WoU-MMA: Collaborative Research: Constraining the Nuclear Equation of State and Neutron Star Astrophysics Through Multi-messenger and Multi-object Observations of Neutron Stars

第一颗已知的合并双中子星（GW170817）的革命性发现和多信使后续行动表明，观察和分析这种合并可以提供独特的机会。罗彻斯特理工学院和田纳西大学诺克斯维尔分校之间的一项科学合作将开发利用引力波（GW）观测和电磁观测所需的研究基础设施，以确定致密物质的性质。研究小组将开发一种灵活的程序，直接从多个中子星（NS）的多次测量中，使用GW测量合并，星系NS的x射线观测以及由此产生的千新星爆炸的光曲线和光谱，来自一致地推断中子星（NS）的核状态方程（EOS）。EOS是一个方程，就像物理学中的理想气体定律一样，它描述了在给定的物理条件下物质的状态。利用衍生的工具来理解核EOS，研究人员将确定双星合并是否对观察到的r过程元素丰度负责。快速中子俘获过程（r-process）是一组核反应，许多比铁重的原子元素通过该反应在天体物理环境中产生。该项目将包括培养年轻研究人员成为第一代真正的多信使天体物理学家，主要研究人员将创建新的广义相对论入门课程材料，以GW天文学的成果教育下一代科学家。该研究计划有两个主要目标：限制致密核物质的性质，并确定是否仅靠NS合并就能解释r过程元素的丰度。研究小组将为千新星光曲线和光谱创建新的高精度替代模型，并根据详细的辐射传递计算进行校准。为了使用来自多个信使和多个对象的数据进行推断，其中每个数据源以不同的方式连接到EOS，研究人员将创建一个统一的贝叶斯推理引擎，称为Concordance。这个推理机将约束致密核物质和中子星核心的组成。它还将推断出NS合并率、抛射物质量和抛射物组成，这将使科学家们能够预测当前局部宇宙中每个元素的r过程丰度，这是由于观测到的双NS合并的数量。他们会将自己的预测与观察结果进行比较；确定是否需要以及需要什么样的缺失种群（如黑洞(BH)-NS）来调和观测结果与元素丰度；看看失踪的人口是否与形成情景和观测限制相一致。这个项目推进了NSF宇宙大构想窗口的目标。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The revolutionary discovery and multi-messenger follow-up of the first known merging binary neutron star (GW170817) has demonstrated the unique opportunities that observations and analysis of such mergers can provide. A scientific collaboration between Rochester Institute of Technology and the University of Tennessee, Knoxville, will develop the research infrastructure needed to exploit gravitational wave (GW) observations and electromagnetic observations in order to determine the nature of dense matter. The research team will develop a flexible procedure to self-consistently infer the nuclear equation of state (EOS) for neutron stars (NS), directly from multiple measurements of many NS, using GW measurements of mergers, X-ray observations of galactic NS, and light curves and spectra from the resulting kilonova explosion. An EOS is an equation, like the ideal gas law of physics, which describes the state of matter under a given set of physical conditions. Using the tools derived to understand the nuclear EOS, the investigators will determine if binary mergers are responsible for the observed r-process elemental abundances. The rapid neutron-capture process (r-process) is a set of nuclear reactions by which many of the atomic elements heavier than iron are produced in astrophysical settings. The project will include the training of young researchers as the first generation of truly multi-messenger astrophysicists, and the principal investigators will create new course materials for introductory general relativity, to educate the next generation of scientists in results from GW astronomy. The research program has two major goals: to constrain the nature of dense nuclear matter and to determine whether NS mergers alone explain the abundances of r-process elements. The research team will create new high-precision surrogate models for kilonova light curves and spectra, calibrated to detailed radiative-transfer calculations. To draw inferences with data from multiple messengers and multiple objects, where each data source is connected to the EOS in a different way, the researchers will create a unified Bayesian inference engine, called Concordance. This inference engine will constrain dense nuclear matter and the composition of the neutron star core. It will also infer the NS merger rate, ejecta mass, and ejecta composition, which will allow the scientists to predict the element-by-element r-process abundances in the present-day local universe due to the observed population of binary NS mergers. They will compare their prediction to observations; determine whether and what kind of missing population (like black hole (BH)-NS) would be required to reconcile observations with element abundances; and see whether that missing population is consistent with formation scenarios and observational constraints. This project advances the goals of the NSF Windows on the Universe Big Idea.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.