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

该奖项支持鲍登学院在计算物理方面的研究和教育项目，这是一所位于缅因州布伦瑞克的高度挑剔的本科院校。所支持的研究领域是引力波源模拟(数值相对论)和计算天体物理学，为本科生提供参与的机会。研究目标涉及双轨中子星和黑洞的数值模拟，主要是因为利用包括激光干涉仪引力波天文台(LIGO)在内的新一代引力波激光干涉仪探测这类天体的引力辐射的前景。要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，需要源的理论模型。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开发必要的数值算法，数值构建此类理论模型，预测引力波信号以便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，为他们提供实践经验。研究经验和创造一个研究丰富的学习环境。学生将致力于各种定义明确、易于管理和有意义的项目，例如，包括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介绍他们的工作，使这一研究经验成为研究生培训和其他科学及其他领域未来职业生涯的非常宝贵的准备。

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.