EAPSI: Determining Disk Galaxy Evolutionary State through Spatially-Resolved Gas Mass Fractions

目前对星系形成和演化的研究试图回答一个主要问题：我们观察到的异质宇宙--在由极其紧密的恒星和热气组成的岛屿之间的大片几乎空旷的空间--是如何从一个压倒性的均匀开始--大爆炸--形成的？在单个星系中，气体质量分数，即热等离子体和冷原子分子氢中包含的质量百分比，与恒星中包含的质量相反，有力地表明了这一点。一小部分气体表明--总的来说--形成新恒星的演化系统的能力降低，而较大的气体部分表明有可能形成大的恒星和星际介质的金属浓缩。与陈艳梅教授(南京大学：南京，江苏，中国)合作，PI将构建统计上稳健的恒星质量估计，并与他现有的空间分辨气体质量测量进行比较。气体质量分数的径向变化将与星系总质量、恒星形成率和星系环境密度的估计进行比较。在积分场光谱测量(如MANGA、SAMI和CALIFA)的新时代，响应性、健壮性和廉价的恒星-连续谱拟合方法是与大型夜间数据流相对应的必要方法。大多数恒星质量估算方法的计算成本都很高，而且没有利用统计学和机器学习方面的现代进步。陈艳梅教授发展了一种拟合恒星连续体的方法，该方法依赖于单星群(SSP)模型库的一次性主成分分析(PCA)，这将在计算时间上产生数量级的改进，并将使更大、更灵活的SSP库的使用成为可能。PI已经获得了一套完全理论的SSP模型，其光谱分辨率超过了漫画。这类SSP包括近红外特征，如CaII三重态(打破年龄-金属丰度简并所必需的)，并改进了现有的热脉动渐近巨型分支(TP-AGB)模型。将高分辨率恒星库与陈的PCA代码(由PI从IDL转换为Python)相结合，将在可分辨恒星质量估计方面产生可测量的改进。当与使用新的光学光谱方法(而不是通过昂贵的无线电波段跟踪)估计的分解的总气体质量(HI+H2)配对时，将产生对附近星系中的恒星和气体的普查。这些对星系演化状态的单源估计将改善目前对银河系化学演化和质量组装的了解，并将银河系置于宇宙环境中。该奖项由东亚和太平洋夏季学院计划支持一名美国研究生的夏季研究，由美国国家科学基金会和中国的科技部联合资助。

Current research in galaxy formation and evolution seeks to answer one main question: how did the heterogeneous universe we observe--with its vast tracts of virtually-empty space between immensely compact islands of stars and hot gas--form from an overwhelmingly homogeneous beginning, the Big Bang? This is indicated robustly in individual galaxies by the gas mass fraction, the percentage of mass contained in both hot plasma and cool atomic & molecular hydrogen--as opposed to mass contained in stars. A small gas fraction indicates--in general--an evolved system with reduced capacity for forming new stars, while a large gas fraction suggests the potential for large star formation and metal-enrichment of the interstellar medium. In collaboration with Prof. Yanmei Chen (Nanjing University: Nanjing, Jiansu, China), the PI will construct statistically-robust estimates of stellar mass, and compare to his existing measurements of spatially-resolved gas mass. The radial variation of gas mass fraction will be compared with estimates of total galaxy mass, star formation rate, and galaxy environment density.In the new era of integral-field spectroscopic surveys (such as MaNGA, SAMI, and CALIFA), responsive, robust, and cheap methods of stellar-continuum fitting are necessary counterparts to large, nightly datastreams. Most methods of stellar-mass estimation are computationally costly, and do not take advantage of modern advances in statistics and machine learning. Prof. Yanmei Chen has developed a method of fitting the stellar continuum, which relies on the one-off principal-component analysis (PCA) of a library of single stellar population (SSP) models, which yields order-of-magnitude improvements in compute time and will enable the use of larger, more flexible SSP libraries. The PI has obtained a set of fully-theoretical SSP models, with a spectral resolution exceeding that of MaNGA. Such SSPs include near-IR features like the CaII triplet (necessary for breaking the age-metallicity degeneracy), and improve on existing models of the thermally-pulsating asymptotic giant branch (TP-AGB). Combining the high-resolution stellar library with Chen's PCA code (translated by the PI from IDL to Python) will yield measurable improvements in resolved stellar-mass estimates. When paired with resolved total gas mass (HI + H2), estimated using new optical-spectroscopic methods (rather than from expensive, radio-band follow-up), a census of stars and gas in nearby galaxies will result. These single-source estimates of galaxy evolutionary state will improve current knowledge of galactic chemical evolution and mass assembly, and place the Milky Way in a cosmic context.This award under the East Asia and Pacific Summer Institutes program supports summer research by a U.S. graduate student and is jointly funded by NSF and the Ministry of Science and Technology of China.