Speaker
Description
In deep-inelastic scattering, the energetic quarks liberated from hadrons travel and interact with the nuclear medium via several processes. One of these processes is the quark energy loss induced by gluon bremsstrahlung and intra-nuclear interactions of creating future hadrons. Moreover, one manifestation of these interactions is the enhanced emission of low-energy charged particles, referred to as "grey tracks", protons with momentum between 200 and 600 MeV. Using the components of BeAGLE, the leptoproduction Monte Carlo event generator, we interpret grey track signatures of parton transport and hadron formation by initially comparing its predictions to E665 data in order to establish an important basis for future tagging studies.
With the upgrade of the PyQM module, the parton energy loss section of BeAGLE which describes the parton energy loss to the existing complement of hadronic and prehadronic interactions inside nuclei. We compare multiplicity ratios for E665 grey tracks, to the predictions of BeAGLE, varying the PyQM options and parameters to determine which physics phenomena can be identified by these data. The E665 data we used consist of multiplicity ratios for fixed-target scattering of 490 GeV muons on gaseous xenon normalized to liquid deuterium as a function of the number of grey tracks produced. We divided the data into charge and rapidity regions for charged hadrons with an average momentum of 5 GeV. The BeaGLE predictions for forward rapidities (y >2 ) agree with the data of up to 4 grey tracks per event. Beyond that range, BeAGLE overpredicts the charged particle multiplicity ratios. For backward rapidities (y<-1), BeAGLE underpredicts multiplicity ratios for positively charged particles, which are primarily protons, while providing an excellent description of negatively charged particles. Meanwhile, we observe a strong correlation between grey tracks and the in-medium path length, offering the advantage that selecting certain particles in the forward region is unlikely to bias a centrality selection. These outcomes lay a significant basis for tagging studies in CLAS and the EIC, considering grey track studies with protons or neutrons will be possible using very small momenta.
