Hard Core Protonssoft-physics at hadron colliders

Craig Buttar University of Sheffield

With Arthur Moraes and Ian Dawson

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

LHC and ATLAS

7 TeV protons on 7 TeV protons25ns bunch crossing rateLow luminosity=1033cm-2s-1

High luminosity=1034 cm-2s-1

Cross-sections

ediffractivnonSDDDelasticpp

inelastic

At the LHC 101mb 23mb 78mb

55mb

Soft physics processesAn event where there is no observable high-pt signature eg jetPhysically a combination of several physical processes: mainly non-diffractive inelastic double diffractiveExperimentally depends on the experiment-trigger: Collider expts usually measure non-single diffractive(NSD)

Soft physics

Minimum bias

Underlying event

Associated with high PT events:Beam remnantsISRMore difficult to define experimentally and theoretically

How are minimum bias and underlying events related ?

Forward productionLow multiplicityLarge E-flow

Central productionHigh multiplicitySmall E-flow

A minimum bias event

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 diffractionPhysics 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

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%

Radiation Background

A crucial aspect of this is the calculation of the particle levels in ATLAS

• Radiation levels• Background contributions to

trigger rates• Occupancy

PHOJET/PYTHIA neutrons photons e+e- protons muons pionstotal >10MeV >30keV >0.5MeV >10MeV >10MeV >10MeV

Inner-detector regions 1.08->1.11 1.06->1.11 0.99->1.15 1.0->1.1 1.1 1.1 1.1Muon-barrel regions 1.09->1.12 1.09->1.21 1.09->1.18 0.9->1.2 1.0->1.2 1.0->1.2 low-statsMuon-forward regions 1.09->1.15 1.05->1.14 1.06->1.13 0.9->1.4 1.0->1.2 1.1->1.6 low-stats

Effect of soft-physics on events

Hbb high luminosity~ 15 minimum bias events/crossing

Hbb low luminosity~ 1.5 minimum bias events/crossing

The underlying event

High PT scatter

Beam remnants

ISR

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

Modelling soft physics

How to describe low-pt behaviour ?

• Different approaches but all lead to multi-parton scattering

Evidence for multi-parton interactions-UA5

Look at minimum biasEvents

Violation of KNO scaling-Multiparton interactions ?

CDF analysis of underlying event

The underlying event cannot be explained by single partonParton scattering

ZEUS Multijet analysis

CDF evidence for multi-parton interactions

mbeff7.13.27.15.14

Xjetspp 3/ 0

eff

BADP m

2

Related to distribution of partons in transverse space

Modelling multi-parton interactions

pp@40TeV

QCD 22 cross-section increasesRapidly with Pt-minExceeds the total pp xsect ??????

s

utpQxfQxfutstddxdx

dp

dTji

kij

kjiT ˆ

ˆˆ),(),()ˆ,ˆ,ˆ(ˆˆ 22

122

11

2,,

12

4/

min

2

2

s

p

t

t

hard

T

dpdp

d

pp

hardn

Solution ?Introduce Multi-partonscattering

PYTHIA model

• pT-min • Impact parameter

• energy dependence

Multiple interactions solve total xsect problemNeed to tame the PT divergenceParameters of the model:

Control divergenceAbrupt vs smooth cut-off

Defines number of interactionsSmall i.p.high probability of interactionMatter distribution

Pt-min

PT

σ

Pt-min

Abrupt cut-off typcially givesSmaller cross-sections than Abrupt cut-off Leads to few multi-parton interactions

2

2

2

32

21

2

31

expexp1

a

r

aa

r

ar

d

Impact parameter

Double Gaussian-hard core

Greater overlap gives greaterProbability of interaction

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

Pt-min is ~1.9GeV default value

The underlying event requires less activity => higher ptLose ‘unification’ of min-bias and underlying event

Increasing Pt-min

Double gaussian with defaultCore size = 0.2

Alternatively we can tune the matter distribution

Small coreCore x2 default

Hard core

Default Pt-min=1.9

Increasing core size

The min-bias are insensitive to the matter distribution

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

HERA Data2/df High ET 2/df Low ET

Default MI model (abrupt cut-off) 2.23 3.72Defaults with double gaussian core=0.2 (default) 2.83 3.44Defaults with double gaussian core=0.4 2.09 5.04Defaults with single gaussian Pt-min =1.6 (R.Field/CDF) 3.17 4.93

Extrapolation to LHC energies

4.4

)()(

)()(

CDFMBCDFUE

LHCMBLHCUE

PYTHIA tuning

PYTHIA’s model parameters

Minimum bias Underlying event “Universal”

MSTP(81) 1 1 1 (D) √

MSTP(82) 4 4 4 √

PARP(82) 1.9 2.2 / 1.9(?) 1.9 (D) (BUT need to change core)

PARP(83) 0.5 0.5 0.5 (D) √

PARP(84) 0.2 / 0.4 (?) 0.2 (PARP(82)=2.2) / 0.4 (PARP(82)=1.9)

0.4 (investigate minimum bias!)

PARP(90) 0.16 0.16 0.16 (D) √

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

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

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

pp

QCDn

Low x_gamma 2nd jet forward

r19822.1/6

R36518.3/6

R38818.7/7

R28463.3/6

Low x_gamma 2nd jet central

R36515.3/7

R38819.3/7

R28448.7/7

R19812.2/7

R36512.8/8

R38816.4/8

R28421.9.8

R19821.9/8

Min-bias also relatively insensitive to pt-min