RUI: WoU-MMA: Multi-Messenger Astronomy and Astrophysics with Gravitational-Wave Data

一百多年前，阿尔伯特·爱因斯坦在他的广义相对论中预言了引力波的存在，引力波是时空结构中以光速传播的涟漪。这些引力波是由宇宙中一些最剧烈的事件产生的，比如中子星碰撞和黑洞合并。当两颗中子星相撞时，中子星内部的物质被排出。在中子星的极端环境之外，这种物质是不稳定的，衰变迅速，辐射出的电磁波可以在数十亿光年之外被探测到。这些电磁事件被称为基洛诺瓦。然而，在类似银河系的星系中，千新星是非常罕见的事件（大约每百万年发生一次）。因此，为了有合理的机会探测到这些事件，我们需要能够看到宇宙深处，让我们能够进入大量的星系。这也意味着，我们将探测到的大多数千新星都将位于我们能到达的最远的地方，因此从地球上很难观测到。更复杂的是，这些事件也会迅速消失。因此，观测者在两颗中子星相撞后立即观测天空的正确区域是非常重要的。探测来自合并中子星的引力波将使我们能够定位天空区域，并计算由于这些碰撞而产生电磁发射的概率。PI将开发低延迟引力波警报基础设施的组成部分，该基础设施将使用引力波探测来促进世界各地和太空望远镜的后续观测。其次，中子星本身的结构在物理学中仍然是一个谜。这主要是因为没有办法在实验室中模拟类似中子星内部的极端环境。引力波向我们揭示了中子星内部物质的重要线索，这些线索可以用来提高我们对中子星结构的理解。PI将开发一种技术，将来自多个双中子星合并事件的引力波数据结合起来，比较中子星物质的不同理论模型。该工具还将帮助用户比较定制的模型，允许对目前没有任何理论预测的模型进行探索性研究。这两个项目的结果将为美国和世界各地的物理学家、天文学家和天体物理学家提供工具和数据，以进行进一步的科学研究。PI是一所地方公立大学的教授，他将指导他所在机构的本科生，让他们有机会处理大量数据并学习统计技术。这将使他们在日益数据驱动的世界中成为未来的科学家、工程师和/或数据分析师。PI将通过讲座、外展展览和教师培训项目与更广泛的公众接触，以确保传播所获得的知识。LIGO-Virgo合作组织了三次观测运行，从轨道中子星和黑洞的双星中探测到50多次引力波。随着探测器的按计划改进，我们期望在下一次LIGO运行中看到10倍以上的天体物理事件。此外，我们期望在2004年看到第四个引力波探测器——日本的KAGRA的落成。因此，增加探测器的灵敏度、更大的占空比和由于网络中额外的探测器而改进的天空灵敏度将大大提高检测率。从上次观察运行开始，目前的基础设施不足以满足这种高吞吐量的事件。PI承诺提供一个低延迟警报基础设施，能够处理引力波探测器预期增加的低延迟触发器。该基础设施将解决上次观测运行中导致警报过程延迟的关键问题。PI建议开发网络基础设施，以处理警报流，并在检测后不到10秒内向公众提供源分类和源属性信息。其次，PI还将开发一种技术，将合并中子星双星的多重引力波观测信息快速结合起来，以提高对中子星内部结构的理解。该工具将利用单一参数估计研究，该研究对中子星内部物质的性质（状态方程）是不可知的。然后，它将采用一系列有效的近似，以减少计算需求，从而能够快速计算任何两个中子星状态方程模型的证据比（贝叶斯因子）。这种方法可以推广到多事件联合贝叶斯因子的计算，从而对中子星状态方程有一个整体的认识。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。

More than a hundred years ago Albert Einstein in his general theory of relativity predicted the existence of gravitational waves, ripples in the fabric of spacetime that propagate at the speed of light. These waves are generated by some of the most violent events in the universe, like colliding neutron stars and coalescing black holes. When two neutron stars collide the matter inside the neutron star is expelled out. Outside the extreme environment of the neutron star this matter is unstable and decays rapidly, radiating electromagnetic waves that can be detected billions of lightyears away. These electromagnetic events are called Kilonova. A kilonova however is a very rare event (roughly happening once per million years) in a Milky Way like galaxy. Thus, to have a reasonable chance of detecting these events we need to be able to see deep into the universe, giving us access to a large number of galaxies. This also means that most of the kilonova that we will be detecting are going to be at the farthest distances that we can reach, and hence will be very faintly observable from Earth. To make matters more complicated, these events also rapidly fade away. Thus, it is very important that observers are looking at the right part of the sky immediately after two neutron stars have collided. Detection of gravitational waves from a coalescing neutron star will allow us to localize the region of the sky and calculate the probability of having an electromagnetic emission as a result of these collisions. The PI will develop components of a low-latency gravitational wave alert infrastructure that will use gravitational wave detections to facilitate follow-up observations using telescopes around the world and in space. Secondly, the structure of neutron stars itself continues to remain a mystery in physics. This is primarily because there is no way of emulating the extreme environment akin to the interior of a neutron star in a laboratory. Gravitational waves reveal to us important clues about the matter inside the neutron star that can be used to improve out understanding of their structure. The PI will develop a technology that will allow combining gravitational wave data from multiple binary neutron star coalescence events to compare different theoretical models of neutron star matter. The tool will also help the user to compare custom-made models, allowing exploratory studies on models that are not currently predicted by any theory. The results of both these projects will provide tools and data to physicists, astronomers, and astrophysicists in the US and around the world to pursue further scientific investigations. The PI, who is a professor at a regional public university, will mentor undergraduate students at his institution, giving them the opportunity to work on large volumes of data and learn statistical techniques. This will prepare them as future scientists, engineers, and/or data analysts in an increasingly data driven world. The PI will engage with the broader public through lectures, outreach exhibits, teacher training programs to ensure dissemination of knowledge acquired.The LIGO-Virgo collaboration has organized three observing runs which have led to more than fifty detection of gravitational waves from binaries of orbiting neutron stars and black holes. With scheduled improvements in the detectors we expect to see as many as ten times more astrophysical events in the next LIGO run (O4). Furthermore, in O4 we expect to see the inauguration of the fourth gravitational wave detector, KAGRA in Japan. Thus, an increased sensitivity of the detectors, greater duty cycle and improved sky-sensitivity due to an extra detector in the network are going to greatly increase the rate detection. The infrastructure currently in place from the last observing run is inadequate to meet this high throughput of events. The PI commits to deliver a low-latency alert infrastructure that is capable of handling the expected increase of low-latency triggers from the gravitational wave detectors. This infrastructure will address the key issues of the last observing run that resulted in delays in the alert process. The PI proposes to develop cyberinfrastructure to process alert streams and provide source-classification and source-properties information to the public in less 10 seconds after detection. Secondly, the PI will also develop a technology that will rapidly combine information from multiple gravitational wave observations of coalescing neutron star binaries to improve the understanding of the internal structure neutron stars. This tool will leverages upon a single parameter estimation study that is agnostic about the nature of the matter inside the neutron star (equation of state). It will then employ a series of valid approximations, to reduce the computational requirement enabling the rapid calculation of the ratio of the evidences (Bayes-factor) of any two models of the neutron star equation of state. This method can then be extended to the computation of joint Bayes-factors of multiple events, giving us a holistic picture about the neutron star equation of state.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.