volume 12, issue S333, P43-46 2017
DOI: 10.1017/s174392131700984x
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Claude J. Schmit, Jonathan R. Pritchard

Abstract: AbstractNext generation radio experiments such as LOFAR, HERA and SKA are expected to probe the Epoch of Reionization and claim a first direct detection of the cosmic 21cm signal within the next decade. One of the major challenges for these experiments will be dealing with enormous incoming data volumes. Machine learning is key to increasing our data analysis efficiency. We consider the use of an artificial neural network to emulate 21cmFAST simulations and use it in a Bayesian parameter inference study. We th…

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