Single Detector Gravitational Wave Detection Using Multivariate Analysis
نویسندگان
چکیده
We investigate the possibility of including multivariate analysis (MVA) in the standard X-Pipeline gravitational wave (GW) burst search analysis for a single detector. MVA has been very effective in data analysis involving high energy particle physics, and is very promising in showing similar results in the GW data analysis community as well. We use the software package Toolkit for Multivariate Analysis (TMVA) with a focus on the use of the Boosted Decision Tree (BDT) classifier for the discrimination between GW signals and background detector noise. We find that we are able to achieve an increase in sensitivity to both circular sine Gaussian and inspiral waveforms when an MVA step is integrated into the standard X-Pipeline GW burst search process while analyzing data from a single detector.
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