Study of Monte Carlo approach to experimental uncertainty propagation with MSTW 2008 PDFs

By Graeme Watt, R. Thorne. 2012

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A bstractWe investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established “MSTW 2008” global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the strong coupling. We show that the Monte Carlo approach using replicas of the original data gives PDF uncertainties in good agreement with the usual Hessian approach using the standard Δχ2 = 1 criterion, then we explore potential parameterisation bias by increasing the number of free parameters, concluding that any parameterisation bias is likely to be small, with the exception of the valence-quark distributions at low momentum fractions x. We motivate the need for a larger tolerance, Δχ2> 1, by making fits to restricted data sets and idealised consistent or inconsistent pseudodata. Instead of using data replicas, we alternatively produce PDF sets randomly distributed according to the covariance matrix of fit parameters including appropriate tolerance values, then we demonstrate a simpler method to produce an arbitrary number of random predictions on-the-fly from the existing eigenvector PDF sets. Finally, as a simple example application, we use Bayesian reweighting to study the effect of recent LHC data on the lepton charge asymmetry from W boson decays.

Subfields: Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/58455cb67a7bad826c49790885e5aa8cb56b05a9

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In Nuclear and High Energy Physics

Citations in the corpus

Les Houches 2015: Physics at TeV Colliders Standard Model Working Group Report (2016, methodology): “0 [184] PDF ensembles, by utilizing the Monte Carlo (MC) replica technique [185].”
Progress in the Determination of the Partonic Structure of the Proton (2013, methodology): “In practice it turns out that Nrep ∼ 50 − 100 replicas are necessary and sufficient to either reproduce the input data set of a typical present-day global fit [30, 96, 97], or its output Hessian PDFs [98].”
Handbook of LHC Higgs Cross Sections: 3. Higgs Properties (2013, methodology): “A similar conclusion, though based on studies without the recent LHC data appeared in [206].”
The Structure of the Proton in the LHC Precision Era (2017, methodology): “It is important to point out here that for native Hessian PDF sets, as well as for Monte Carlo sets converted from Hessian sets using the procedure of [37], the weighting Eq.”
Parton distributions for the LHC run II (2014, methodology): “We do so by using a methodology which has been repeatedly suggested [2], and recently used to study specific sources of PDF uncertainty [14] though never (to the best of our knowledge) for full characterization: the so called “closure test”.”
LHAPDF6: parton density access in the LHC precision era (2014, methodology): “[23] to preserve correlations by not taking the absolute value of the quantity in square brackets.”
Parton distribution benchmarking with LHC data (2012, methodology): “[18] it is shown that once the LHC W asymmetry data is included in MSTW08 using PDF reweighting [66, 67], the fit quality improves substantially.”
Constraints on the gluon PDF from top quark pair production at hadron colliders (2013, background): “9 The same study could be carried out with Hessian PDF sets as discussed in [74].”
PDF4LHC recommendations for LHC Run II (2015, methodology): “1 The Monte Carlo combination of PDF sets The first step in the construction of a Monte Carlo statistical combination [2,3,101,111,113,114] is the transformation of the Hessian PDF sets into Monte Carlo PDF sets using the WattThorne method [101].”