Speaker
Description
Unmodeled methods are extensively employed to detect generic gravitational wave transients (GWTs), including signals that lack precise theoretical modeling. Interestingly, these methods also demonstrate competitive efficiency when applied to well-modeled gravitational wave signals, such as those from compact binary coalescences (CBCs), rivaling the widely used matched-filter approach. In this presentation, I will discuss the GWTboost non-flagship use-case, which seeks to enhance the detection and post-processing of gravitational wave transients. This project focuses on advancing core detection algorithms, optimizing them for high-performance computing environments, improving waveform reconstruction techniques, and refining CBC parameter estimation during post-processing. These developments aim to strengthen the robustness and accuracy of current gravitational wave analysis pipelines.
