sigma (mb)

CTEQ-MCnet School 2010 Lauterbad, Germany 26 July - 4 August 2010

Introduction to

Monte Carlo Event Generators

Torbj ¨orn Sj ¨ostrand

Lund University

1. (yesterday) Introduction and Overview; Monte Carlo Techniques 2. (yesterday) Matrix Elements; Parton Showers I

3. (today) Parton Showers II; Matching Issues 4. (today) Multiple Parton–Parton Interactions

5. (tomorrow) Hadronization and Decays; Generator Status

Underlying Events and Minimum Bias

What is minimum bias?

≈ “all events, with no bias from restricted trigger conditions”

σ_tot = σ_elastic+σsingle−diffractive+σdouble−diffractive+. . .+σnon−diffractive

y dn/dy

reality: σ_min−bias ≈ σnon−diffractive+σdouble−diffractive ≈ 2/3 × σ_tot

What is underlying event?

y dn/dy

underlying event jet

pedestal height

What is multiple (partonic) interactions?

Cross section for 2 → 2 interactions is dominated by t-channel gluon exchange, so diverges like dˆσ/dp²_⊥ ≈ 1/p⁴_⊥ for p_⊥ → 0.

integrate QCD 2 → 2 qq^′ → qq^′

qq → q^′q^′ qq → gg qg → qg gg → gg gg → qq

with CTEQ 5L PDF’s

0.01 0.1 1 10 100 1000 10000

0 5 10 15 20 25 30 35 40 45 50

sigma (mb)

pTmin (GeV)

Integrated cross section above pTmin for pp at 14 TeV jet cross section total cross section

σ_int(p_⊥min) =

Z Z Z

p_⊥min dx₁ dx₂ dp²_⊥ f₁(x₁, p²_⊥) f₂(x₂, p²_⊥) dˆσ dp²_⊥ Half a solution to σ_int(p_⊥min) > σ_tot: many interactions per event

σ_tot =

∞ X

n=0

σ_n σ_int =

∞ X

n=0

n σ_n

σ_int > σ_tot ⇐⇒ hni > 1

n P_n

hni = 2

0 1 2 3 4 5 6 7

If interactions occur independently then Poissonian statistics

P_n = hniⁿ

n! e^−hni

but energy–momentum conservation

⇒ large n suppressed

Other half of solution:

perturbative QCD not valid at small p_⊥ since q, g not asymptotic states (confinement!).

Naively breakdown at p_⊥min ≃ ¯h

rp ≈ 0.2 GeV · fm

0.7 fm ≈ 0.3 GeV ≃ Λ_QCD

. . . but better replace rp by (unknown) colour screening length d in hadron

r r

d resolved

r r

d

screened λ ∼ 1/p_⊥

so modify dˆσ

dp²_⊥ ∝ α²_s(p²_⊥)

p⁴_⊥ → α²_s(p²_⊥)

p⁴_⊥ θ (p_⊥ − p_⊥min) (simpler) or → α²_s(p²_⊥0 + p²_⊥)

(p²_⊥0 + p²_⊥)² (more physical)

p²_⊥ dˆσ/dp²_⊥

0

where p_⊥min or p_⊥0 are free parameters, empirically of order 2 GeV

Typically 2 – 3 interactions/event at the Tevatron, 4 – 5 at the LHC, but may be more

in “interesting” high-p_⊥ ones.

Basic generation of multiple (partonic) interactions

• For now exclude diffractive (and elastic) topologies,

i.e. only model nondiffractive events, with σ_nd ≃ 0.6 × σ_tot

• Differential probability for interaction at p_⊥ is dP

dp_⊥ = 1 σ_nd

dσ dp_⊥

• Average number of interactions naively hni = 1

σ_nd

Z _Ecm/2 0

dσ

dp_⊥ dp_⊥

• Require ≥ 1 interaction in an event

or else pass through without anything happening

P_≥1 = 1 − P₀ = 1 − exp(−hni) (Alternatively: allow soft nonperturbative interactions even if no perturbative ones.)

Can pick n from Poissonian and then generate n independent interactions according to dσ/dp_⊥ (so long as energy left), or better. . .

. . . generate interactions in ordered sequence p_⊥1 > p_⊥2 > p_⊥3 > . . .

• recall “Sudakov” trick used e.g. for parton showers:

if probability for something to happen at “time” t is P (t)

and happenings are uncorrelated in time (Poissonian statistics) then the probability for a first happening after 0 at t₁ is

P(t₁) = P (t₁) exp



−

Z _t1

0 P (t) dt



and for an i’th at t_i is

P(t_i) = P (t_i) exp −

Z _ti

t_i−1 P (t) dt

!

