论文标题

减少带有不同视力线的模拟星系目录的红移空间失真测量的方差

Reducing the Variance of Redshift Space Distortion Measurements from Mock Galaxy Catalogues with Different Lines of Sight

论文作者

Smith, Alex, de Mattia, Arnaud, Burtin, Etienne, Chuang, Chia-Hsun, Zhao, Cheng

论文摘要

准确的模拟目录对于评估大型星系调查的宇宙学分析中的系统学至关重要。来自同一模拟的各向异性两点聚类测量结果显示,由于宇宙方差,不同的视线(LOS)散射,但平均相等。这导致测得的宇宙学参数散射。我们使用Outerrim N体模拟晕圈目录来研究这一点,将3个模拟轴视为LOS。两点统计的四极杆对LOS的变化特别敏感,速度分布的次级级别差异导致〜1.5 $σ$ shifts在大尺度上移动。在多个LOS上平均可以减少宇宙差异的影响。我们在功率谱多极测量之间,用于任何两个LOS(包括射击噪声)以及平均测量值的相应降低,我们得出了高斯交叉共振的表达式。四极杆测量值是反相关的,对于三个正交LOS,平均测量的差异降低了1/3以上。我们执行Fisher分析,以预测宇宙参数测量的相应增益,我们将其与一组300个扩展的Baryon振荡光谱调查(EBOSS)发射线星系(ELG)EZMOCKS进行了比较。 $fσ_8$的增益也比1/3好。在未来的模拟挑战中平均多个LOS将使RSD模型以相同的系统误差约束,而CPU时间却小于3倍。

Accurate mock catalogues are essential for assessing systematics in the cosmological analysis of large galaxy surveys. Anisotropic two-point clustering measurements from the same simulation show some scatter for different lines of sight (LOS), but are on average equal, due to cosmic variance. This results in scatter in the measured cosmological parameters. We use the OuterRim N-body simulation halo catalogue to investigate this, considering the 3 simulation axes as LOS. The quadrupole of the 2-point statistics is particularly sensitive to changes in the LOS, with sub-percent level differences in the velocity distributions resulting in ~1.5$σ$ shifts on large scales. Averaging over multiple LOS can reduce the impact of cosmic variance. We derive an expression for the Gaussian cross-covariance between the power spectrum multipole measurements, for any two LOS, including shot noise, and the corresponding reduction in variance in the average measurement. Quadrupole measurements are anti-correlated, and for three orthogonal LOS, the variance on the average measurement is reduced by more than 1/3. We perform a Fisher analysis to predict the corresponding gain in precision on the cosmological parameter measurements, which we compare against a set of 300 extended Baryon Oscillation Spectroscopic Survey (eBOSS) emission line galaxy (ELG) EZmocks. The gain in $fσ_8$, which measures the growth of structure, is also better than 1/3. Averaging over multiple LOS in future mock challenges will allow the RSD models to be constrained with the same systematic error, with less than 3 times the CPU time.

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