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Soft QCD with ATLAS detector

Soft QCD with ATLAS detector. Samir FERRAG On behalf of ATLAS collaboration University of Glasgow. ATLAS Soft QCD Public results. https:// twiki.cern.ch / twiki /bin/view/ AtlasPublic / StandardModelPublicResults#Soft_QCD. 6 papers >50 conference notes and proceedings. Introduction.

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Soft QCD with ATLAS detector

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  1. Soft QCD with ATLAS detector Samir FERRAG On behalf of ATLAS collaboration University of Glasgow

  2. ATLAS Soft QCD Public results https://twiki.cern.ch/twiki/bin/view/AtlasPublic/StandardModelPublicResults#Soft_QCD 6 papers >50 conference notes and proceedings

  3. Introduction • Soft QCD: low transverse momentum transfer: • Initial and final state radiations & development of showers in jets • colour recombination • Multiple Parton Interactions (MPI) • Underlying events… • Soft QCD processes are unavoidable background for lot of collider observable: jet cross sections, Missing energy, isolation… • Impact on resolutions: Missing Et, jets, eGamma,… • Not well understood since non-perturbative physics is involved • Phenomenological models and Monte Carlo tunes can be tested looking for agreement with data for various observables • Intensive ATLAS soft QCD program, analyses in this talk: Minimum bias, underlying events, 2 particle correlation and full inelastic cross-section.

  4. Min-Bias related Analyses

  5. Minimum Bias analysis cuts • Underlying Event, 2 particle correlations and many other soft QCD measurements, use the Minimum-Bias analysis cuts • Datasets: • at 900 GeV: 360 K events • At 7 TeV: 10 M events • Event selection: • MBTS single-cell trigger in coincidence with beam pickup (BPTX) • Track quality cuts (pixel, SCT and TRT hits) • 1 primary vertex reconstructed: 2 tracks, beam spot, no pileup • Cut on impact parameters at primary vertex (remove secondary tracks) • Phase space considered: • Inclusive phase space: • At least 2 good tracks, pT > 100 MeV, |h|<2.5 • Lower diffractive contribution • At least 6 good tracks, pT > 500 MeV, |h|<2.5

  6. Efficiencies and ATLAS performances Primary vertex finding efficiency Trigger efficiency Measured on data Tracking efficiency Tracking efficiency Estimated on Monte Carlo

  7. Minimum Bias • MC independent correction method of detector effects • Compared to MC: 900 GeV, 2.36 TeV and 7 TeV • Inclusive region • Lower diffractive region (also called AMBT1 region: AMBT1 is a Pythia tune to data) • Data above all MC in dN/dh • spectrum • 10 orders of magnitude • PHOJET is most successful to • reproduce dN/dpT spectrum

  8. Minimum Bias • Disagreement at level of factor 2 in some regions between data and MC in dN/dnCHdistribution: • Low nCH region is badely modeled by MC, large diffractive component • There is a good agreement in the AMBT1 region • AMBT1 tune is closer to the data in d<pT>/dnCHdistribution: • provides best modeling at high nCH, but agreement is poor • high sensitivity to diffraction at low nCH(poor agreement)

  9. MB: energy dependence • Energy dependence of dN/dh • At h=0: • AMBT1 tuned to data in AMBT1 region. • Satisfactory agreement of MC09 and Pythia 8 tunes in AMBT1 region • Diffraction component problematic

  10. Underlying Events (UE) • Definition: Except the hard scattered part in a pp event everything else is considered as underlying events • In the transverse region: perpendicular to hard process and sensitive to UE: • Used leading track to identify the leading jet • First measurement with charged particles only: • Phys. Rev. D83 (2011) 112001 • This measurement: charged + neutral particles: • arXiv:1103.1816v2 (submitted to EPJC)

  11. Including neutral particles in UE • correlation between topological clusters and charged track multiplicities • Based on calorimeter 3 dimensional energy deposit • Benefit from fine granularity • Electromagnetic calorimeter: • 4 longitudinal depth • Dh-Df: 0.003 X 0.1 – 0.05 X 0.025 • Hadronic calorimeter • 3 longitudinal depth • Dh-Df: 0.1 X 0.1 for |h|<2.5 • Dh-Df: 0.2 X 0.2 for 2.5<|h|<3.2 • Complementarity to charged-particle-only analysis ATLAS-STDM-2010-05

  12. UE: angular distributions • None of the MC describe properly the data • At Dfaround± π/2: • Herwig+Jimmy overestimate the data at PTlead > 1 GeV • Phojet always underestimate data • Disagreement more pronounced when Ptleadincreased • Data above MC prediction when Ptleadincreased

  13. UE: multiplicity and SpTdistributions • All MC underestimate data in multiplicity and Summed pT • Pythia DW tune has the best description of data especially at high Ptlead • Other tunes: far from ideal description of data in transverse region • Same behaviourobserved at 900 GeV ATLAS-STDM-2010-05

  14. Two Particle Correlations: correlation function Correlations in a pattern of radiation emitted in proton-proton collisions can give an insight Into underlying particle production mechanism The two-particle angular correlation function is given by: Two-particle pair density function. Normalised by the number of events. Distribution of uncorrelated pairs. Normalised by its integral. The two-particle correlation function shows the probability that given a single particle Emission there will be a second particle emitted at a distance DhDf

  15. Two Particle Correlations: detector effect correction • Classic corrections with track reweighting failed the closure test • Reconstructed distributions are used: • loop over the tracks “1”, “2”, ... “N” times, in each step, remove probabilistically some of them according to their tracking efficiency • estimate the correlation function every time • Extrapolate to step “-1” in each Dh bin ATLAS-CONF-2011-055

  16. Two Particle Correlations: results ATLAS-CONF-2011-055 Corrected two-particle correlation distribution functions in Delta eta and Delta phi for 7 TeV and 900 GeV data. By construction, these plots are symmetric around Delta eta = 0 and Delta phi is plotted from −pi/2 to 3pi/2 to avoid splitting the away-side region.

  17. Two Particle Correlations: data/MC comparison Away-side Near-side Short-Range • Strength of correlations seen on data is not reproduced by Monte Carlo’s: • Away-side: Pythia8 has the closest description of data over the full range • Near-side: none of the tunes have the right shape. Pythia8 closest to data in the tails • Short-range: none of the tunes agrees with data over the full range ATLAS-CONF-2011-055

  18. Proton-proton Inelastic cross section

  19. Full Inelastic cross section • Events selected by requiring hits in MBTS (scintillation counters) • 1.2 M events at 7TeV in a single run • Define: x=M2X/s M2X is calculated for the most spread set of hadrons • Detector acceptance ~ x>5X10-6

  20. Inelastic cross section: results • Inelastic cross section measured for x>5x10-6: • s=60.3 ± 2.1mb • MC preditions: • Pythia: 64.7 mb • Phojet: 73.5 mb • When extrapolated down to x=m2p/s using Pythia to compare with analytic models: • s=69.1 ± 2.4(exp) ± 6.9(extr) mb • Data agree with most analytic calculations

  21. conclusion • ATLAS has an intensive production of soft QCD measurements • Few tunes reproduces well few observables but no one reproduces all the data measurements. • AMBT1 tune created to reproduce the non-diffractive part of data. • Full inelastic cross-section measurement in good agreement with MC’s • More ATLAS results to come in the near future…

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