Flow-Based Generative Emulation of Grids of Stellar Evolutionary Models
Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology（麻省理工学院卡弗里天体物理与空间研究所）；Institute for Astronomy, University of Hawai‘i（夏威夷大学天文研究所）
Marc Hon, Yaguang Li, Joel Ong
备注：
27 pages, 18 figures. Accepted for publication in ApJ. Code, animation, and interactive visualizations are available at https://github.com/mtyhon/modelflows/. Table 4 is also available as ancillary file attached to this submission
We present a flow-based generative approach to emulate grids of stellar evolutionary models. By interpreting the input parameters and output properties of these models as multi-dimensional probability distributions, we train conditional normalizing flows to learn and predict the complex relationships between grid inputs and outputs in the form of conditional joint distributions. Leveraging the expressive power and versatility of these flows, we showcase their ability to emulate a variety of evolutionary tracks and isochrones across a continuous range of input parameters. In addition, we describe a simple Bayesian approach for estimating stellar parameters using these flows and demonstrate its application to asteroseismic datasets of red giants observed by the Kepler mission. By applying this approach to red giants in open clusters NGC 6791 and NGC 6819, we illustrate how large age uncertainties can arise when fitting only to global asteroseismic and spectroscopic parameters without prior information on initial helium abundances and mixing length parameter values. We also conduct inference using the flow at a large scale by determining revised estimates of masses and radii for 15,388 field red giants. These estimates show improved agreement with results from existing grid-based modelling, reveal distinct population-level features in the red clump, and suggest that the masses of Kepler red giants previously determined using the corrected asteroseismic scaling relations have been overestimated by 5-10%.
Loosely Conditioned Emulation of Global Climate Models With Generative Adversarial Networks
Western Washington University（西华盛顿大学）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；Indiana University（印第安纳大学）；Joint Global Change Research Institute（联合全球变化研究所）；Computer Science Department, Western Washington University（西华盛顿大学计算机科学系）；Computing & Analytics Division, Pacific Northwest National Laboratory（太平洋西北国家实验室计算与分析部）；Earth and Atmospheric Sciences Department, Indiana University（印第安纳大学地球与大气科学系）
Evolution of young protoclusters embedded in dense massive clumps. A new grid of population synthesis SED models and a new set of L/M evolutionary tracks
The effects of surface fossil magnetic fields on massive star evolution: IV. Grids of models at Solar, LMC, and SMC metallicities
磁场可以通过质量损失淬火，磁制动和有效的角动量传输，我们的目标是在这项工作中量化的大质量恒星的演化模型的预测急剧变化。我们使用MESA软件工具来计算恒星结构和演化模型的广泛的主序星网格，以及等时线，考虑到归因于表面化石磁场的影响。该网格在初始质量（3-60 M $_\odot$）、表面赤道磁场强度（0-50 kG）和金属丰度（代表太阳邻域和麦哲伦云）方面密集分布。我们使用两个磁制动和两个化学混合方案，并比较模型预测的缓慢旋转，富氮（“组2”）恒星与观测的大麦云云。我们量化了一系列的初始场强，允许生产组2星，并发现典型的值（高达几公斤）导致的解决方案。在子网格之间，我们发现表面丰度和演化路径有显着的偏离。在我们的磁性模型中，由于快速自旋下降，与非磁性模型相比，化学混合总是效率较低。我们确定，准化学均匀的主序列演化的有效混合可以防止化石磁场。我们建议将这个演化模型网格与分光偏振和光谱观测进行比较，目的是i）重新审视已知磁星的恒星参数，ii）观测上限制不确定的磁制动和化学混合方案。
MESAlab: A Python pipeline for MESA grid processing with integrated GYRE/MESA-RSP execution
Konkoly Observatory, HUN-REN CSFK, MTA Centre of Excellence（孔科利天文台，HUN-REN 匈牙利科学院研究中心，MTA 卓越中心）；MTA–HUN-REN CSFK Lendület ”Momentum” Stellar Pulsation Research Group（MTA-HUN-REN 匈牙利科学院研究中心 Lendulet “动量”恒星脉动研究组）
Diameters and Temperatures VII: High-angular resolution measurements of Solar-type stars with the CHARA Array
Louisiana State University（路易斯安那州立大学）；Lowell Observatory（洛厄尔天文台）；Georgia State University（佐治亚州立大学）；University of Sydney（悉尼大学）；University of Hawaii（夏威夷大学）；Australian National University（澳大利亚国立大学）；University of Rochester（罗切斯特大学）
Toward a Comprehensive Grid of Cepheid Models with MESA. III. Evolutionary and Pulsation Relations for Models with Core and Envelope Overshooting
Nicolaus Copernicus Astronomical Centre, Polish Academy of Sciences（波兰科学院尼古拉·哥白尼天文学中心）；Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange（法国蔚蓝海岸大学、蔚蓝海岸天文台、法国国家科学研究中心、拉格朗日实验室）
Linking Young Stellar Object Morphology to Evolutionary Stages with Self-Organizing Maps
Universität Wien（维也纳大学）；Natural History Museum Vienna（维也纳自然历史博物馆）；Université de Genève（日内瓦大学）；Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, Hungarian Research Network (HUN-REN)（孔科利天文台，匈牙利研究网络（HUN-REN）地球与天文学研究中心）；CSFK, MTA Centre of Excellence（MTA卓越中心天文研究所）；Department of Experimental Physics, Institute of Physics, University of Szeged（塞格德大学物理学院实验物理系）；HITS gGmbH（海德堡理论研究所）
Modelling $δ$ Scuti pulsations: A new grid of p, g, and f modes across pre-main-sequence to post-main-sequence evolution
Centre for Astrophysics, University of Southern Queensland（南昆士兰大学天体物理中心）；Sydney Institute for Astronomy, School of Physics, University of Sydney（悉尼大学物理学院悉尼天文研究所）
Toward a Comprehensive Grid of Cepheid Models with MESA. IV. Modest Effects of Rotation on Blue Loops
Nicolaus Copernicus Astronomical Centre, Polish Academy of Sciences（波兰科学院尼古拉·哥白尼天文学中心）；Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange（蔚蓝海岸大学，蔚蓝海岸天文台，法国国家科学研究中心，拉格朗日实验室）
