Stronger together: Joint probes for the measurement of the neutrino mass using the Hyper Suprime-Cam survey

该项目的主要目标之一是开发一个分析管道，可以在弱透镜和星系集群等宇宙学观测中寻找大质量中微子的影响。特别是，我建议开发一种基于高斯过程回归的快速预测方案，称为仿真器，根据晕偏差和晕质量函数对这些观测量进行理论预测。另一个目标是使用仿真器分析来自Hyper Suprime Cam Survey的红移空间聚类统计。N体模拟分析。我开发了一些工具来分析红移空间中N体模拟的输出。我测量的N体模拟使用晕占据分布模型模拟模拟星系人口的四极和四极相关函数。我研究了改变星系性质的影响以及增加速度偏差的影响。我进一步研究了晕偏差，通过补充我现有的分析，从聚类分析的偏差测量。开发预测工具。我继续开发用于分析星系团数据的预测工具，特别是那些可以在红移空间中使用的工具。我对模拟器需要覆盖的星系属性参数空间进行了详细的研究，以便将其应用于调查。我还研究了使用其他统计数据的可能性，例如相关函数，但我发现模拟的大小不够。

One of the main goals of this project is to develop an analysis pipeline that could look for the effects of massive neutrinos in cosmological observables such as weak lensing and galaxy clustering. In particular, I proposed to develop a fast prediction scheme based on Gaussian Process regression, called emulators, to make theoretical predictions for these observational quantities based on the halo bias and halo mass function. Another goal was to analyze the redshift space clustering statistics from the Hyper Suprime Cam Survey using the emulators.1.1. Analysis of N-body simulations. I developed tools to analyze the outputs of N-body simulations in redshift space. I measured the monopole and quadrupole correlation functions from N-body simulations using a halo occupation distribution model to model a mock galaxy population. I studied the effect of changing the galaxy properties as well as the effect of adding velocity bias.I further investigated the halo bias by complementing my existing analysis with bias measurements from clustering statistics.1.2. Development of Prediction Tools. I continued to develop prediction tools for the analysis of galaxy clustering data, especially those that can be used in redshift space. I performed a detailed study of the parameter space of galaxy properties needed to be covered by the emulator in order for it to be applied to a survey.I also investigated the possibility of using other statistics, e.g. correlation function, but I found that the sizes of the simulations weren't suffcient.