Measuring the Galaxy Power Spectrum with Future Redshift Surveys
Measuring the Galaxy Power Spectrum with Future Redshift Surveys
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通过未来的红移巡天测量星系功率谱
DOI：
10.1086/305663
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发表时间：
1997
期刊：
影响因子：
--
通讯作者：
A. Szalay
中科院分区：
文献类型：
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作者：
Max Tegmark;A. Hamilton;M. Strauss;M. Vogeley;A. Szalay
精确测量星系功率谱P（k）需要一个数据分析管道，该管道既要足够快以在计算上可行，又要足够准确以充分利用高质量数据。我们提出了一个严格的讨论不同的方法的功率谱估计，重点是传统的傅立叶方法和线性（Karhunen-Loève; KL）和二次数据压缩方案，显示在什么样的近似，他们给出了相同的结果。为了提高速度，我们展示了KL数据压缩和功率谱估计的优点，可以实现计算速度更快的二次方法。为了提高精度，我们推导出处理的积分约束的解析表达式，因为它是至关重要的，有限体积的影响进行精确校正的规模可比的深度的调查。我们还表明，对于KL和二次技术，可以通过简单的矩阵运算包括多个约束，从而使结果对银河系消光和径向选择函数的错误估计不太敏感。我们提出了一个数据分析管道，我们认为不公正的质量和数量的数据，即将到来的红移调查将提供的增加。它结合使用三种分析技术：小尺度上的传统傅立叶方法，大尺度上的像素化二次矩阵方法，以及像素化KL本征模分析来探测各向异性效应，如红移空间失真。
Precision measurements of the galaxy power spectrum P(k) require a data analysis pipeline that is both fast enough to be computationally feasible and accurate enough to take full advantage of high-quality data. We present a rigorous discussion of different methods of power spectrum estimation, with emphasis on the traditional Fourier method and linear (Karhunen-Loève; KL) and quadratic data compression schemes, showing in what approximations they give the same result. To improve speed, we show how many of the advantages of KL data compression and power spectrum estimation may be achieved with a computationally faster quadratic method. To improve accuracy, we derive analytic expressions for handling the integral constraint, since it is crucial that finite volume effects are accurately corrected for on scales comparable to the depth of the survey. We also show that for the KL and quadratic techniques, multiple constraints can be included via simple matrix operations, thereby rendering the results less sensitive to Galactic extinction and misestimates of the radial selection function. We present a data analysis pipeline that we argue does justice to the increases in both quality and quantity of data that upcoming redshift surveys will provide. It uses three analysis techniques in conjunction: a traditional Fourier approach on small scales, a pixelized quadratic matrix method on large scales, and a pixelized KL eigenmode analysis to probe anisotropic effects such as redshift-space distortions.