Assessing the Impact of Fitting Methodology at aN$^3$LO with FPPDF: an Open Source Tool for Extracting Parton Distribution Functions in the Hessian Approach

TL;DR

This paper introduces FPPDF, an open-source tool for global PDF fitting using a fixed polynomial parameterisation and Hessian error propagation, enabling consistent comparisons between NNLO and aN$^3$LO orders.

Contribution

FPPDF complements existing tools by allowing community-wide PDF fits with fixed polynomial parameterisations, facilitating direct comparison with neural network approaches.

Findings

Higher perturbative order impacts PDFs similarly across methodologies.

Including higher order uncertainties has a consistent effect regardless of parameterisation.

The new code enables systematic comparisons of different fitting approaches.

Abstract

We present a new public code, FPPDF, to perform global fits of parton distribution functions (PDFs). The fitting methodology follows that implemented by the MSHT collaboration, namely applying a fixed polynomial parameterisation of the PDFs and Hessian approach to error propagation, while for data and theory settings the libraries used by the NNPDF collaboration are taken. This therefore complements the already publicly available NNPDF fitting code to enable fits with both neural network and fixed polynomial PDF parameterisations to be performed by the community, with otherwise identical theoretical and experimental inputs. As a first application, we use the new code to compare the PDFs found from fits at both NNLO and aN$^3$LO perturbative orders, but applying these two fitting approaches. We assess the impact of the two different methodologies on the PDFs and their uncertainties, providing results that complement previous comparisons between published PDF sets at NNLO and aN$^3$LO. We in particular find that the relative impact of going to the higher perturbative order and/or including missing higher order uncertainties is rather insensitive to which of these PDF parameterisation methodologies are used.