Soft QCD Measurements at 900 GeV and 7 TeV with ATLAS

James Proudfoot

doi:10.1016/j.nuclphysbps.2010.10.009

Abstract

We present results on charged particle production in proton-proton collisions at the Large Hadron Collider and center of mass energies s=900GeV and 7 TeV in the ATLAS Detector. Charged tracks are measured with high precision in the inner tracking system; track multiplicities, transverse momentum spectrum and the average track transverse momentum as a function of track multiplicity are compared to phenomenological models describing the soft QCD processes participating in the interaction. Although all models approximately describe the data, none show complete agreement, with the deviation between data and Monte Carlo becoming more significant at the the higher center of mass energy and for higher track transverse momentum. These data have been used in the determination of a new optimised model which provides a much improved description of the data.

Highlights

– Trigger and event selection – Track reconstruction and determination of efficiency – Unfolding from track to hadron level – No model dependent corrections – Compare to Monte Carlo phenomenological models based on PYTHIA – using PYTHIA to provide relative weighting of SD, DD, and ND in the MC distributions
No single model is best: all disagree with data for high charged particle multiplicity &
None of the pre-LHC tunes provided “perfect” agreement with the experimental data, though they come close to describing several kinematic distributions as well as the increase in densities with √s. Used these measurement to obtain a new PYTHIA tune. This does a good job of describing the experimental data

Summary

Inclusive Distributions

Underlying event: transverse region should be most sensitive Should be ~independent of energy scale. – Trigger and event selection – Track reconstruction and determination of efficiency – Unfolding from track to hadron level (using Monte Carlo) – No model dependent corrections (e.g. for SD contribution) – Compare to Monte Carlo phenomenological models based on PYTHIA – using PYTHIA to provide relative weighting of SD, DD, and ND in the MC distributions

Trigger and event selection

Parameterize Reconstruction efficiency as a function of h and pT

Transverse Region Particle Densities

Summary