Particle production in pp collisions at the LHC with CMS N. van Remortel Universiteit Antwerpen, Belgium On behalf of the CMS Collaboration WISH 2010,

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Presentation transcript:

Particle production in pp collisions at the LHC with CMS N. van Remortel Universiteit Antwerpen, Belgium On behalf of the CMS Collaboration WISH 2010, 8-10/9/2010

2 Motivations  At high s, all hadron hadron (and  *p at fixed low Q) cross sections grow in a similar way  Many indications of universality   tot and  inel are not easy measurements, but inclusive single particle spectra and multiplicities are  Precision of present day measurements do not allow discrimination between power law (regge-Type) behavior, s , or fits by log(s) or log 2 (s) or e  (logs)  Minimum bias=typical p-p collision free of non-collision background  Dominated by low pt QCD processes (non –perturbative)  Also  nd ~2/3  tot, = 75 mb  At High lumi, pile up will consist of many min bias events (O(20)).  Soft component superimposed on hard scatters (UE event) is not identical to MB but has same phenomenology  As reference to heavy ion runs at 2.76*ATeV But also to learn about the physics ! Donnachie-Landshoff Uvarov-Schlapnikov-Likhoded

3 CMS minimum bias triggers inner tracker solenoid HF magnet yoke EM and HAD calorimeters muon detectors Trigger : any hit in the beam scintillator counters (BSC) AND filled bunch passing the beam pickups (BPTX) Offline event selection :  3 GeV in both sides of the HF rejection of the beam halo using BSC timing beam induced background rejection (pixel cluster shapes) at least a reconstructed vertex near the collision point ProcesFractionEfficiency SD19.2%26.7% NSD80.8%86.3% Sample composition at 7 TeV Pythia definitions

4 Charged particle reconstruction 9.6 M Si strips, 66 M pixels Hit reconstruction efficiency > 99% >97% of all channels operational coverage of |  |<2.4 with  10 strips  3 pixels p t reco down to 100 MeV/c with 3 pixels  # clusters/layer Largest acceptance: pt>30 MeV/c Insensitive to alignment most sensitive to bg: detector noise, loopers 2 out of 3 pixel layers data driven bg subtraction pt> 50 MeV/c Very robust Low bg p t > 100 MeV/c:  >70% and bg < 5% fakes at lowest p t CMS Silicon tracker pixel strips

5 Pseudorapidity density Average all methods & Symmetrize V. Khachatryan et al., JHEP 02 (2010) 041 V. Khachatryan et al., Phys. Rev. Lett. 105 (2010) Cluster counting: eliminate short clusters at large  Tracklets: Estimate bg from sidebands All measurements in agreement with other experiments, however densities are higher than most MC models (see later).

6 Transverse momenta Differential yield of charged hadrons in the range |η | < 2.4 in 0.2-unit-wide bins of |η | in NSD events. V. Khachatryan et al., JHEP 02 (2010) 041 V. Khachatryan et al., Phys. Rev. Lett. 105 (2010) Tsallis fit gives good description CMS PAS QCD Measured tracks up to 140 GeV/c Power law scaling: n  5-6 for p<1TeV

7 Energy dependence CMS only measured NSD so far Compatible with fits using lower energy data CMS data in RED

8 Model Comparisons Most PYTHIA tunes overestimate and underestimate dN/d  Some analytical models are spot on

9 Strangeness CMS PAS QCD Pythia underestimates the production yield of Strange particles at all energies And Also underestimates the large increase of the production cross section (1.7 K 0 - , 2.1  ) between 0.9 and 7 TeV

10 Multiplicities  Universal high s behavior of  tot, independent of the particle species is an important observation, calling for a deeper understanding  Related to number of dipoles in parton shower  Contains information on particle production mechanism, short range order and QM symmetrisation effects Accelerated parton radiates soft ‘wee’ partons Wee partons forget the identity of their parent hadron Hadron-hadron collisons are to first order an interaction of 2 ‘wee’ partons interaction probability of two wee partons (nowadays called color dipoles) is INDEPENDENT of s in LO QCD s dependence comes from the probability distribution of wee partons P(n) If P(n) is Poissonian.  Good & Walker formalism, based on unitarity! Explains also t-slope of inelastic events Feynman & Gribov

