Benjamin Aylott, University of Birmingham
John G. Baker, NASA Goddard Space Flight Center
William D. Boggs, University of Maryland, College Park
Michael Boyle, California Institute of Technology
Patrick R. Brady, University of Wisconsin-Milwaukee
Duncan A. Brown, Syracuse University
Bernd Brügmann, Friedrich-Schiller-Universität Jena
Luisa T. Buchman, California Institute of Technology
Alessandra Buonanno, University of Maryland, College Park
Laura Cadonati, University of Massachusetts Amherst
Jordan Camp, NASA Goddard Space Flight Center
Manuela Campanelli, Rochester Institute of Technology
Joan Centrella, NASA Goddard Space Flight Center
Shourov Chatterji, Istituto Nazionale di Fisica Nucleare, Sezione di Firenze
Nelson Christensen, Carleton College, USA
Tony Chu, California Institute of Technology
Peter Diener, Louisiana State University
Nils Dorband, Max Planck Institute for Gravitational Physics (Albert Einstein Institute)
Zachariah B. Etienne, University of Illinois Urbana-Champaign
Joshua Faber, Rochester Institute of Technology
Stephen Fairhurst, Cardiff University
Benjamin Farr, Rochester Institute of Technology
Sebastian Fischetti, University of Massachusetts Amherst
Gianluca Guidi, Istituto Nazionale di Fisica Nucleare, Sezione di Firenze
Lisa M. Goggin, University of Wisconsin-Milwaukee
Mark Hannam, University College Cork
Frank Herrmann, Pennsylvania State University
Ian Hinder, Pennsylvania State University
Sascha Husa, Max Planck Institute for Gravitational Physics (Albert Einstein Institute)
Vicky Kalogera, Northwestern University
Drew Keppel, California Institute of Technology
Lawrence E. Kidder, Cornell Center for Astrophysics and Planetary Science
Bernard J. Kelly, NASA Goddard Space Flight Center

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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. © 2009 IOP Publishing Ltd.

Publication Source (Journal or Book title)

Classical and Quantum Gravity