# BayesWave analysis pipeline in the era of gravitational wave observations

@article{Cornish2021BayesWaveAP, title={BayesWave analysis pipeline in the era of gravitational wave observations}, author={Neil J. Cornish and Tyson B. Littenberg and Bence B'ecsy and Katerina Chatziioannou and James Alexander Clark and Sudarshan Ghonge and Margaret Millhouse}, journal={Physical Review D}, year={2021}, volume={103}, pages={044006} }

We describe updates and improvements to the BayesWave gravitational wave transient analysis pipeline, and provide examples of how the algorithm is used to analyze data from ground-based gravitational wave detectors. BayesWave models gravitational wave signals in a morphology-independent manner through a sum of frame functions, such as Morlet-Gabor wavelets or chirplets. BayesWave models the instrument noise using a combination of a parametrized Gaussian noise component and non-stationary and…

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