11 CMS Multiplicity CMS PAS QCD  Same trigger and event selection as single particle spectra  Corrected for Trigger and selection efficiency  Dedicated minimum bias tracking extending to p T =100 MeV/c up to |  |<2.4  Unfolded up to primary hadron level  Extrapolated to p T >0 (2% correction)  Cross-checked with tracklets and B=0T data

12 Model comparisons  More Pythia Tunes (P0, ProQ20, DW) exist but are omitted for clarity  No Monte Carlo is able to describe all multiplicities at all energies  In general all MC’s generate too many high pT particles (by tuning up the MPI)

13 KNO Scaling with  (z) becomes asymptotically independent of s for self-similar branching: KNO Scaling law KNO Scaling holds in smallest rapidity interval but is strongly violated in increasing phase space Quantifiable with higher order moments

14 KNO Scaling cont. Increase with s indicates KNO scaling violation KNO scaling holds for small rapidity intervals CMS Preliminary

15 Correlation between and n and energy evolution  Most sensitive quantity for MC tuners  If particle production is random walk, then ~n  Observed to be ~Independent of energy

16 Recent MC Tuning efforts New CMS Pythia 6.4 (pt-ordered showers) tune by R.Field based on UE observables Main parameters related to MPI model in Pyhthia Predictions of this new tune compared with MB multiplicity data Works much better than older (Tevatron tunes) Still fail to describe the highest multiplicity tails LHC wide working group on analysis of MB data and tuning of MC generators to MB and UE measurements

17 Conclusion and outlook  Minimum bias data is useful in context of understanding the bg in high pt physics  has interests in itself: non-pQCD laboratory  LHC wide working group formed to work on common tunes, common data sets:  Most recent tunes work very well  Lots of topics uncovered  Keep eyes open for surprises

18 Backup

19 CMS Detector inner tracker solenoid HF magnet yoke EM and HAD calorimeters muon detectors Magnetic field of 3.8 Tesla Acceptance of tracker is |  | < 2.5 Acceptance of BSC is 3.23 < |η| < 4.65 Used to trigger on real collisions Acceptance of Forward Calorimeter ( HF ) is 2.9 < |η| < 5.2 Used to reject mainly SD events BSC

20 Unfolding

21 Cross sections, Pomerons and MPI at high s With  =0.170  From Phys. Lett. B215, 417, 1988  Universal rise of the cross section,  tot  s , violates unitarity at high s   el  ½  tot (black disk geometrical limit)   SD /  tot is observed to be fairly constant  Multi-Pomeron exchanges  Multi Parton interactions R. Engel:

22 Multiple Parton interactions Realisation from experiment: ISR, Tevatron,... –Some p-p collisions exhibit 2 or more (semi-) hard parton-parton scatters Realisation from theory: below pt scale of ~2GeV the parton-parton cross section exceeds the total p-p cross section Amount of parton-parton interactions Is Poisson process with mean

23 Modeling MPI Theoretical fact: differential 2  2 cross section diverges as p t  0 Solution: Introduce cut-off p t0 to ensure finite and calculable results Screens color and evolves with center of mass energy as s  d Impact Parameter Pythia MPI Model with Varying impact parameter between the colliding hadrons: hadronic matter is described by double Gaussians Introduce IP correlations in Multiple Parton Interactions  Describe Tails! T. Sjöstrand and M. Van Zijl, Phys. Rev. D 36 (1987) 2019Basic idea Independent MPI: Poisson process, with minimal 1 interaction Make Poisson broader by impact parameter based average number of MPI All generators use this model, but differ in choice of p t0 and subsequent showers Currently only way to get N ch and p tch correct over wide energy range