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arXiv 0901.4399gr-qc
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用数值相对论波形检验引力波搜索:来自第一个数值注入分析(NINJA)项目的结果

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

Benjamin Aylott, John G. Baker, William D. Boggs, Michael Boyle, Patrick R. Brady, Duncan A. Brown, Bernd Brügmann, Luisa T. Buchman, Alessandra Buonanno, Laura… 展开作者

Benjamin Aylott, John G. Baker, William D. Boggs, Michael Boyle, Patrick R. Brady, Duncan A. Brown, Bernd Brügmann, Luisa T. Buchman, Alessandra Buonanno, Laura Cadonati, Jordan Camp, Manuela Campanelli, Joan Centrella, Shourov Chatterji, Nelson Christensen, Tony Chu, Peter Diener, Nils Dorband, Zachariah B. Etienne, Joshua Faber, Stephen Fairhurst, Benjamin Farr, Sebastian Fischetti, Gianluca Guidi, Lisa M. Goggin, Mark Hannam, Frank Herrmann, Ian Hinder, Sascha Husa, Vicky Kalogera, Drew Keppel, Lawrence E. Kidder, Bernard J. Kelly, Badri Krishnan, Pablo Laguna, Carlos O. Lousto, Ilya Mandel, Pedro Marronetti, Richard Matzner, Sean T. McWilliams, Keith D. Matthews, R. Adam Mercer, Satyanarayan R. P. Mohapatra, Abdul H. Mroué, Hiroyuki Nakano, Evan Ochsner, Yi Pan, Larne Pekowsky, Harald P. Pfeiffer, Denis Pollney, Frans Pretorius, Vivien Raymond, Christian Reisswig, Luciano Rezzolla, Oliver Rinne, Craig Robinson, Christian Röver, Lucía Santamaría, Bangalore Sathyaprakash, Mark A. Scheel, Erik Schnetter, Jennifer Seiler, Stuart L. Shapiro, Deirdre Shoemaker, Ulrich Sperhake, Alexander Stroeer, Riccardo Sturani, Wolfgang Tichy, Yuk Tung Liu, Marc van der Sluys, James R. van Meter, Ruslan Vaulin, Alberto Vecchio, John Veitch, Andrea Viceré, John T. Whelan, Yosef Zlochower

摘要:

数值注入分析(NINJA)项目是数值相对论和引力波数据分析社区成员之间的合作努力。NINJA的目的是使用数值生成的波形研究现有引力波搜索算法的灵敏度,并促进数值相对论和数据分析社区之间的密切合作。我们描述的第一个NINJA分析的结果集中在引力波形从二进制黑洞合并。十个数值相对论小组提供了数值数据,这些数据被用来产生一组引力波信号。这些信号被注入模拟数据集,旨在模拟初始LIGO和Virgo引力波探测器的响应。九个小组使用搜索和参数估计管道分析了这些数据。匹配滤波算法,未建模的突发搜索和贝叶斯参数估计和模型选择算法应用于数据。我们报告的效率,这些搜索方法在检测数值波形和测量其参数。我们描述了不同的搜索方法之间的初步比较,并建议改进未来的NINJA分析。

英文摘要:

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.

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