• Apply to ordered sequence of decreasing p_⊥, starting from E_cm/2 P(p_⊥ = p_⊥i) = 1

σ_nd dσ

dp_⊥ exp

"

−

Z _p

⊥(i−1)

p_⊥

1 σ_nd

dσ

dp^′_⊥dp^′_⊥

#

• Use rescaled PDF’s taking into account already used momentum

=⇒ n_int narrower than Poissonian

Impact parameter dependence

So far assumed that all collisions have equivalent initial conditions, but hadrons are extended,

e.g. empirical double Gaussian:

ρ_matter(r) = N₁ exp −r² r²₁

!

+ N₂ exp −r² r²₂

!

where r₂ 6= r₁ represents “hot spots”, and overlap of hadrons during collision is

O(b) =

Z

d³x dt ρ^boosted_1,matter(x, t)ρ^boosted_2,matter(x, t) or electromagnetic form factor:

Sp(b) =

Z d²k 2π

exp(ik · b) (1 + k²/µ²)² where µ = 0.71 GeV → free parameter, which gives

O(b) = µ²

96π (µb)³ K₃(µb)

1e-05 0.0001 0.001 0.01 0.1 1

0 1 2 3 4 5 6 7 8

O(b)

b

Tune A double Gaussian old double Gaussian Gaussian ExpOfPow(d=1.35) exponential EM form factor

p p

b

b hni

1 all

n ≥ 1

• Events are distributed in impact parameter b

• Average activity at b proportional to O(b)

⋆ central collisions more active ⇒ P_n broader than Poissonian

⋆ peripheral passages normally give no collisions at all ⇒ finite σ_tot

• Also crucial for pedestal effect (more later)

PYTHIA implementation

(1) Simple scenario (1985):

first model for event properties based on perturbative multiple interactions no longer used (no impact-parameter dependence)

(2) Impact-parameter-dependence (1987):

still in frequent use (Tune A, Tune DWT, ATLAS tune, . . . )

• double Gaussian matter distribution,

• interactions ordered in decreasing p_⊥,

• PDF’s rescaled for momentum conservation,

• but no showers for subsequent interactions and simplified flavours (3) Improved handling of PDFs and beam remnants (2004)

• Trace flavour content of remnant, including baryon number (junction)

u u

d

• Study colour (re)arrangement

among outgoing partons (ongoing!)

• Allow radiation for all interactions

(4) Evolution interleaved with ISR (2004)

• Transverse-momentum-ordered showers dP

dp_⊥ = dP_MI

dp_⊥ + ^X dP_ISR dp_⊥

!

exp −

Z _p⊥i−1 p_⊥

dP_MI

dp^′_⊥ + ^X dP_ISR dp^′_⊥

!

dp^′_⊥

!

with ISR sum over all previous MI

interaction number

p_⊥

p_⊥max

p_⊥min

hard int.

1 p_⊥1

mult. int.

2

mult. int.

3 p_⊥2

p_⊥3

ISR

ISR

ISR p^′_⊥1

(5) Rescattering (2009)

is 3 → 3 instead of 4 → 4:

HERWIG implementation

(1) Soft Underlying Event (1988), based on UA5 Monte Carlo

´ H µ C¶ ·N <= < U º Ö Q

N K FIWV ? K

N < F= B R Q IJ S I ;< W Q AM= K

ZX ç ` ì _ ] _ ê a

` Yjk i ^

` mn flop t Z[ s

[ Z\ w v^] ] q

y

Ü = O ; FIP = S IJ A Q I ;K M I< FB ISN FI AJ < ; Q >K= M @ AB _ `a

xK

N < F= B < O

= J= B ; F= M N J FIK >B= <= K

= ? F= M _ ` a I< B= ; ?: = M

• Distribute a (∼ negative binomial) number of clusters independently in rapidity and transverse momentum according to parametrization/extrapolation of data

• modify for overall energy/momentum/flavour conservation

• no minijets; correlations only by cluster decays

(2) Jimmy (1995; HERWIG add-on; part of HERWIG++)

• only model of underlying event, not of minimum bias

• similar to PYTHIA (2) above; but details different

• matter profile by electromagnetic form factor (tuned)

• no p_⊥-ordering of emissions, no rescaling of PDF:

abrupt stop when (if) run out of energy

(3) Ivan (2002, code not public; part of HERWIG++)

• also handles minimum bias

• soft and hard multiple interactions together fill whole p_⊥ range p_⊥min p_⊥ dσ/dp_⊥

PhoJet (& relatives) implementation

(1) Cut Pomeron (1982)

• Pomeron predates QCD; nowadays ∼ glueball tower

• Optical theorem relates σ_total and σ_elastic

∝

2

⇒

• Unified framework of nondiffractive and diffractive interactions

• Purely low-p_⊥: only primordial k_⊥ fluctuations

• Usually simple Gaussian matter distribution

(2) Extension to large p_⊥ (1990)

