Stellar populations in galaxies with the large galaxy survey SDSS-IV/MaNGA

候选人将在APO（MaNGA）的项目Mapping Nearby Galeries工作，这是在新墨西哥州斯隆2.5米望远镜上进行的第四代斯隆数字巡天（SDSS-IV）的一部分。MaNGA是一种基于光纤的多目标IFU，将在2020年夏季之前的6年活动中瞄准10，000个星系。MaNGA将允许内部的运动学和空间分辨性能的恒星人口和气体内星系被研究作为一个功能的localenvironment和晕质量的第一次。在这个特别的项目中，我们将研究星系的恒星人口特性，即它们的形成年龄和金属丰度，在星系中作为星系环境和暗物质晕质量的函数在空间上如何变化。这项工作是我们在戈达德等人（2017）和帕里克等人（2018）中与以前和现在的博士生一起发表的工作。该项目将涉及python编程，包括星系光谱，大数据和我们的超级计算机。科学分析将提供关键的洞察力的物理过程，管理的形成和演变的星系和结构在宇宙中。

The candidate will work on the project Mapping Nearby Galaxies at APO (MaNGA), which is part ofthe fourth generation Sloan Digital Sky Survey (SDSS-IV) conducted on the Sloan 2.5m Telescope inNew Mexico. MaNGA is an optical fiber-based multi-object IFU that will target 10,000 galaxies over a6 year campaign operating until summer 2020. MaNGA will allow the internal kinematics and spatiallyresolved properties of stellar populations and gas inside galaxies to be studied as a function of localenvironment and halo mass for the very first time. In this particular project we will study how stellarpopulation properties of galaxies, i.e. their formation ages and metal abundances, vary spatially in galaxies as a function of galaxy environment and dark matter halo mass. This work follows on workwe have published with previous and current PhD students in Goddard et al (2017) and Parikh et al(2018). The project will involve python programming and include work with galaxy spectra, big data,and our supercomputer. The scientific analysis will provide key insight into the physical processes thatgovern the formation and evolution of galaxies and structure in the Universe.