Systematics in Weak Lensing and Galaxy Clustering

随着新一代观测(如欧几里得、LSST、DESI)的到来，我们正在进入一个高精度宇宙学的新时代。与以前的调查相比，数据收集的精度和规模都有所提高，这让我们对宇宙信息有了新的见解。大量的数据使得快速和计算成本低廉的分析变得困难，但如果可以做到这一点，就可以实现非常精确和健壮的约束。通过宇宙切变分析和星系团等物质探测器，我们可以追踪物质在我们宇宙中的分布，并利用这些信息来约束宇宙学。这些方法可以组合在多探头方法中，例如3x2点相关函数分析，它使用剪切相关、聚类和它们的交叉项，以允许更精确的参数约束。然而，如果我们的统计不确定性减少了，我们必须更仔细地研究由于我们分析中的假设、退化和概括而引起的系统不确定性。以前被统计不确定性掩盖的一些系统性偏差可能已经大到严重限制了我们的约束能力。最重要的是，探测器内部和探测器之间的系统效应之间的相互作用可能会导致进一步的限制，例如内在对准和光度学红移不确定性之间的限制。因此，准备这些调查的一个重要步骤是了解和减轻系统学可能对它们施加的限制。我的博士项目围绕着优化来自弱透镜和星系团分析的参数约束，重点关注可能影响即将到来的调查的约束力的系统效应和系统学的组合。作为CDT的一部分，我正在攻读博士学位，其中的一个组成部分是参加教授数据科学方法的模块。我将使用我在这些模块中学到的技术来了解有问题的系统效应，并改进它们导致的错误。我的目标是使用机器学习和深度学习技术来消除系统影响和去耦合系统学。更广泛地说，我希望将这些方法应用于来自3x2相关函数的参数约束，目的是提高速度和约束能力。

With a new generation of surveys on the horizon (e.g. Euclid, LSST, DESI) we are entering a new era of high-precision cosmology. The increase in precision and the scale of data collections compared to previous surveys gives us a new insight into cosmological information. The large amount of the data makes fast and computationally cheap analysis difficult, but if this can be done very precise and robust constraints can be achieved. Through matter probes such as cosmic shear analysis and galaxy clustering we can trace the matter distribution in our universe and use this information to constrain cosmology. These methods can be combined in multi-probe methods such as thein 3x2-point correlation function analysis, which uses both shear-shear correlation, clustering, and their cross-term, to allow more precise parameter constraints. However, are our statistical uncertainties are reduced, we must look closer at the systematic uncertainties induced due to assumptions, degeneracies, and generalisations in our analysis. It's possible that some systematic biases previously concealed by statistical uncertainty are large enough to severely limit our constraining power. On top of this, interactions between systematic effects within and between probes may cause further limitations, such as that between intrinsic alignments and photometric redshift uncertainty. Therefore, an important step in preparation for these surveys is to understand and mitigate the limitations systematics may impose upon them.My PhD project revolves around optimising parameter constraints from weak lensing and galaxy clustering analysis, with a focus on the systematic effects and combinations of systematics that may affect the constraining power of upcoming surveys. I am pursuing my PhD as a part of the CDT, and a component of this is taking part in modules teaching data science methods. I will use the techniques I learn in these modules to understand problematic systematic effects and improve the errors they induce. I aim to use machine learning and deep learning techniques to remove systematic effects and decouple systematics. More broadly, I hope to apply these methods to the parameter constraints from the 3x2 correlation function with the aim to improve the speed and constraining power.