论文标题
BACCO仿真项目：利用大规模结构的全部功能用于宇宙学
The BACCO Simulation Project: Exploiting the full power of large-scale structure for cosmology
论文作者
论文摘要
我们介绍了BACCO Project，这是一个仿真框架，专门设计，旨在为质量，星系和气体的分布提供高度准确的预测，这是宇宙参数的函数。在本文中，我们描述了我们的主要模拟套件（l $ \ sim2 $ gpc和$ 4320^3 $粒子），并介绍各种验证测试。使用宇宙学换句技术，我们预测红移范围内的非线性质量功率谱$ 0 <z <1.5 $，并且超过尺度$ 10^{ - 2} <k/（h mpc^{ - 1}）<5 $在8维元素上的宇宙学参数方面的800点。为了进行有效的结果插值，我们构建了一个模拟器，并将其预测与几种广泛使用的方法进行比较。在考虑的整个量表范围内，我们期望我们的预测在最小$λ$ CDM模型中的参数的2 \％水平上准确，并且当扩展到动态性暗能量和大量中微子时，我们的预测是准确的，至3 \％。我们通过http://www.dipc.org/bacco公开提供模拟器
We present the BACCO project, a simulation framework specially designed to provide highly-accurate predictions for the distribution of mass, galaxies, and gas as a function of cosmological parameters. In this paper, we describe our main suite of simulations (L $\sim2$ Gpc and $4320^3$ particles) and present various validation tests. Using a cosmology-rescaling technique, we predict the nonlinear mass power spectrum over the redshift range $0<z<1.5$ and over scales $10^{-2} < k/(h Mpc^{-1} ) < 5$ for 800 points in an 8-dimensional cosmological parameter space. For an efficient interpolation of the results, we build an emulator and compare its predictions against several widely-used methods. Over the whole range of scales considered, we expect our predictions to be accurate at the 2\% level for parameters in the minimal $Λ$ CDM model and to 3\% when extended to dynamical dark energy and massive neutrinos. We make our emulator publicly available under http://www.dipc.org/bacco
