Poster Title

P-21 Parameterization of BayesWave for Analysis of Gravitational Waves Caused by Inspiraling Black Holes

Presenter Information

Isabel Stafford, Andrews University

Abstract

Gravitational waves are ripples in the fabric of spacetime caused by large gravitational events. LIGO was built to detect gravitational wave signals. Programs such as BayesWave are designed to analyze signals detected by LIGO. By analyzing these signals, it is possible to gain a greater understanding of gravitational waves and their sources, which include binary stars, supernovas, and black holes. However, BayesWave remains unoptimized in many areas. By examining BayesWave’s analysis of an injected gravitational wave signal while systematically varying several pre-set parameters, this research aims to optimize BayesWave for the analysis of gravitational waves caused by inspiraling black holes.

Acknowledgments

Dr. Tiffany Summerscales

Location

Buller Hall

Start Date

2-26-2016 2:30 PM

End Date

2-26-2016 4:00 PM

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COinS
 
Feb 26th, 2:30 PM Feb 26th, 4:00 PM

P-21 Parameterization of BayesWave for Analysis of Gravitational Waves Caused by Inspiraling Black Holes

Buller Hall

Gravitational waves are ripples in the fabric of spacetime caused by large gravitational events. LIGO was built to detect gravitational wave signals. Programs such as BayesWave are designed to analyze signals detected by LIGO. By analyzing these signals, it is possible to gain a greater understanding of gravitational waves and their sources, which include binary stars, supernovas, and black holes. However, BayesWave remains unoptimized in many areas. By examining BayesWave’s analysis of an injected gravitational wave signal while systematically varying several pre-set parameters, this research aims to optimize BayesWave for the analysis of gravitational waves caused by inspiraling black holes.