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The LISA Data Challenges Working Group within the LISA Consortium has startedpublishing datasets to benchmark, compare, and build LISA data analysisinfrastructure as the Consortium prepares for the launch of the mission. Wepresent our solution to the dataset from LISA Data Challenge (LDC) 1Acontaining a single massive black hole binary signal. This solution is builtfrom a fully-automated and GPU-accelerated pipeline consisting of threesegments: a brute-force initial search; a refining search that uses theefficient Likelihood computation technique of Heterodyning (also calledRelative Binning) to locate the maximum Likelihood point; and a parameterestimation portion that also takes advantage of the speed of the Heterodyningmethod. This pipeline takes tens of minutes to evolve from randomized initialparameters throughout the prior volume to a converged final posteriordistribution. Final posteriors are shown for both datasets from LDC 1A: onenoiseless data stream and one containing additive noise. A posteriordistribution including higher harmonics is also shown for a self-injectedwaveform with the same source parameters as is used in the original LDC 1Adataset. This higher-mode posterior is shown in order to provide a morerealistic distribution on the parameters of the source.

A fully-automated end-to-end pipeline for massive black hole binary signal extraction from LISA data