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Modeling NNLO jet corrections with neural networks · Around

2017

Modeling NNLO jet corrections with neural networks

Carrazza, Stefano

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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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J. Currie, A. Gehrmann-De Ridder, E. W. N. Glover and J. Pires, JHEP 1401
Original
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Then

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Later among the works it cites.
V. Bertone, S. Carrazza and N. P. Hartland, Comput. Phys. Commun. 212
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2016
Later among the works it cites.
J. Currie, E. W. N. Glover and J. Pires, Phys. Rev. Lett. 118
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