Collaborative Research: SI2-SSE: Modules for Experiments in Stellar Astrophysics

恒星作为最常见的观测天体，一直处于天体物理研究的前沿。探测器、计算机处理能力、网络和数据存储方面的技术进步使新的天空测量成为可能。其中许多搜索光学波长的瞬变事件，例如Palomar瞬变工厂和泛星S1，它们探测越来越大的天空区域和越来越暗的来源，开辟了巨大的“时间域天文学”的发现空间。最近的开普勒和COROT太空任务实现了对10万多颗恒星的几乎连续监测。从这些调查中发现的恒星包括关于恒星演化的揭示，罕见恒星，不寻常的爆炸结果，以及非常复杂的双星系统。随着天基勘测盖亚和地面大型天气观测望远镜的实现，不久的将来前景广阔。这股数据海啸产生了对计算恒星天体物理学中可靠和公开可用的研究和教育工具的新需求，这种工具将从这些发现中获得全部科学利益，同时也创造了一个合作环境，在这个环境中，理论、计算和解释可以结合在一起，解决关键的科学问题。恒星社区的这种需求导致我们在2011年发布了恒星天体物理实验模块(MESA)软件项目。在该奖项的支持下，梅萨已经并将继续推动恒星社区以及系外行星、银河系和宇宙学社区的创新。教育工作者在本科生和研究生的恒星演化课程中广泛部署了MESA，因为MESA是一个社区平台，拥有为前沿科学研究提供积极支持的网络。恒星天体物理研究和所有依赖恒星天体物理的社区将通过MESA的持续创新发展而得到显著加强。该奖项支持恒星天体物理实验模块(MESA)软件项目和用户社区。梅萨解决了控制恒星演化的一维完全耦合的结构和组成方程。它基于隐式有限差分格式，具有自适应网格细化和复杂的时间步长控制；最先进的模块提供状态方程、不透明度、核反应速率、元素扩散、边界条件和恒星质量的变化。MESA是一个开源库，它采用了当代的数值方法，支持基于OpenMP的共享内存并行，并且是考虑到现在和未来的多核和多线程架构而编写的。MESA结合了强大、高效、线程安全的数值和物理模块，用于模拟从极低质量到大质量恒星的广泛恒星演化场景。台地及其适用领域的创新在继续增长，最近才扩大到包括巨行星、振荡和自转。该项目将支持MESA作为恒星天体物理学的关键软件基础设施，同时建立新的科学和教育网络。

As the most commonly observed objects, stars remain at the forefront of astrophysical research. Technical advances in detectors, computer processing power, networks and data storage have enabled new sky surveys. Many of these search for transient events at optical wavelengths, such as the Palomar Transient Factory and Pan-STARRS1 that probe ever-larger areas of the sky and ever-fainter sources, opening up the vast discovery space of "time domain astronomy". The recent Kepler and COROT space missions achieved nearly continuous monitoring of more than 100,000 stars. The stellar discoveries from these surveys include revelations about stellar evolution, rare stars, unusual explosion outcomes, and remarkably complex binary star systems. The immediate future holds tremendous promise, as both the space-based survey Gaia and the ground based Large Synoptic Survey Telescope come to fruition. This tsunami of data has created a new demand for a reliable and publicly available research and education tool in computational stellar astrophysics that will reap the full scientific benefits of these discoveries while also creating a collaborative environment where theory, computation and interpretation can come together to address critical scientific issues. This demand by the stellar community led to our release of the Modules for Experiments in Stellar Astrophysics (MESA) software project in 2011. MESA has driven, and will continue to drive with support from this award, innovation in the stellar community as well as the exoplanet, galactic, and cosmological communities. Educators have widely deployed MESA in their undergraduate and graduate stellar evolution courses because MESA is a community platform with an active support network for leading-edge scientific investigations. Stellar astrophysics research, and all the communities that rely on stellar astrophysics, will be significantly enhanced by sustaining innovative development of MESA.This award supports the Modules for Experiments in Stellar Astrophysics (MESA) software project and user community. MESA solves the 1D fully coupled structure and composition equations governing stellar evolution. It is based on an implicit finite difference scheme with adaptive mesh refinement and sophisticated timestep controls; state-of-the-art modules provide equation of state, opacity, nuclear reaction rates, element diffusion, boundary conditions, and changes to the mass of the star. MESA is an open source library that employs contemporary numerical approaches, supports shared memory parallelism based on OpenMP, and is written with present and future multi-core and multi-thread architectures in mind. MESA combines the robust, efficient, thread-safe numerical and physics modules for simulations of a wide range of stellar evolution scenarios ranging from very-low mass to massive stars. Innovations in MESA and its domain of applicability continues to grow, just recently extended to include giant planets, oscillations, and rotation. This project will sustain MESA as a key piece of software infrastructure for stellar astrophysics while building new scientific and educational networks.