Supermassive black holes through cosmic time: Exploiting the era of Big Data in astronomy

穿越宇宙时间的超大质量黑洞：利用天文学大数据时代

• 批准号: 2488912
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2488912
• 关键词: Supermassive; black; holes; through; cosmic

How do supermassive black holes form? How are they influencing and are influenced by their host galaxies? The 2020s will see a see change in how we tackle the big questions in astronomy. With the advent of the Vera Rubin Observatory's Legacy Survey of Space and Time (LSST), the entire sky will be observed within 2-3 days in several optical bands to unprecedented depth over a total span of 10 years. We will be able to study the evolution of galaxies with samples containing billions of objects. At the same time, the repeat observations will provide us with the dynamic picture of the growth of supermassive black holes in the centre of these galaxies. In Southampton, we are leading several LSST-related research activities on galaxy evolution and active galactic nuclei (AGN). The key to solving these questions with the vast amount of data becoming available soon is knowledge of techniques to handle, analyse, and interpret them - the "Big Data Challenge in Astronomy." Dr Sebastian Hoenig and Dr Manda Banerji are offering a PhD studentship as part of the Centre of Doctoral Training (CDT) DISCnet. The student will be working on multi-wavelength surveys, including the Southampton-led VISTA Extragalactic Infrared Legacy Survey VEILS, and will prepare and exploit LSST and supporting survey (including 4MOST) data. This will range from compiling and analysing LSST pre-cursor data to leading spectroscopic follow-up observations of targets of interest. The student will benefit from the A-graded training and research environment, including residential courses in Machine Learning, Statistics, Big Data, and Parallel programming on High-Performance Computers.

超大质量黑洞是如何形成的？它们是如何影响它们的宿主星系的，又是如何被它们影响的？本世纪20年代，我们将看到解决天文学重大问题的方式发生重大变化。随着维拉鲁宾天文台的传统时空调查(LSST)的到来，整个天空将在2-3天内在几个光学波段被观测到前所未有的深度，总跨度为10年。我们将能够用包含数十亿个天体的样本来研究星系的演化。同时，重复观测将为我们提供这些星系中心超大质量黑洞增长的动态图景。在南安普敦，我们正在领导几项与LSST有关的星系演化和活动星系核(AGN)的研究活动。随着海量数据即将面世，解决这些问题的关键是掌握处理、分析和解释这些数据的技术知识--“天文学中的大数据挑战”。Sebastian Hoenig博士和Manda Banerji博士正在提供博士研究生学位，作为博士培训中心(CDT)DISCnet的一部分。该学生将从事多波长调查，包括南安普顿领导的Vista河外红外遗产调查面纱，并将准备和利用LSST和支持性调查(包括4MOST)数据。这将包括汇编和分析LSST光标前数据，以及对感兴趣目标进行领先的光谱后续观测。学生将受益于A级的培训和研究环境，包括机器学习、统计学、大数据和高性能计算机上的并行编程的驻留课程。