Showing papers by "Satyanarayan Ray Pitambar Mohapatra published in 2009"
University of Birmingham1, Goddard Space Flight Center2, University of Maryland, College Park3, California Institute of Technology4, University of Wisconsin–Milwaukee5, Syracuse University6, University of Jena7, University of Massachusetts Amherst8, Rochester Institute of Technology9, Carleton College10, Louisiana State University11, Albert Einstein Institution12, University of Illinois at Urbana–Champaign13, Cardiff University14, University of Urbino15, University College Cork16, Pennsylvania State University17, University of the Balearic Islands18, Northwestern University19, Cornell University20, Georgia Institute of Technology21, Florida Atlantic University22, University of Texas at Austin23, Princeton University24, University of Cambridge25
TL;DR: The Numerical InJection Analysis (NINJA) project as mentioned in this paper is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities to study the sensitivity of existing search algorithms using numerically generated waveforms.
Abstract: 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.
134 citations
TL;DR: The Numerical InJection Analysis (NINJA) project as discussed by the authors is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities to study the sensitivity of existing gravitational wave search algorithms using numerically generated waveforms.
Abstract: 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.
99 citations
University of Massachusetts Amherst1, University of Birmingham2, Goddard Space Flight Center3, University of Maryland, College Park4, California Institute of Technology5, University of Wisconsin–Milwaukee6, Syracuse University7, University of Jena8, Rochester Institute of Technology9, Carleton College10, Louisiana State University11, Albert Einstein Institution12, University of Illinois at Urbana–Champaign13, Cardiff University14, University of Urbino15, University College Cork16, Pennsylvania State University17, University of the Balearic Islands18, Northwestern University19, Cornell University20, Georgia Institute of Technology21, Florida Atlantic University22, University of Texas at Austin23, Princeton University24, University of Cambridge25
TL;DR: The Numerical InJection Analysis project (NINJA) as discussed by the authors is a collaborative effort between the numerical relativity community and the data analysis community to detect gravitational wave signatures from the coalescence of binary system of compact objects.
Abstract: 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.
54 citations
TL;DR: The Numerical InJection Analysis project (NINJA) as discussed by the authors is a collaborative effort between the numerical relativity community and the data analysis community that focuses on modeling and searching for gravitational wave signatures from the coalescence of binary system of compact objects.
Abstract: 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.
36 citations
TL;DR: In this paper, the authors analyzed the NINJA simulated data set with the Q-pipeline algorithm, designed for the all-sky detection of gravitational-wave bursts with minimal assumptions on the shape of the waveform.
Abstract: The gravitational-wave signature from binary black hole coalescences is an important target for ground-based interferometric detectors such as LIGO and Virgo. The Numerical INJection Analysis (NINJA) project brought together the numerical relativity and gravitational wave data analysis communities, with the goal to optimize the detectability of these events. In its first instantiation, the NINJA project produced a simulated data set with numerical waveforms from binary black hole coalescences of various morphologies (spin, mass ratio, initial conditions), superimposed to Gaussian colored noise at the design sensitivity for initial LIGO and Virgo. We analyzed the NINJA simulated data set with the Q-pipeline algorithm, designed for the all-sky detection of gravitational-wave bursts with minimal assumptions on the shape of the waveform. The algorithm filters the data with a bank of sine-Gaussians, sinusoids with Gaussian envelope, to identify significant excess power in the time-frequency domain. We compared the performance of this burst search algorithm with lalapps_ring, which match-filters data with a bank of ring-down templates to specifically target the final stage of a coalescence of black holes. A comparison of the output of the two algorithms on NINJA data in a single detector analysis yielded qualitatively consistent results; however, due to the low simulation statistics in the first NINJA project, it is premature to draw quantitative conclusions at this stage, and further studies with higher statistics and real detector noise will be needed.
5 citations
TL;DR: In this article, the NINJA project produced a simulated data set with numerical waveforms from binary black hole coalescences of various morphologies (spin, mass ratio, initial conditions), superimposed to Gaussian colored noise at the design sensitivity for initial LIGO and VIRGO.
Abstract: The gravitational wave signature from binary black hole coalescences is an important target for LIGO and VIRGO. The Numerical INJection Analysis (NINJA) project brought together the numerical relativity and gravitational wave data analysis communities, with the goal to optimize the detectability of these events. In its first instantiation, the NINJA project produced a simulated data set with numerical waveforms from binary black hole coalescences of various morphologies (spin, mass ratio, initial conditions), superimposed to Gaussian colored noise at the design sensitivity for initial LIGO and VIRGO. We analyzed this simulated data set with the Q-pipeline burst algorithm. This code, designed for the all-sky detection of gravitational wave bursts with minimal assumptions on the shape of the waveform, filters the data with a bank of sine-Gaussians, or sinusoids with Gaussian envelope. The algorithm's performance was compared to matched filtering with ring-down templates. The results are qualitatively consistent; however due to the low simulation statistics in the first NINJA project, it is premature to draw quantitative conclusions at this stage.
2 citations