• distinguish soft and hard Pomerons (cf. Ivan):

soft = nonperturbative, low-p_⊥, as above hard = perturbative, “high”-p_⊥

• hard based on PYTHIA code, with lower cutoff in p_⊥

Indirect evidence for multiple interactions

without multiple interactions

with multiple interactions

Direct observation of multiple interactions

Five studies: AFS (1987), UA2 (1991), CDF (1993, 1997), D0 (2009) Order 4 jets p_⊥1 > p_⊥2 > p_⊥3 > p_⊥4 and define ϕ

as angle between p_{⊥1 ∓} p_⊥2 and p_{⊥3 ∓} p_⊥4 for AFS/CDF Double Parton Scattering

1 2

3

4

|p_⊥1 + p_⊥2| ≈ 0

|p_⊥3 + p_⊥4| ≈ 0 dσ/dϕ flat

Double BremsStrahlung

1 2

3 4

|p_⊥1 + p_⊥2| ≫ 0

|p_⊥3 + p_⊥4| ≫ 0

dσ/dϕ peaked at ϕ ≈ 0/π for AFS/CDF

AFS 4-jet analysis (pp at 63 GeV): observe 6 times Poissonian prediction, with impact parameter expect 3.7 times Poissonian,

but big errors ⇒ low acceptance, also UA2

Figure 1:
S distribution for 1VTX data (points). The DP component to the data, determined by the two-dataset method to be 52.6% of the sample, is shown as the shaded region (the shape is taken from MIXDP). Also shown is the admixture 52.6% MIXDP + 47.4% PYTHIA, normalized to the data (line).

16

CDF 3-jet + prompt photon analysis Yellow region = double parton scattering (DPS) The rest =

PYTHIA showers

σ_DPS = σ_Aσ_B

σ_eff for A 6= B =⇒ σ_eff = 14.5 ± 1.7^+1.7_−2.3 mb Strong enhancement relative to naive expectations!

D0 results:

(GeV)

jet2

pT

10 12 14 16 18 20 22 24 26 28 30

Fraction of DP events

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

tune A, Pythia 6.420 tune S0, Pythia 6.420 data

+ 3 jets + X γ

(GeV)

jet2

pT

16 18 20 22 24 26 28 30 (mb) effσ

0 5 10 15 20 25

= 1.0 fb -1

DØ Preliminary, Lint

σ_eff = 15.1 ± 1.9 mb agreement and precision “too good to be true”;

tunes 7 and 3 years old, respectively, and not to this kind of data

Same study also planned for LHC Selection for DPS delicate balance:

showers dominate at large p_⊥

⇒ too large background

multiple interactions dominate at small p_⊥, but there jet

identification difficult

.

(jet 3) (GeV/c) p

10 20 30 40 50

(nb / GeV/c)

/dp σ d

10

10

1

MI off

Pythia 8.108

+ X @ 14 TeV γ

→ pp

(R = 0.4), CDF selections kT

Jet pedestal effect

Events with hard scale (jet, W/Z, . . . ) have more underlying activity!

Events with n interactions have n chances that one of them is hard, so “trigger bias”: hard scale ⇒ central collision

⇒ more interactions ⇒ larger underlying activity.

Centrality effect saturates at p_⊥hard ∼ 10 GeV.

Studied in detail by Rick Field, comparing with CDF data:

(see http://www.phys.ufl.edu/∼rfield/cdf/rdf talks.html)

“MAX/MIN Transverse” Densities

x Define the MAX and MIN “transverse” regions on an event-by-event basis with MAX (MIN) having the largest (smallest) density.

x The “transMIN” region is very sensitive to the “beam-beam remnant” and x

Jet #1 Direction 'I

“Toward”

“TransMAX” “TransMIN”

“Away”

Jet #1 Direction

'I

“TransMAX” “TransMIN”

“Toward”

“Away”

“Toward-Side” Jet

“Away-Side” Jet Jet #3

“TransMIN” very sensitive to the “beam-beam remnants”!

MC Tools for the LHC CERN July 31, 2003

Rick Field - Florida/CDF Page 28

Tuned PYTHIA 6.206 Tuned PYTHIA 6.206

“Transverse” P

“Transverse” P _{T T} Distribution Distribution

"Transverse" Charged Particle Density: dN/dKdI

0.00 0.25 0.50 0.75 1.00

0 5 10 15 20 25 30 35 40 45 50

PT(charged jet#1) (GeV/c)

"Transverse" Charged Density

1.8 TeV |K|<1.0 PT>0.5 GeV CDF Preliminary

data uncorrected theory corrected

CTEQ5L

PYTHIA 6.206 (Set A) PARP(67)=4

PYTHIA 6.206 (Set B) PARP(67)=1

PARP(67)=4.0 (old default) is favored over PARP(67)=1.0 (new default)!

