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A compression algorithm for the combination of PDF sets.

Carrazza S, Latorre JI, Rojo J, Watt G - Eur Phys J C Part Fields (2015)

Bottom Line: We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets.The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions.We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

View Article: PubMed Central - PubMed

Affiliation: Dipartimento di Fisica, Università di Milano and INFN, Sezione di Milano, Via Celoria 16, 20133 Milan, Italy.

ABSTRACT

The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different groups, each of which comprises a relatively large number of either Hessian eigenvectors or Monte Carlo (MC) replicas. While many fixed-order and parton shower programs allow the evaluation of PDF uncertainties for a single PDF set at no additional CPU cost, this feature is not universal, and, moreover, the a posteriori combination of the predictions using at least three different PDF sets is still required. In this work, we present a strategy for the statistical combination of individual PDF sets, based on the MC representation of Hessian sets, followed by a compression algorithm for the reduction of the number of MC replicas. We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets. The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions. We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

No MeSH data available.


Comparison of the predictions from the NNPDF3.0, MMHT14 and CT14 NNLO sets, with those of their Monte Carlo combination MC900, for a number of inclusive benchmark LHC cross sections. For illustration, we also indicate the envelope of the predictions of the three different PDF sets, which would determine the total PDF uncertainty in the current PDF4LHC recommendation. From top to bottom and from left to right: Higgs production in gluon fusion, , , and Z production, and top quark pair production. All processes have been computed at the LHC with a center-of-mass energy of 13 TeV
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Fig3: Comparison of the predictions from the NNPDF3.0, MMHT14 and CT14 NNLO sets, with those of their Monte Carlo combination MC900, for a number of inclusive benchmark LHC cross sections. For illustration, we also indicate the envelope of the predictions of the three different PDF sets, which would determine the total PDF uncertainty in the current PDF4LHC recommendation. From top to bottom and from left to right: Higgs production in gluon fusion, , , and Z production, and top quark pair production. All processes have been computed at the LHC with a center-of-mass energy of 13 TeV

Mentions: The results for these inclusive cross sections are shown in Fig. 3. We also show with dashed lines the envelope of the one-sigma range obtained from the three individual sets, which would correspond to the total PDF uncertainty for this process if obtained following the present PDF4LHC recommendation. We see that in general the two methods, the MC combination and the envelope, give similar results, the former leading to a smaller estimate of the total PDF uncertainty since the envelope assigns more weight to outliers than what would be required on a statistical basis.


A compression algorithm for the combination of PDF sets.

Carrazza S, Latorre JI, Rojo J, Watt G - Eur Phys J C Part Fields (2015)

Comparison of the predictions from the NNPDF3.0, MMHT14 and CT14 NNLO sets, with those of their Monte Carlo combination MC900, for a number of inclusive benchmark LHC cross sections. For illustration, we also indicate the envelope of the predictions of the three different PDF sets, which would determine the total PDF uncertainty in the current PDF4LHC recommendation. From top to bottom and from left to right: Higgs production in gluon fusion, , , and Z production, and top quark pair production. All processes have been computed at the LHC with a center-of-mass energy of 13 TeV
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4594162&req=5

Fig3: Comparison of the predictions from the NNPDF3.0, MMHT14 and CT14 NNLO sets, with those of their Monte Carlo combination MC900, for a number of inclusive benchmark LHC cross sections. For illustration, we also indicate the envelope of the predictions of the three different PDF sets, which would determine the total PDF uncertainty in the current PDF4LHC recommendation. From top to bottom and from left to right: Higgs production in gluon fusion, , , and Z production, and top quark pair production. All processes have been computed at the LHC with a center-of-mass energy of 13 TeV
Mentions: The results for these inclusive cross sections are shown in Fig. 3. We also show with dashed lines the envelope of the one-sigma range obtained from the three individual sets, which would correspond to the total PDF uncertainty for this process if obtained following the present PDF4LHC recommendation. We see that in general the two methods, the MC combination and the envelope, give similar results, the former leading to a smaller estimate of the total PDF uncertainty since the envelope assigns more weight to outliers than what would be required on a statistical basis.

Bottom Line: We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets.The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions.We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

View Article: PubMed Central - PubMed

Affiliation: Dipartimento di Fisica, Università di Milano and INFN, Sezione di Milano, Via Celoria 16, 20133 Milan, Italy.

ABSTRACT

The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different groups, each of which comprises a relatively large number of either Hessian eigenvectors or Monte Carlo (MC) replicas. While many fixed-order and parton shower programs allow the evaluation of PDF uncertainties for a single PDF set at no additional CPU cost, this feature is not universal, and, moreover, the a posteriori combination of the predictions using at least three different PDF sets is still required. In this work, we present a strategy for the statistical combination of individual PDF sets, based on the MC representation of Hessian sets, followed by a compression algorithm for the reduction of the number of MC replicas. We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets. The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions. We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

No MeSH data available.