Accurate and precise statistical methods for weak gravitational lensing

引力透镜效应——来自遥远光源的光通过干涉物质发生偏转——是一种了解我们宇宙的强大技术。星系形状的相干扭曲可以用来推断暗物质的属性，特别是它的空间分布（即它有多聚集或多光滑）以及它在整个宇宙历史中的演变。透镜对时空的几何形状很敏感，因此对宇宙的组成成分也很敏感。主要成分是所谓的“暗能量”，这是一种鲜为人知的能量密度来源，似乎模仿了爱因斯坦场方程中的宇宙常数项。了解暗能量的性质是我们理解物理学的基础，也是即将到来的欧几里得太空望远镜等宇宙学调查的主要科学驱动力之一。拥有精确的技术来测量天空中透镜强度波动的功率谱对于用欧几里得测量暗能量特性至关重要。学生将从宇宙微波背景分析中获得启发，发展统计方法，并将其应用于现实的宇宙剪切合成图。爱丁堡领导欧几里得的弱透镜分析，并主办英国科学地面段科学数据中心。将有机会在欧几里得弱透镜团队中工作，使学生能够接触到最先进的宇宙学调查。还将有机会将这些方法应用于当前数据。

Gravitational lensing - the deflection of light from distant luminous sources by intervening matter - is a powerful technique for understanding our Universe. Coherent distortions in the shapes of galaxies can be used to infer the properties of the intervening dark matter, in particular its spatial distribution (i.e. how clumped or how smooth it is) and its evolution throughout cosmic history. Lensing is sensitive to the geometry of space-time and hence to the constituent components of the Universe. The dominant component is the so-called "dark energy", a poorly-understood source of energy-density which appears to mimic a cosmological constant term in the Einstein field equations. Gaining an understanding into the properties of dark energy is fundamental to our understanding of physics and is one of the main science drivers for upcoming cosmology surveys such as the Euclid space telescope. Having accurate and precise techniques for measuring the power spectrum of fluctuations in the lensing strength over the sky will be crucial for measuring dark energy properties with Euclid. The student will develop statistical methods inspired by analyses of the cosmic microwave background and apply them to realistic synthetic maps of cosmic shear. Edinburgh leads the weak lensing analysis of Euclid and hosts the UK Science Ground Segment Science Data Centre. There will be the opportunity to work within the Euclid weak lensing team, giving the student access to a state-of-the-art cosmology survey. There will also be opportunities to apply the methods to current data.