) 宇宙学 N 体模拟。SR 模型通过生成 512 倍以上的示踪粒子提高了模拟分辨率,延伸到发生复杂结构形成过程的深度非线性区域。我们通过在 10 个盒子大小为 100 h-1 Mpc 的测试模拟中部署模型来验证 SR 模型,并检查红移空间中的物质功率谱、双谱和二维功率谱。我们发现生成的 SR 场与真实 HR 结果在百分比水平上匹配到 k ∼ 10 h Mpc-1 的尺度。我们还识别和检查暗物质晕及其子结构。我们的 SR 模型生成视觉上真实的小规模结构,这些结构无法通过 LR 输入来解析,并且与真实的 HR 结果具有良好的统计一致性。SR 模型在光晕占据分布、真实空间和红移空间中的光晕相关性以及成对速度分布方面表现令人满意,将 HR 结果与可比较的散射相匹配,从而展示了其在制作模拟光晕目录方面的潜力。SR 技术可以成为在大宇宙体积中模拟小规模星系形成物理的强大且有前途的工具。SR 模型在光晕占据分布、真实空间和红移空间中的光晕相关性以及成对速度分布方面表现令人满意,将 HR 结果与可比较的散射相匹配,从而展示了其在制作模拟光晕目录方面的潜力。SR 技术可以成为在大宇宙体积中模拟小规模星系形成物理的强大且有前途的工具。SR 模型在光晕占据分布、真实空间和红移空间中的光晕相关性以及成对速度分布方面表现令人满意,将 HR 结果与可比较的散射相匹配,从而展示了其在制作模拟光晕目录方面的潜力。SR 技术可以成为在大宇宙体积中模拟小规模星系形成物理的强大且有前途的工具。
更新日期:2021-07-22
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