Binary Black Holes and Gravitational Radiation

*9800722德克萨斯大学相对论中心的理查德·马茨纳教授和马修·肖普图克教授将与博士后和该中心的其他成员合作，开发描述天体物理黑洞相互作用和碰撞以及在相互作用中产生引力辐射的计算机代码。这些技术将在对单个黑洞的更简单描述的基础上进行扩展，并将利用一组现有的计算机代码来模拟黑洞相互作用。由于计算和分析描述(特别是定位黑洞表面的方法)方面的技术进步，这是一项及时的努力，应该会产生重大的科学成果。其中一些工作将与匹兹堡大学和宾夕法尼亚州立大学合作完成。正在建设中的探测器对引力辐射的探测将打开一扇戏剧性的新宇宙之窗。从理论上预测来自可能的天体物理源的信号对于理解预期的信号以及设计探测算法本身将是极其重要的。黑洞相互作用非常重要，因为黑洞可能是引力辐射信号的最强来源。该项目将检验这一说法，并将为探测到引力波信号时的预测提供实质性的理论投入。此外，这是一个超大规模科学计算的例子，并将开发和扩展适用于广泛的计算科学问题的技术。

***9800722MatznerProfessors Richard Matzner and Matthew Choptuik of the University of Texas Center for Relativity will work with postdocs and other members of the Center, to develop computer codes that describe the interaction and collision of astrophysical black holes and the production of gravitational radiation in their interactions. The techniques will be extended from simpler descriptions of single black holes, and will make use of a set of existing computer codes that simulate black hole interactions. Because of technical advances in the computational and analytical description (particularly methods for locating the surfaces of the black holes), this is a timely effort, and should yield significant scientific results. Some of this work will be done in collaboration with The University of Pittsburgh, and with The Pennsylvania State University.The detection of gravitational radiation by detectors now under construction will open a dramatic new window on the universe. Having a theoretical prediction of the signals from possible astrophysical sources will be extremely important to understanding the expected signals, and to designing the detection algorithms themselves. Black hole interactions are very important, because black holes may be the strongest sources of gravitational radiation signals. This project will test this statement, and will provide a substantial theoretical input to the prediction of gravitational wave signals as they are detected. In addition this is an example of very large scale scientific computation, and will develop and extend techniques that are applicable in a wide range of computational-science problems.***