Abstract

We consider forward neutron production in DIS within fracture functions formalism. By performing a QCD analysis of available data we extract proton-to-neutron fracture functions exploiting a method which is in close relation with the factorisation theorem for this class of processes.

Highlights

  • In hadronic collisions a portion of the produced particle spectrum is characterised by hadrons carrying a sizeable fraction of the available energy and produced at small polar angle with respect to the collision axis

  • Forward particle production has been observed in processes which involve point-like probes in lepton– hadron interactions, such as Semi-Inclusive Deep Inelastic Scattering (SIDIS)

  • The presence of a hard scale is a basic requirement in the derivation of a dedicated factorisation theorem [4,5,6,7] which ensures that collinear QCD factorisation holds in the leading-twist approximation for forward particle production in DIS

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Summary

Introduction

In this paper we will focus on forward neutron production in DIS which provides, with respect to the aforementioned processes, complementary informations on soft QCD dynamics. The resulting set of proton-to-neutron fracture functions (nFFs) could be used in hard-scattering factorisation tests [24] in forward neutron tagged dijet photoproduction in ep collisions, as already measured at HERA [25,26], where factorisation is expected to hold only for the so-called direct component of the cross section. J. C (2014) 74:3029 be the possibility of using nFFs for predicting the cross section for the associated production of a forward neutron and a Drell–Yan pair or dijet system in hadronic collisions. C (2014) 74:3029 be the possibility of using nFFs for predicting the cross section for the associated production of a forward neutron and a Drell–Yan pair or dijet system in hadronic collisions For this processes the factorisation theorem is not expected to hold and nFFs determined by DIS data alone offer the opportunity to gauge factorisation breaking effects.

Data set and observable
Theory setup
Fitting procedure
Error estimation and propagation
Findings
Conclusions
Full Text
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