%0 Generic %1 Hou2016Reconstruction %A Hou, Tie-Jiun %A Gao, Jun %A Huston, Joey %A Nadolsky, Pavel %A Schmidt, Carl %A Stump, Daniel %A Wang, Bo-Ting %A Xie, Ke-Ping %A Dulat, Sayipjamal %A Pumplin, Jon %A Yuan, C. P. %D 2016 %K statistics, tools %T Reconstruction of Monte Carlo replicas from Hessian parton distributions %U http://arxiv.org/abs/1607.06066 %X 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 numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

@misc{Hou2016Reconstruction, 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 numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.}}, added-at = {2019-02-23T22:09:48.000+0100}, archiveprefix = {arXiv}, author = {Hou, Tie-Jiun and Gao, Jun and Huston, Joey and Nadolsky, Pavel and Schmidt, Carl and Stump, Daniel and Wang, Bo-Ting and Xie, Ke-Ping and Dulat, Sayipjamal and Pumplin, Jon and Yuan, C. P.}, biburl = {https://www.bibsonomy.org/bibtex/2b131b6af4a0ee9b93704994bfa3d3aba/cmcneile}, citeulike-article-id = {14098618}, citeulike-linkout-0 = {http://arxiv.org/abs/1607.06066}, citeulike-linkout-1 = {http://arxiv.org/pdf/1607.06066}, day = 20, eprint = {1607.06066}, interhash = {5053add6eff68a0532c7b864c950e457}, intrahash = {b131b6af4a0ee9b93704994bfa3d3aba}, keywords = {statistics, tools}, month = jul, posted-at = {2016-07-21 12:32:34}, priority = {2}, timestamp = {2019-02-23T22:15:27.000+0100}, title = {{Reconstruction of Monte Carlo replicas from Hessian parton distributions}}, url = {http://arxiv.org/abs/1607.06066}, year = 2016 }