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Uncertainty in 2-point correlation function estimators and BAO detection in SDSS DR7

机译:2点相关函数估计和BaO检测的不确定性   在sDss DR7中

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摘要

We study the uncertainty in different two-point correlation function (2PCF)estimators in currently available galaxy surveys. This is motivated by theactive subject of using the baryon acoustic oscillations (BAOs) feature in thecorrelation function as a tool to constrain cosmological parameters, whichrequires a fine analysis of the statistical significance. We discuss howestimators are affected by both the uncertainty in the mean density $\bar{n}$and the integral constraint $\frac{1}{V^2}\int_{V^2} \hat{\xi} (r) d^3r =0$which necessarily causes a bias. We quantify both effects for currentlyavailable galaxy samples using simulated mock catalogues of the Sloan DigitalSky Survey (SDSS) following a lognormal model, with a Lambda-Cold Dark Matter($\Lambda\text{CDM}$) correlation function and similar properties as thesamples (number density, mean redshift for the $\Lambda\text{CDM}$ correlationfunction, survey geometry, mass-luminosity bias). Because we need extensivesimulations to quantify small statistical effects, we cannot use realisticN-body simulations and some physical effects are neglected. Our simulationsstill enable a comparison of the different estimators by looking at theirbiases and variances. We also test the reliability of the BAO detection in theSDSS samples and study the compatibility of the data results with our$\Lambda\text{CDM}$ simulations.
机译:我们研究了当前可用星系调查中不同的两点相关函数(2PCF)估计量中的不确定性。这是由活跃的研究对象所激发的,该主题是将相关函数中的重子声振荡(BAOs)功能用作约束宇宙学参数的工具,这需要对统计显着性进行精细分析。我们讨论了平均密度$ \ bar {n} $的不确定性和积分约束$ \ frac {1} {V ^ 2} \ int_ {V ^ 2} \ hat {\ xi}(r )d ^ 3r = 0 $这必然引起偏差。我们使用对数正态模型,具有Lambda-Cold Dark Matter($ \ Lambda \ text {CDM} $)相关函数和与样本相​​似的属性,使用对数正态模型,使用Sloan DigitalSky Survey(SDSS)的模拟模拟目录对当前可用的星系样本的两种效果进行量化。 (数字密度,$ \ Lambda \ text {CDM} $相关函数的平均红移,测量几何形状,质量-光度偏差)。因为我们需要大量的模拟来量化小的统计影响,所以我们无法使用逼真的N体模拟,并且忽略了一些物理影响。我们的模拟仍然可以通过查看它们的偏差和方差来比较不同的估计量。我们还测试了SDSS样本中BAO检测的可靠性,并通过我们的\ Lambda \ text {CDM} $仿真研究了数据结果的兼容性。

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