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arXiv · 1704.00471

Modeling NNLO jet corrections with neural networks

Stefano Carrazza
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Abstract

We present a preliminary strategy for modeling multidimensional distributions through neural networks. We study the efficiency of the proposed strategy by considering as input data the two-dimensional next-to-next leading order (NNLO) jet k-factors distribution for the ATLAS 7 TeV 2011 data. We then validate the neural network model in terms of interpolation and prediction quality by comparing its results to alternative models.

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Stefano Carrazza. 2017-04-03. Modeling NNLO jet corrections with neural networks. https://doi.org/10.5506/aphyspolb.48.947

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