We study the correlation between different sets of parton distributions (PDFs). Specifically, viewing different PDF sets as distinct determinations, generally correlated, of the same underlying physical quantity, we examine the extent to which the correlation between them is due to the underlying data. We do this both for pairs of PDF sets determined using a given fixed methodology, and between sets determined using different methodologies. We show that correlations have a sizable component that is not due to the underlying data, because the data do not determine the PDFs uniquely. We show that the data-driven correlations can be used to assess the efficiency of methodologies used for PDF determination. We also show that the use of data-driven correlations for the combination of different PDFs into a joint set can lead to inconsistent results, and thus that the statistical combination used in constructing the widely used PDF4LHC15 PDF set remains the most reliable method.

Correlation and combination of sets of parton distributions / R.D. Ball, S. Forte, R. Stegeman. - In: THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS. - ISSN 1434-6044. - 81:11(2021), pp. 1-18. [10.1140/epjc/s10052-021-09863-6]

Correlation and combination of sets of parton distributions

S. Forte
Secondo
;
R. Stegeman
Ultimo
2021

Abstract

We study the correlation between different sets of parton distributions (PDFs). Specifically, viewing different PDF sets as distinct determinations, generally correlated, of the same underlying physical quantity, we examine the extent to which the correlation between them is due to the underlying data. We do this both for pairs of PDF sets determined using a given fixed methodology, and between sets determined using different methodologies. We show that correlations have a sizable component that is not due to the underlying data, because the data do not determine the PDFs uniquely. We show that the data-driven correlations can be used to assess the efficiency of methodologies used for PDF determination. We also show that the use of data-driven correlations for the combination of different PDFs into a joint set can lead to inconsistent results, and thus that the statistical combination used in constructing the widely used PDF4LHC15 PDF set remains the most reliable method.
Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici
Settore FIS/04 - Fisica Nucleare e Subnucleare
H2020_ERC17SFORT_01 - Proton strucure for discovery at the Large Hadron Collider (NNNPDF) - FORTE, STEFANO - H2020_ERC - Horizon 2020_Europern Research Council - 2017
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/887520
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