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：我们所观察到的异质宇宙——在极其紧凑的恒星岛和热气体之间有着大片几乎空无一物的空间——是如何从一个极其均匀的开始——大爆炸——形成的？这一点在单个星系中可以通过气体质量分数（即热等离子体和冷原子分子氢所含质量的百分比）有力地表明，而恒星所含质量则相反。一般来说，一个小的气体部分表明，一个进化的系统形成新恒星的能力降低了，而一个大的气体部分表明，潜在的大恒星形成和星际介质的金属富集。在与陈艳梅教授（南京大学：南京，中国）的合作下，PI将构建统计上可靠的恒星质量估计，并与他现有的空间分辨气体质量测量结果进行比较。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。在积分场光谱调查的新时代（如MaNGA、SAMI和CALIFA），响应灵敏、健壮且廉价的恒星连续体拟合方法是大型夜间数据流的必要对应。大多数估算恒星质量的方法在计算上都很昂贵，而且没有利用统计学和机器学习方面的现代进步。陈艳梅教授开发了一种拟合恒星连续体的方法，该方法依赖于单恒星群（SSP）模型库的一次性主成分分析（PCA），该方法在计算时间上产生了数量级的改进，并将允许使用更大，更灵活的SSP库。PI获得了一套完全理论化的SSP模型，其光谱分辨率超过了MaNGA。这些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支（TP-AGB）模型。将高分辨率恒星库与Chen的PCA代码（由PI从IDL翻译到Python）相结合，将在分辨恒星质量估计方面产生可测量的改进。当与分解的总气体质量（HI + H2）配对时，使用新的光谱学方法（而不是昂贵的无线电波段跟踪）进行估计，就可以对附近星系中的恒星和气体进行普查。这些对星系演化状态的单一来源估计将改善目前对星系化学演化和质量聚集的了解，并将银河系置于宇宙背景中。该奖项隶属于东亚和太平洋暑期研究所项目，由美国国家科学基金会和中国科技部共同资助，支持美国研究生的暑期研究。

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.