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L-PICOLA: A parallel code for fast dark matter simulation

机译:L-PICOLA:用于快速暗物质模拟的并行代码

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摘要

Robust measurements based on current large-scale structure surveys require precise knowledge of statistical and systematic errors. This can be obtained from large numbers of realistic mock galaxy catalogues that mimic the observed distribution of galaxies within the survey volume. To this end we present a fast, distributed-memory, planar-parallel code, L-PICOLA, which can be used to generate and evolve a set of initial conditions into a dark matter field much faster than a full non-linear N-Body simulation. Additionally, L-PICOLA has the ability to include primordial non-Gaussianity in the simulation and simulate the past lightcone at run-time, with optional replication of the simulation volume. Through comparisons to fully non-linear N-Body simulations we find that our code can reproduce the z = 0 power spectrum and reduced bispectrum of dark matter to within 2% and 5% respectively on all scales of interest to measurements of Baryon Acoustic Oscillations and Redshift Space Distortions, but 3 orders of magnitude faster. The accuracy, speed and scalability of this code, alongside the additional features we have implemented, make it extremely useful for both current and next generation large-scale structure surveys. L-PICOLA is publicly available at https://cullanhowlett.github.io/l-picola. (C) 2015 Elsevier B.V. All rights reserved.
机译:基于当前大规模结构调查的稳健测量需要对统计和系统误差的精确了解。这可以从大量现实的模拟星系目录中获得,这些目录模仿了调查体积内观察到的星系分布。为此,我们提出了一种快速的分布式内存平面并行代码L-PICOLA,该代码可用于将一组初始条件生成并演化到暗物质场中,比完全非线性N体要快得多。模拟。此外,L-PICOLA能够在模拟中包括原始非高斯性,并在运行时模拟过去的光锥,并且可以选择复制模拟量。通过与完全非线性N体仿真的比较,我们发现我们的代码可以重现z = 0功率谱,并将重物质的双谱在所有感兴趣的尺度上分别降低到2%和5%以内,以进行重子声振荡和Redshift空间扭曲,但速度提高了3个数量级。该代码的准确性,速度和可伸缩性,加上我们已实现的其他功能,使其对于当前和下一代大规模结构勘测极为有用。 L-PICOLA可在https://cullanhowlett.github.io/l-picola上公开获得。 (C)2015 Elsevier B.V.保留所有权利。

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