Inpainting allows recovery of pre-merger massive black hole binary signals in LISA data despite gaps and overlaps.
A How-To for the Mock LISA Data Challenges
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abstract
The LISA International Science Team Working Group on Data Analysis (LIST-WG1B) is sponsoring several rounds of mock data challenges, with the purpose of fostering development of LISA data-analysis capabilities, and of demonstrating technical readiness for the maximum science exploitation of the LISA data. The first round of challenge data sets were released at this Symposium. We describe the models and conventions (for LISA and for gravitational-wave sources) used to prepare the data sets, the file format used to encode them, and the tools and resources available to support challenge participants.
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Inpainting over the cracks: challenges of applying pre-merger searches for massive black hole binaries to realistic LISA datasets
Inpainting allows recovery of pre-merger massive black hole binary signals in LISA data despite gaps and overlaps.