论文标题
通过优化的光谱星系调查的优化角功率谱模拟现实的数据分析
Towards simulating a realistic data analysis with an optimised angular power spectrum of spectroscopic galaxy surveys
论文作者
论文摘要
角功率谱是分析观察到的星系数计数波动的天然工具。在标准分析中，角星系分布将其切成同心红移箱，并考虑其谐波系数之间所有谐波系数的相关性 - 被称为“断层扫描”的过程。但是，鉴于垃圾箱的数量越来越多，宇宙学光谱星系调查的无与伦比的数据质量将使这种方法在计算上不可行。在这里，我们对合成数据进行测试，一种在先前的研究中提出的一种新方法，以节省计算时间。根据这种方法，整个星系红移分布被细分为厚的垃圾箱，忽略了它们之间的跨箱相关性。然而，每个厚的箱都进一步细分为较薄的垃圾箱，在这种情况下，所有跨蛋白相关性。我们创建一个模拟数据集，然后在贝叶斯框架中分析，并在贝叶斯框架中进行分析。我们确认新提出的方法节省了计算时间，并提供了超过标准方法的结果。
The angular power spectrum is a natural tool to analyse the observed galaxy number count fluctuations. In a standard analysis, the angular galaxy distribution is sliced into concentric redshift bins and all correlations of its harmonic coefficients between bin pairs are considered---a procedure referred to as `tomography'. However, the unparalleled quality of data from oncoming spectroscopic galaxy surveys for cosmology will render this method computationally unfeasible, given the increasing number of bins. Here, we put to test against synthetic data a novel method proposed in a previous study to save computational time. According to this method, the whole galaxy redshift distribution is subdivided into thick bins, neglecting the cross-bin correlations among them; each of the thick bin is, however, further subdivided into thinner bins, considering in this case all the cross-bin correlations. We create a simulated data set that we then analyse in a Bayesian framework. We confirm that the newly proposed method saves computational time and gives results that surpass those of the standard approach.
