The Underlying Event in Jet Physics at TeV Colliders Arthur M. Moraes University of Glasgow PPE – ATLAS IOP HEPP Conference - Dublin, 21 st – 23 rd March 2005.

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 2 Outline: II.Hadron collisions: how can we model them?  Describing soft hadronic interactions. IV. LHC predictions; V. Conclusions. III. The underlying event in jet analysis; I. LHC and ATLAS;

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 3 Outline: II.Hadron collisions: how can we model them?  Describing soft hadronic interactions IV. LHC predictions; V. Conclusions. III. The underlying event in jet analysis I. LHC and ATLAS;

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 4

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 5 p-p√s = 14TeV  p-p collisions at √s = 14TeV  low-luminosity: L ≈ 2 x cm -2 s -1 ( L ≈ 20 fb -1 /year)  high-luminosity: L ≈ cm -2 s -1 ( L ≈ 100 fb -1 /year) Proton-proton collisions at the LHC p p quarksgluons Essentially all physics at LHC are connected to the interactions of quarks and gluons (small & large transferred momentum).  Hard processes (high-pT)  Hard processes (high-pT) : well described by perturbative QCD  Soft interactions (low-pT) (strong coupling constant,  s (Q 2 ), saturation effects,… )  Soft interactions (low-pT) : require non-perturbative phenomenological models (strong coupling constant,  s (Q 2 ), saturation effects,… ) underlying event “soft” The underlying event is dominated by “soft” partonic interactions.

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 6 Models for soft hadronic interactions Uncorrelated soft scatter Uncorrelated soft scatter – HERWIG/UA5 model (S.U.E.) ( ) Questionable modelling for: 1.Energy dependence; 2.Minimum-bias and UE hard component; Multiple interactions: Multiple interactions: Soft partonic scatters matched to hard 2  2 scatters: PYTHIA PYTHIA ( several options ) ( pt0pt0 n ~ σ int ↓ pt 0 ↑ n (and vice-versa) PHOJET PHOJET ( based on DPM ) ( JIMMY JIMMY ( multiple parton interactions – b-space picture ) ( )

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 7 II.Hadron collisions: how can we model them?  Describing soft hadronic interactions IV. LHC predictions; V. Conclusions. III. The underlying event in jet analysis I. LHC and ATLAS;

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 8 Underlying event in charged jet evolution (CDF analysis – Run I data) It is not  It is not only minimum bias event!  Sometimes, the underlying event can also be defined as everything in the collision except the hard process.  The underlying event has hard (multiple “semi-hard” parton scatterings) and soft components (beam-beam remnants).  ljet CDF analysis: charged particles: p t >0.5 GeV and | η | 0.5 GeV and | η | <1 cone jet finder: UE is defined as the Transverse Region except  All particles from a single particle collision except the process of interest. Phys. Rev. D, (2002)

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 9 distributions (particles from different angular regions) distributions (particles from different angular regions) - event - event - leading jet - leading jet - away region - away region - UE - UE Phys. Rev. D, (2002)

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 10 and distributions (particles from the underlying event) and distributions (particles from the underlying event) Average p T sum (GeV) of charged particles in the underlying event associated to a leading jet with P t ljet (GeV). Average multiplicity of charged particles in the underlying event associated to a leading jet with P t ljet (GeV). dN chg /dη ~ 10 Central Region (min-bias data dN chg /dη ~ 4) ~ 3 GeV ~ 3 GeV ~ 1.3 GeV ~ 1.3 GeV Central Region (min-bias data ~ 0.5 GeV )

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 11 Tuning models to the underlying event Small, dense core-size generates more multiplicity in the UE. Similarly to the observed for min-bias distributions, varying the lower p T cut-off also changes the particle density (and p T density) in the UE. Particle density in the UE decreases as p T min rises!

