Soft QCD WG Summary Xavier Janssen, Anna Kulesza, Andrew Pilkington - - PowerPoint PPT Presentation
Soft QCD WG Summary Xavier Janssen, Anna Kulesza, Andrew Pilkington QCD@LHC 2011 St Andrews Scotland 8/26/2011 X. Janssen - 8/26/2011 1/12 QCD@LHC 2011 Soft QCD Summary Contributions Thanks to all speakers and apologize for not
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Xavier Janssen, Anna Kulesza, Andrew Pilkington
QCD@LHC 2011 St Andrews – Scotland – 8/26/2011
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Thanks to all speakers and apologize for not covering everything
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Thanks to all speakers and apologize for not covering everything
We will rather go through some topics that leaded to discussions and for which further work is needed
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The majority of the pp collisions are soft → no hard parton scattering → no “perturbative” predictions
→ need to model them phenomenologically
Can we come up with measurements addressing this ?
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Plenty of results from ATLAS/CMS (see plenary talks) and ALICE/LHCb: Publish “corrected” data in HEPData/Rivet * Only corrected results useful for comparison to theory/models * Rivet default in ATLAS/CMS for new standard model analysis approval What about LHCb/ALICE results ? * From preliminary to papers, it takes time (careful further cross-checks performed) Compare data to other MC e.g. different hadronization models, ... * Solved via Rivet (but slow) ! * Best would be if experiments do it directly * Only corrected results useful for comparison to theory/models * Rivet default in ATLAS/CMS for new standard model analysis approval What about LHCb/ALICE results ? * From preliminary to papers, it takes time (careful further cross-checks performed) Study particle flavour in UE * Ongoing in some experiments ….
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Other measurements to be performed to understand these effects: * Lambda / Lambda_bar ratios at central rapidity from CMS/ATLAS/ALICE * Correlations for identified particles: Kaons, Lambdas, …
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Craig Buttar
ICM Fit
Δϕ Correlations (cresp)
Correlations (vs) MC tuning: → Identify parameters to vary to discriminate between component: e.g. pT cut to remove soft contribution, include hard scale, … → Study of forward-backward correlations to probe MPI (dominant at large ∆η) Cluster model fit: → Do we have to use another functional form
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Craig Buttar
High Multiplicity events studies to do: * Redo ALICE analysis (BEC, J/Psi, …) in CMS and ATLAS if possible * s/u ratio (vs) multiplicity * particle flavour composition (in jets) vs multiplicity * properties of jets (constituent, brodening, …) vs multiplicity
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Diffraction – how to make the most useful measurements?
SD x-section extrapolated by MC !
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+ Status of MC tunes in CMS (Rick Field) + Energy dependent Herwig++ tunes (C. Röhr)
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Should we maintain so many tunes of PYTHIA 6&8, HERWIG(JIMMY/++), Sherpa ... ? Answer: No, we should stop using discarded ones for good reason !
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Why should we produce new tunes based on LHC data ? Answer 1: To be able to describe pile-up at LHC and do searches
Answer 2: Identify places where the MC are failing (and maybe try to develop/test/use other/better models)
PT Particle Ratio: Kaons/Pions
0.00 0.20 0.40 0.60 1 2 3 4
PT (GeV/c)
PT Particle Ratio
(K++K-)/(π++π-)
ALICE Data
PYTHIA Tune Z1 & Z1CINEL (|Y| < 0.75)
900 GeV
Z1 Z1C Tune Z1C qq/q: 0.1 -> 0.12 us/s: 0.4 -> 0.8
(Lam+LamBar) Rapidity Distribution: dN/dY
0.00 0.05 0.10 0.15 0.20 0.25
1 2 3 4
Rapidity Y
Charged Particle Rati CMS Data
PYTHIA Tune Z1C900 GeV 7 TeV
NSD (all pT) Tune Z1C qq/q: 0.1 -> 0.12 us/s: 0.4 -> 0.8
(Λ+Λ)
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