折刀尺度对精确的大尺度结构协方差真的重要吗？
Does jackknife scale really matter for accurate large-scale structure covariances?
摘要：
刀切法给出了大尺度结构测量的内部协方差估计，并允许宇宙学参数的模型无关误差。使用SDSS-III BOSS CMASS样本，我们研究了折刀大小和重采样次数对关联函数多极子协方差估计精度和重子声学标度误差的影响。我们比较的测量与MultiDark补丁模拟星系目录，我们也验证了它对一组对数正态模拟具有相同的调查几何。我们建立了几个不同的大小和数量的重采样刀切配置。我们在协方差估计中引入Hartlap因子，该因子取决于刀切重采样的数量。我们还发现，它是有用的，适用于锥形计划估计精度矩阵从有限数量的重采样。CMASS和模拟星表的结果表明，重子声学标度的误差估计不依赖于折刀标度。对于移位参数$α$，我们发现CMASS，补丁和对数正态刀切协方差的平均误差分别为1.6%，2.2%和1.2%。尽管这些不确定性波动显着，由于一些结构上的限制，刀切法，我们的$α$估计是在合理的协议与公布的重建前的分析。刀切法将为未来的大尺度结构勘测提供有价值的互补协方差估计。
英文摘要：
The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the inferred baryon acoustic scale. We compare the measurement with the MultiDark Patchy mock galaxy catalogues, and we also validate it against a set of log-normal mocks with the same survey geometry. We build several jackknife configurations that vary in size and number of resamplings. We introduce the Hartlap factor in the covariance estimate that depends on the number of jackknife resamplings. We also find that it is useful to apply the tapering scheme to estimate the precision matrix from a limited number of resamplings. The results from CMASS and mock catalogues show that the error estimate of the baryon acoustic scale does not depend on the jackknife scale. For the shift parameter $α$, we find an average error of 1.6%, 2.2% and 1.2%, respectively from CMASS, Patchy and log-normal jackknife covariances. Despite these uncertainties fluctuate significantly due to some structural limitations of the jackknife method, our $α$ estimates are in reasonable agreement with published pre-reconstruction analyses. Jackknife methods will provide valuable and complementary covariance estimates for future large-scale structure surveys.
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