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 12 p T ljet > 5 GeV p T ljet > 30 GeV ~ 3GeV CDF analysis – Run I data Phys. Rev. D, (2002) Measurements recently made available for tuning models

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 13 maximum parton virtuality allowed in showers Q 2 scale of the hard scattering is multiplied by a factor to define the maximum parton virtuality allowed in showers. = 4 = 4 harder p T spectrum =1 =1 p T ljet > 30 GeV

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 14 PYTHIA6.2 tunings PHOJET1.12 Examples of MC tunings for the UE Used for DC2 production…

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 15 HERWIG6.5 + JIMMY4.1 tunings Transverse P t (leading jet in GeV) Ratio (MC/Data) JIMMY4.1 – Tuning A Proton radius shrunk by 1.73 JIMMY4.1 – Tuning B Transverse Ratio (MC/Data) P t (leading jet in GeV) ( p T min reduced from its default value

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 16 LHC predictions: JIMMY4.1 Tunings A and B vs. PYTHIA6.214 – ATLAS Tuning Transverse P t (leading jet in GeV) Tevatron LHC x 4 x 5 x 3

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 17 Predictions for the UE: from Tevatron to LHC energies Measurement JIMMY4.1PYTHIA6.214 PHOJET1.12Data Tuning ATuning BATLAS TuningCDF Tuning pT ljet > 10 GeV pT ljet > 10 GeV pT ljet > 10 GeV “?” pT ljet > 10 GeV “?” Tevatron LHC x 3x 2 LHC x 5x 4 x 1.5 x “?”

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 18  Two cones in  space are defined:  =  ljet (same as the leading jet)  =  ljet ± 90° R=0.7 P T 90max P T 90min P T 90max and P T 90min “MAX/MIN analysis” CDF analysis – Run I data The underlying event in Hard Interactions at the Tevatron ppbar collider, CDF Collaboration, PRD 70, (2004). Measurements recently made available for tuning models

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 19 “MAX/MIN analysis” CDF analysis – Run I data 630 GeV and 1800 GeV  The underlying event is measured for jet events at two different colliding energies: 630 GeV and 1800 GeV. energy extrapolation  This will provide important information on how to model the energy extrapolation in UE models.  s = 630 GeV  s = 1.8 TeV  s = 14 TeV   ?

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 20Conclusions: PYTHIA, PHOJET and HERWIG+JIMMY Current underlying event data can be described with appropriate tunings ( PYTHIA, PHOJET and HERWIG+JIMMY ). There are sizeable uncertainties in LHC predictions generated by different models. We need to understand better how to tune the energy dependence of the event activity: multiple parton scattering rate? (e.g. PYTHIA6.3) New MC models (e.g. PYTHIA6.3) and measurements can provide us with more tools to understand minimum-bias and the UE, and also to estimate more precisely this physics at the LHC. At the LHC, the best chance to the UE is at the low (very low?) luminosity runs. We are currently studying strategies to perform these measurements at ATLAS.

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 21 Backup…

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 22 Dijet azimuthal decorrelation Jets are defined in the central region using seed- based cone algorithm (R=0.7) leading jet p T max > 75 GeV second leading jet p T max > 40 GeV both leading p T jets: |y jet | < 0.5  dijet  jet1  jet2  =  Dijet production in hadron-hadron collisions result in  dijet  jet1  jet2  =  in the absence of radiative effects.  dijet  =   dijet  =   exactly two jets, no further radiation  dijet  small deviations from   dijet  small deviations from   additional soft radiation outside the jets  dijet  as small as 2    dijet  as small as 2    one additional high-p T jet small  dijet  – no limit small  dijet  – no limit  multiple additional hard jets in the event hep-ex/ Sep. 2004

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 23 hep-ex/ Sep  dijet  =  2     dijet     dijet  ~ 2       dijet   2  

IOP Conference, 21 st – 23 rd March 2005 A. M. Moraes 24 Dijet azimuthal decorrelation: ISR PARP(67) defines the maximum parton virtuality allowed in ISR showers (PARP(67) x hard scale Q 2 ) PARP(67)=1 (default): distributions underestimate the data! Need to increase the decorrelation effect, i.e. increase radiative and multiple interaction effects. Increasing PARP(67) (from 1 to 4) the azimuthal decorrelation is increased. Best value is somewhere between PARP(67)= 1 and 4!