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29 March 2024
 
  » arxiv » 0905.4227

 Article overview


Status of NINJA: the Numerical INJection Analysis 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 Cadonati ; Jordan Camp ; Manuela Campanelli ; Joan Centrella ; Shourov Chatterjis ; 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 ;
Date 26 May 2009
AbstractThe 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.
Source arXiv, 0905.4227
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