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Welcome to the wiki for the first Machine Learning Gravitational-Wave Search mock data Challenge (MLGWSC-1). Here you will find more detailed information on the requirements for participation, the data sets, as well as the timeline. We also provide a set of basic tutorials for those not already familiar with the details of gravitational-wave data analysis.
The MLGWSC-1 is a mock data challenge hosted by the Albert-Einstein-Institute Hannover and the Friedrich-Schiller Universität Jena that tasks participants with finding gravitational-wave signals embedded in noise. It aims to compare state-of-the-art machine learning based algorithms with currently in-use search pipelines. For this purpose, four distinct data sets of increasing realism are used to evaluate the sensitivity as well as the computational efficiency of the submissions. For more details on the data sets please refer to the dedicated wiki page here.
All results will be collectively published and anyone submitting a search algorithm gains co-authorship. Submissions may be retracted at any point prior to the final publication as this is explicitly not a competitive challenge. To submit an algorithm please notify us of your intend by writing to [email protected] by December 31st, 2021 (we have excess capacity, get in touch if you still want to participate). The deadline for algorithm submission is March 31st, 2022. For details on the publication, please refer to this page and for details on the submission, please refer to this page.