Stability of NLO Global Analysis and Implications for Hadron Collider Physics

Abstract

The phenomenology of Standard Model and New Physics at hadron colliders depends critically on results from global QCD analysis for parton distribution functions (PDFs). The accuracy of the standard next-to-leading-order (NLO) global analysis, nominally a few percent, is generally well matched to the expected experimental precision. However, serious questions have been raised recently about the stability of the NLO analysis with respect to certain inputs, including the choice of kinematic cuts on the data sets and the parametrization of the gluon distribution. In this paper, we investigate this stability issue systematically within the CTEQ framework. We find that both the PDFs and their physical predictions are stable, well within the few percent level. Further, we have applied the Lagrange Multiplier method to explore the stability of the predicted cross sections for W production at the Tevatron and the LHC, since W production is often proposed as a standard candle for these colliders. We find the NLO predictions on sigma_W to be stable well within their previously-estimated uncertainty ranges.

24 pages, 11 figures. Minor changes in response to JHEP referee report

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• The Three-Loop Splitting Functions in QCD: The Singlet Case
• Physical Gluons and High $E_T$ Jets

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• Dynamical parton distributions of the nucleon and very small-x physics
• Heavy Quark Mass Effects in Deep Inelastic Scattering and Global QCD Analysis
• Parton Distributions and the Strong Coupling Strength: CTEQ6AB PDFs
• Combination of electroweak and QCD corrections to single W production at the Fermilab Tevatron and the CERN LHC
• Production of a W boson and two jets with one b-quark tag
• Deviations from NLO QCD evolution in inclusive HERA data
• Parton distribution functions from the precise NNLO QCD fit
• Production of a Z boson and two jets with one heavy-quark tag
• Collider Inclusive Jet Data and the Gluon Distribution
• Parton Distributions
• Self-Organizing Maps Algorithm for Parton Distribution Functions Extraction