Rapidity gaps and the PHOJET Monte Carlo
F. W. Bopp, R. Engel, J. Ranft
TL;DR
The paper presents PHOJET as a Monte Carlo implementation of the two-component Dual Parton Model to describe rapidity-gap and diffractive events in high-energy $pp$ collisions. It combines Regge-based soft interactions with LO QCD hard processes, implements a two-channel eikonal unitarization, and uses soft color reconnection to generate rapidity gaps, testing predictions against Tevatron data at $\sqrt{s}=1.8$ TeV. Key findings show that unitarization dampens diffractive cross sections and that SCR can reproduce jet-gap-jet signatures, though normalization depends on pomeron PDFs and the possible presence of a direct pomeron coupling; comparisons to diffractive dijet data indicate areas where the model may require stronger hard pomeron components to match observed rates. Overall, PHOJET provides a comprehensive framework to study both soft and hard diffraction across multiple collision systems, guiding interpretation of current data and outlining measurements capable of constraining pomeron structure and gap-survival effects.
Abstract
A model for the production of large rapidity gaps being implemented in the Monte Carlo event generator PHOJET is discussed. In this model, high-mass diffraction dissociation exhibits properties similar to hadron production in non-diffractive hadronic collisions at high energies. Hard diffraction is described using leading-order QCD matrix elements together with a parton distribution function for the pomeron and pomeron-flux factorization. Since this factorization is imposed on Born graph level only, unitarity corrections lead to a non-factorizing flux function. Rapidity gaps between jets are obtained by soft color reconnection. It was previously shown that this model is able to describe data on diffractive hadron production from the CERN-SPS collider and from the HERA lepton-proton collider. In this work we focus on the model predictions for rapidity gap events in p-p collisions at \sqrt{s} = 1800 GeV and compare to TEVATRON data.
