Sept. 23, 2022, 1:11 a.m. | Marlin B. Schäfer, Ondřej Zelenka, Alexander H. Nitz, He Wang, Shichao Wu, Zong-Kuan Guo, Zhoujian Cao, Zhixiang Ren, Paraskevi Nousi, Niko

cs.LG updates on arXiv.org arxiv.org

We present the results of the first Machine Learning Gravitational-Wave
Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups
had to identify gravitational-wave signals from binary black hole mergers of
increasing complexity and duration embedded in progressively more realistic
noise. The final of the 4 provided datasets contained real noise from the O3a
observing run and signals up to a duration of 20 seconds with the inclusion of
precession effects and higher order modes. We present the average sensitivity …

arxiv astro challenge data machine machine learning mock search

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