RUI: Numerical Simulations of Neutron Stars, Black Holes and Gravitational Radiation

该奖项支持鲍登学院（Bowdoin College）在计算物理方面的研究和教育项目，这是一所位于缅因州不伦瑞克的高选择性本科院校。在重力波源模拟（数值相对论）和计算天体物理学领域的支持研究为本科生提供了参与的机会。研究目标包括对中子星和黑洞在双星轨道上的数值模拟，其主要动机是利用新一代引力波激光干涉仪（包括激光干涉仪引力波天文台（LIGO））探测这些物体的引力辐射。为了识别和解释任何观测到的信号，并提取它们的天体物理内容，需要对信号源建立理论模型。中子星和黑洞的极端环境要求在爱因斯坦广义相对论的框架内对它们进行建模。该奖项支持的研究活动旨在发展必要的数值算法，在数值上构建这样的理论模型，预测引力波信号以与未来的观测进行比较，并回答相关的天体物理问题。本科生将积极参加计算物理研究小组，为他们提供“动手”的机会。研究经验和产生丰富的研究学习环境。学生将从事各种定义良好、易于管理和有意义的项目，包括，例如，对先前结果的概括和扩展，以及对简单模型问题的探索。他们还将有机会与其他机构的科学家合作，并在会议和出版物上展示他们的工作，使这种研究经历成为研究生培训和其他未来科学及其他职业的非常宝贵的准备。

This award supports a program of research and education in computational physics at Bowdoin College, a highly selective undergraduate institution located in Brunswick, Maine. The supported research, in the areas of gravitational wave source simulations (numerical relativity) and computational astrophysics, provides opportunities for undergraduate students to participate. The research goals, involving numerical simulations of neutron stars and black holes in binary orbit, are primarily motivated by the prospect of detecting gravitational radiation from such objects with the new generation of gravitational wave laser interferometers, including the Laser Interferometer Gravitational wave Observatory (LIGO.) To identify and interpret any observed signals, and to extract their astrophysical content, requires theoretical models of the sources. The extreme environments of neutron stars and black holes require them to be modeled within the framework of Einstein's theory of general relativity. The research activities supported by this award are aimed at developing the necessary numerical algorithms, at numerically constructing such theoretical models, at predicting gravitational wave signals for comparison with future observation, and at answering related astrophysical questions.Undergraduate students will actively participate in a computational physics research group, providing them with a ?hands-on? research experience and generating a research-enriched learning environment. The students will work on a variety of well-defined, manageable and meaningful projects, including, for example, the generalization and extension of previous results and the exploration of simple model problems. They will also have the opportunity to collaborate with scientists at other institutions and to present their work at conferences and in publications, making this research experience a very valuable preparation for graduate training and other future careers in the sciences and beyond.