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

2009; IOP Publishing; Volume: 26; Issue: 16 Linguagem: Inglês

10.1088/0264-9381/26/16/165008

1361-6382

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

Seismic Imaging and Inversion Techniques

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.