Building a Better Template Bank​: A test of astrophysical models using the cross-correlation search ​method for intermediate-duration gravitational waves​

The Cross-Correlation Algorithm (COCOA) is an analysis technique that aims to better analyze "intermediate-duration" gravitational waves signals of order 10 to 10,000 seconds in duration. COCOA addresses the shortcoming of traditional methods by providing tunable sensitivity by leveraging partial modeling when fully precise models are unavailable or infeasible. Despite being shown to be highly effective in this regime [R. Coyne, et al. (2016); E. Sowell, et al. (2019)], COCOA has only been tested on a limited number of astrophysical models. This work extends previous efforts by testing COCOA on a broader range of astrophysical model's waveforms [A. Corsi, et al. (2009); M. Van Putten, et al. (2004)]. We test COCOA at both extremes of its sensitivity range.​