Dynamics of compact objects in dense star clusters and implications for gravitational wave detections

Ligo-Virgo干涉仪已经探测到50个双黑洞合并，未来还会探测到数百个。这组新的数据将为研究致密物体（如黑洞和中子星）的特性以及它们形成的环境提供重要线索。需要对导致致密物体合并的过程的理论理解的发展，这将使分析和解释大量的新探测成为可能。合并的紧密天体双星可以在以下情况下形成：(i)星系场中大质量双星的演化；（ii）星团长期演化中的动力学相互作用。我们将对情景（ii）做出第一个精确的预测，我们将与来自Ligo和Virgo的引力波数据进行比较，以确定双黑洞合并是主要来自星系团还是星系场。该学生将基于最先进的软件开发一个数值框架，以预测稠密星团中紧凑物体合并产生的引力波。通过将理论模型的预测与观测结果进行比较，他们将确定LIGO-Virgo探测到的引力波源是如何形成的。天体物理学进入了一个新的黄金时代。先进的LIGO和VIRGO正在运行；新的探测器，如KAGRA和LIGO印度将很快投入使用，LISA将在2030年代飞行。该项目将为物理解释这一前所未有的新数据财富提供理论框架。

The Ligo-Virgo interferometers have already detected 50 binary black hole mergers and hundreds to come. This new set of data will provide important clues to the properties of compact objects such as black holes and neutron stars and to the environments in which they form. The development of a theoretical understanding of the processes leading to compact object coalescence is required, which will enable to analyse and interpret the large number of new detections.Merging compact-object binaries can form as the result of: (i) the evolution of massive binary stars in the field of a galaxy; and (ii) dynamical interactions in the secular evolution of star clusters. We will make the first precise prediction for scenario (ii), which we will compare to gravitational wave data from Ligo and Virgo to establish whether binary black hole mergers come predominantly from clusters or the galactic field. The student will develop a numerical framework based on state-of-the-art software to make predictions for the gravitational waves produced by merging compact-objects in dense star clusters. By comparing the predictions of theoretical models to observations they will determine how the gravitational wave sources detected by LIGO-Virgo are formed.Astrophysics has entered a new Golden Age. Advanced LIGO and VIRGO are operational; new detectors such as KAGRA and LIGO India will soon come online, and LISA will fly in 2030s. This project will provide a theoretical framework for the physical interpretation of this wealth of unprecedented new data.