Future tests of parton distributions

TL;DR

This paper introduces a 'future test' to evaluate the predictive power of parton distribution function methodologies by comparing results from limited past datasets to those from more extensive current datasets, assessing their ability to predict future data.

Contribution

It presents a novel validation approach for PDF determination methods, specifically testing the NNPDF4.0 and NNPDFpol1.1 models' predictive capabilities using historical data.

Findings

NNPDF4.0 could predict the rise of F2 at small x using pre-HERA data.

NNPDFpol1.1 could anticipate the proton spin crisis with pre-EMC data.

The future test effectively assesses the generalization power of PDF methodologies.

Abstract

We discuss a test of the generalization power of the methodology used in the determination of parton distribution functions (PDFs). The "future test" checks whether the uncertainty on PDFs, in regions in which they are not constrained by current data, are compatible with future data. The test is performed by using the current optimized methodology for PDF determination, but with a limited dataset, as available in the past, and by checking whether results are compatible within uncertainty with the result found using a current more extensive dataset. We use the future test to assess the generalization power of the NNPDF4.0 unpolarized PDF and the NNPDFpol1.1 polarized PDF methodology. Specifically, we investigate whether the former would predict the rise of the unpolarized proton structure function $F_2$ at small $x$ using only pre HERA data, and whether the latter would predict the so-called "proton spin crisis" using only pre-EMC data.