论文标题

LSS调查中缓解污染:方法的比较

Mitigating contamination in LSS surveys: a comparison of methods

论文作者

Weaverdyck, Noah, Huterer, Dragan

论文摘要

未来的大规模结构调查将测量数十亿个星系的位置和形状。此类目录的精度将需要对观察到的磁场的系统污染进行一致的处理。我们比较了几种从星系聚类测量中删除此类系统的现有方法。我们展示了如何在公共回归框架下解释所有方法,包括流行的伪$ C_ \ ELL $模式投影和模板减法方法,并使用它来提出改进的估计器。我们展示了如何使用旨在减轻功率谱系中系统学的方法来生成清洁地图,这对于宇宙学分析以外的宇宙学分析是必不可少的,并且我们扩展了当前方法以处理观察到的地图和功率光谱中的下一阶乘法污染。提出了两种新的缓解方法,其中包含了当前最新方法的理想特征,同时更容易实施。从黑暗能源调查的第5年开始,我们研究了所有方法的性能,我们测试了它们对各种分析案例的稳健性。与当前方法相比,我们提出的方法可产生改进的地图和功率谱,同时几乎没有用户调整。我们以未来调查中的系统缓解系统缓解的建议结尾,并注意提出的方法通常适用于银河系分布超出具有空间系统学领域的任何领域。

Future large scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogs will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-$C_\ell$ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.

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