Hard Core Protons soft-physics at hadron colliders

1. Hard Core Protonssoft-physics at hadron colliders Craig Buttar University of Sheffield With Arthur Moraes and Ian Dawson

2. Outline • Brief introduction to LHC and ATLAS • Soft-physics processes • Why study soft processes • Available models for soft physics processes • Comparison of models to data • Final tuning of the model • Extrapolation to the LHC • Outlook

3. LHC and ATLAS 7 TeV protons on 7 TeV protons 25ns bunch crossing rate Low luminosity=1033cm-2s-1 High luminosity=1034 cm-2s-1

4. 55mb At the LHC 101mb 23mb 78mb inelastic Cross-sections

5. Minimum bias Soft physics Underlying event Soft physics processes An event where there is no observable high-pt signature eg jet Physically a combination of several physical processes: mainly non-diffractive inelastic double diffractive Experimentally depends on the experiment-trigger: Collider expts usually measure non-single diffractive(NSD) Associated with high PT events: Beam remnants ISR More difficult to define experimentally and theoretically How are minimum bias and underlying events related ?

6. Forward production Low multiplicity Large E-flow Central production High multiplicity Small E-flow A minimum bias event

7. Charged particle flow and Charged energy flow at the LHC ~77% of charged particles in ||<5 ~6% of charged energy flow in ||<5 ATLAS covers ||<5 ->ATLAS is a central detector ! (miss all that lovely diffraction Physics eg diffractive Higgs) dN/deta~6=>30ch tracks in ID and 60 tracks in ATLAS per event At high luminosity ~ 15/events crossing ! Non-diffractive inelastic Pythia6.2 ATLAS

8. How well is the min-bias understood ? • Compare predictions of PYTHIA and PHOJETQCD+multi-parton vs DPM+multi-chain fragmentation • Results agree at the level of 20%

9. Radiation Background A crucial aspect of this is the calculation of the particle levels in ATLAS • Radiation levels • Background contributions to trigger rates • Occupancy

11. Effect of soft-physics on events Hbb high luminosity ~ 15 minimum bias events/crossing Hbb low luminosity ~ 1.5 minimum bias events/crossing

12. The underlying event High PT scatter Beam remnants ISR

13.  Studying the underlying event How to measure the properties of the underlying event CDF analysis Multi-jet cross-sections: HERA and D0 Important for central jet-veto 

14. Modelling soft physics How to describe low-pt behaviour ? • Different approaches but all lead to multi-parton scattering

15. Evidence for multi-parton interactions-UA5 • Look at minimum bias • Events • Violation of KNO scaling • Multiparton interactions ?

16. CDF analysis of underlying event The underlying event cannot be explained by single parton Parton scattering

17. ZEUS Multijet analysis

18. CDF evidence for multi-parton interactions Related to distribution of partons in transverse space

19. spp@40TeV Modelling multi-parton interactions QCD 22 cross-section increases Rapidly with Pt-min Exceeds the total pp xsect ?????? Solution ? Introduce Multi-parton scattering

20. PYTHIA model Multiple interactions solve total xsect problem Need to tame the PT divergence Parameters of the model: Control divergence Abrupt vs smooth cut-off • pT-min • Impact parameter • energy dependence Defines number of interactions Small i.p.high probability of interaction Matter distribution

21. σ PT Pt-min Pt-min Abrupt cut-off typcially gives Smaller cross-sections than Abrupt cut-off Leads to few multi-parton interactions

22. Impact parameter d Greater overlap gives greater Probability of interaction Double Gaussian-hard core

23. PYTHIA tuning Abrupt vs smooth cut-off scenario-abrupt cut-of does not produce enough parton-parton interactions, has a low multiplicity cut-off

24. Pt-min is ~1.9GeV default value

25.   The underlying event requires less activity => higher pt Lose ‘unification’ of min-bias and underlying event Double gaussian with default Core size = 0.2 Increasing Pt-min

26. Alternatively we can tune the matter distribution Small core Default Pt-min=1.9 Core x2 default Hard core Increasing core size

27. The min-bias are insensitive to the matter distribution

29. Pt-min vs matter distribution • Can we decide which is the correct tuning for the underlying event ? • Use other data, in this case HERA datarequire agreement with precision high ET-jet data

30. Extrapolation to LHC energies

31. PYTHIA tuning

32. Summary and outlook • Study of soft interactions is important for experiment design and analysis • Multi-parton interactions are a good model for soft interactions • Comparing PYTHIA model to min-bias data from ISR, SppS, Tevatron; and underlying event data from HERA and Tevatron, we can define parameters • There is ambiguity in what is the best way to fit the datapt-min vs matter distribution vs ISR • Need to look at other data to try resolve ambiguities • Need to determine energy dependence to allow extrapolation to the LHC • Put data into JETWEB to make quantitative comparisons

33. Why Why: the hadronic event environment • Prediction of radiation levels • Pile-up and pattern recognition issues-detector occupancy, pedestal effect • Low-pt physics and connection to underlying event in ‘interesting high-pt events • Higgs studies eg H • Central jet veto

34. Tuning pythia • Pythia is the standard MC in ATLASbut some work with phojet-compare different physics pQCD vs dual-parton model • Pythia models minimum bias using multiple-interaction formalism • Main parameters are:pt-min cut-off scale for pQCD-physically motivated by screeningmodel of the parton density-double gaussianstring drawing and nearest neighbour(and pdfs) • Use ISR+UA5+Tevatron data

35. Low x_gamma 2nd jet forward R365 18.3/6 R388 18.7/7 R284 63.3/6 r198 22.1/6

36. Low x_gamma 2nd jet central R365 15.3/7 R388 19.3/7 R284 48.7/7 R198 12.2/7

37. R365 12.8/8 R388 16.4/8 R284 21.9.8 R198 21.9/8

38. Min-bias also relatively insensitive to pt-min