论文标题
desi $ n $ - 体仿真项目 - ii。通过快速模拟抑制样品方差
The DESI $N$-body Simulation Project -- II. Suppressing sample variance with fast simulations
论文作者
论文摘要
暗能量光谱仪器(DESI)将构建我们宇宙的大型三维图。调查有效量达到$ \ sim20 \ gpchcube $。准备更大量的高分辨率模拟以验证DESI分析管道,这是一个巨大的挑战。 \ textsc {abacussummit}是一套为此目的而设计的高分辨率黑色模拟套件,基本宇宙学的$ 200 \ gpchcube $(10倍DESI卷)。但是,需要采取进一步的努力来提供对数据的更精确的分析,并涵盖其他宇宙学。最近,提出了拼车方法使用配对的准确和近似模拟,以实现有限数量的高分辨率模拟的高统计精度。依靠这种技术,我们建议使用快速的准$ n $体求解器与准确的模拟相结合,以产生准确的摘要统计信息。这使我们能够获得比我们感兴趣的量表的预期DESI统计差异小的100倍。 $ k <0.3 \ hmpc $用于光晕功率谱。另外,它可以显着抑制光环双光谱的样品方差。我们进一步概括了其他宇宙学的方法,在\ textsc {abacussummit}套件中仅实现了一个实现的方法,以扩展有效卷$ \ sim 20 $ times。总而言之,我们提出的将高保真模拟与快速近似重力求解器和一系列方差抑制技术相结合的策略为对银河系调查数据的强大宇宙学分析提供了途径。
Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim20\Gpchcube$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. \textsc{AbacusSummit} is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\Gpchcube$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-$N$-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k < 0.3\hMpc$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in \textsc{AbacusSummit} suite to extend the effective volume $\sim 20$ times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.