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arXiv · 1607.06066

Reconstruction of Monte Carlo replicas from Hessian parton distributions

Tie-Jiun Hou·Jun Gao·Joey Huston·Pavel Nadolsky·Carl Schmidt·Daniel Stump·Bo-Ting Wang·Ke-Ping Xie·Sayipjamal Dulat·Jon Pumplin·C. -P. Yuan
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Abstract

We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

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Tie-Jiun Hou, Jun Gao, Joey Huston, Pavel Nadolsky, Carl Schmidt, Daniel Stump, Bo-Ting Wang, Ke-Ping Xie, Sayipjamal Dulat, Jon Pumplin, C. -P. Yuan. 2016-07-20. Reconstruction of Monte Carlo replicas from Hessian parton distributions. https://doi.org/10.1007/jhep03(2017)099

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