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arXiv 2009-05-26 DOI 10.1088/0264-9381/26/11/114008 0 views

Status of NINJA: the Numerical INJection Analysis project

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

Original · EN

The 2008 NRDA conference introduced the Numerical INJection Analysis project (NINJA), a new collaborative effort between the numerical relativity community and the data analysis community. NINJA focuses on modeling and searching for gravitational wave signatures from the coalescence of binary system of compact objects. We review the scope of this collaboration and the components of the first NINJA project, where numerical relativity groups shared waveforms and data analysis teams applied various techniques to detect them when embedded in colored Gaussian noise.

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