论文标题
压缩组合探针：接头透镜和聚类分析的红移权重
Compressing combined probes: redshift weights for joint lensing and clustering analyses
论文作者
论文摘要
将不同的观察探针（例如星系聚类和弱透镜）结合在一起，是一种有前途的技术，可以通过即将进行的深色能量实验来揭示宇宙的物理学。尽管该策略可显着改善参数约束，从而减少单个分析的脱落并控制系统学，但从数千万星系中处理数据并不是一项琐碎的任务。在这项工作中，我们得出并测试了一个新的估计值，以进行关节聚类和镜头数据分析，最大化科学回报并降低计算成本。我们的估计器通过对感兴趣的参数最敏感的组件加权来压缩数据，而不会丢失信息，从而考虑到两个探针之间的互相关信息。我们得出最佳的红移权重，在测试给定的统计和宇宙学模型时，可以应用于单个星系。
Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. Whilst this strategy significantly improves parameter constraints, decreasing the degeneracies of individual analyses and controlling the systematics, processing data from tens of millions of galaxies is not a trivial task. In this work we derive and test a new estimator for joint clustering and lensing data analysis, maximising the scientific return and decreasing the computational cost. Our estimator compresses the data by up-weighting the components most sensitive to the parameters of interest, with no loss of information, taking into account information from the cross-correlation between the two probes. We derive optimal redshift weights which may be applied to individual galaxies when testing a given statistic and cosmological model.
