Abstract
We present NNPDF3.0, the first set of parton distribution functions (PDFs) determined with a methodology validated by a closure test. NNPDF3.0 uses a global dataset including HERA-II deep-inelastic inclusive cross-sections, the combined HERA charm data, jet production from ATLAS and CMS, vector boson rapidity and transverse momentum distributions from ATLAS, CMS and LHCb, W +c data from CMS and top quark pair production total cross sections from ATLAS and CMS. Results are based on LO, NLO and NNLO QCD theory and also include electroweak corrections. To validate our methodology, we show that PDFs determined from pseudo-data generated from a known underlying law correctly reproduce the statistical distributions expected on the basis of the assumed experimental uncertainties. This closure test ensures that our methodological uncertainties are negligible in comparison to the generic theoretical and experimental uncertainties of PDF determination. This enables us to determine with confidence PDFs at different perturbative orders and using a variety of experimental datasets ranging from HERA-only up to a global set including the latest LHC results, all using precisely the same validated methodology. We explore some of the phenomenological implications of our results for the upcoming 13 TeV Run of the LHC, in particular for Higgs production cross-sections.
Highlights
Parton distribution functions (PDFs) are currently one of the major sources of uncertainty in processes at hadron colliders, at the LHC
We present NNPDF3.0, the first set of parton distribution functions (PDFs) determined with a methodology validated by a closure test
Results obtained using NNPDF3.0 sets based on alternative datasets are always mutually consistent at the one sigma level, with the conservative partons leading to a lower result and the fit with no jets to a slightly higher one but with significantly larger uncertainty
Summary
Parton distribution functions (PDFs) are currently one of the major sources of uncertainty in processes at hadron colliders, at the LHC Ever since they have been quantified for the first time [1], it has been recognized that PDF uncertainties stem from three sources: the underlying data (which are affected by statistical and systematic errors), the theory which is used to describe them (which is typically based on the truncation of a perturbative expansion) and the procedure which is used to extract the PDFs from the data. A full closure test requires verifying that the procedure is robust: so, for example, that the conclusion that there are no procedural uncertainties is independent of the assumed underlying set of PDFs
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