Min-Bias and the Underlying Event at the LHC
Rick Field
TL;DR
This work analyzes minimum-bias (MB) and underlying-event (UE) phenomena at the LHC by comparing CMS, ATLAS, and ALICE data against PYTHIA tunes tuned to Tevatron results. It assesses how well PYTHIA Tune DW describes the UE and how Tune Z1/Z2 perform for MB and UE, highlighting the need for diffraction modeling to describe MB and the importance of PDFs and energy-dependent pT0 in tune extrapolations. The study finds that UE data at the LHC broadly align with expectations, with Tune Z1 delivering a particularly good description of UE, while MB remains imperfect without explicit diffraction modeling; no single tune perfectly describes both MB and UE. The results underscore the ongoing need for refined tuning and cross-validation with newer generators to achieve consistent descriptions across MB and UE at multiple energies.
Abstract
In a very short time the experiments at the LHC have collected a large amount of data that can be used to study minimum bias (MB) collisions and the underlying event (UE) in great detail. The CDF PYTHIA 6.2 Tune DW predictions for the LHC UE data at 900 GeV and 7 TeV are examined in detail. The behavior of the UE at the LHC is roughly what we expected. The LHC PYTHIA 6.4 Tune Z1 does an excellent job describing the LHC UE data. The modeling of MB (i.e. the overall inelastic cross section) is more complicated because one must include a model of diffraction. The ability of PYTHIA Tune DW and Tune Z1 to simultaneously describe both the UE in a hard scattering process and MB collisions are studied. No model describes perfectly all the features of MB collisions at the LHC.