P_T(charged jet#1) > 30 GeV/c

"Transverse" Charged Particle Density

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00

0 2 4 6 8 10 12 14

PT(charged) (GeV/c)

Charged Density dN/dKdIdPT (1/GeV/c)

CDF Data

data uncorrected theory corrected

1.8 TeV |K|<1 PT>0.5 GeV/c PT(chgjet#1) > 5 GeV/c

PT(chgjet#1) > 30 GeV/c

PYTHIA 6.206 Set A PARP(67)=4

PYTHIA 6.206 Set B PARP(67)=1

¨ Compares the average “transverse” charge particle density (|K|<1, P_T>0.5 GeV) versus P_T(charged jet#1) and the P_T distribution of the “transverse” density, dN_chg/dKdIdP_T with the QCD Monte-Carlo predictions of two tuned versions of PYTHIA 6.206 (P_T(hard) > 0, CTEQ5L, Set B (PARP(67)=1) and Set A (PARP(67)=4)).

KITP Collider Workshop February 17, 2004

Rick Field - Florida/CDF Page 58

Back Back - - to to - - Back Back “Associated” “Associated”

Charged Particle Densities Charged Particle Densities

'I

Jet#1 Region

PTmaxT Direction

Jet#2 Region

¨ Shows the 'I dependence of the “associated” charged particle density, dNchg/dKdI, p_T > 0.5 GeV/c, |K| < 1, PTmaxT > 2.0 GeV/c (not including PTmaxT) relative to PTmaxT (rotated to 180^o) and the charged particle density, dN^chg/dKdI, p_T > 0.5 GeV/c, |K| < 1, relative to jet#1 (rotated to 270^o) for “back-to-back events” with 30 < E_T(jet#1) < 70 GeV.

Jet #1 Direction 'I

“Toward”

“Transverse” “Transverse”

“Away”

Jet #2 Direction

Charged Particle Density: dN/dKdI

2

6 10 14

18 22

26 30

34 38

42 46

50 54

58

62

66

70

74

78

82

86

90

94

98

102

106

110

114

118

122

126 130

134 138 142 146 150 154 158 162 166 174 170 178 182 190 186 194 198 202 206 210 214 218 222 226 230 234 238 242 246 250 254 258 262 266 270 274 278 282 286

290 294

298 302

306 310

314 318

322 326

330 334

338 342

346 350 354 358

CDF Preliminary

data uncorrected

30 < ET(jet#1) < 70 GeV Back-to-Back

Charged Particles (|K|<1.0, PT>0.5 GeV/c)

"Transverse"

Region "Transverse"

Region Jet#1

Associated Density PTmaxT > 2 GeV/c

(not included) PTmaxT

Polar Plot

“Back-to-Back”

“associated” density

“Back-to-Back”

charge density

0.5

1.0

1.5

2.0

KITP Collider Workshop February 17, 2004

Rick Field - Florida/CDF Page 71

“ “ Associated” Charge Density Associated” Charge Density PYTHIA Tune A

PYTHIA Tune A vs vs HERWIG HERWIG

Associated Particle Density: dN/dKdI

0.1 1.0 10.0

0 30 60 90 120 150 180 210 240 270 300 330 360

'I (degrees)

Associated Particle Density

PTmaxT > 2.0 GeV/c PY Tune A

Back-to-Back 30 < ET(jet#1) < 70 GeV Charged Particles

(|K|<1.0, PT>0.5 GeV/c)

PTmaxT

CDF Preliminary

data uncorrected

theory + CDFSIM PTmaxT not included

"Jet#1"

Region

Associated Particle Density: dN/dKdI

0.1 1.0 10.0

0 30 60 90 120 150 180 210 240 270 300 330 360

'I (degrees)

Associated Particle Density

PTmaxT > 2.0 GeV/c HERWIG

Back-to-Back 30 < ET(jet#1) < 70 GeV Charged Particles

(|K|<1.0, PT>0.5 GeV/c)

PTmaxT

CDF Preliminary

data uncorrected

theory + CDFSIM PTmaxT not included

"Jet#1"

Region

Data - Theory: Associated Particle Density dN/dKdI

-1.6 -0.8 0.0 0.8 1.6

0 30 60 90 120 150 180 210 240 270 300 330 360

'I (degrees)

Data - Theory

CDF Preliminary

data uncorrected theory + CDFSIM

Charged Particles (|K|<1.0, PT>0.5 GeV/c)

Back-to-Back 30 < ET(jet#1) < 70 GeV PYTHIA Tune A

PTmaxT "Jet#1"

Region PTmaxT > 2.0 GeV/c (not included)

Data - Theory: Associated Particle Density dN/dKdI

-1.0 -0.5 0.0 0.5 1.0

0 30 60 90 120 150 180 210 240 270 300 330 360

'I (degrees)

Data - Theory

CDF Preliminary

data uncorrected theory + CDFSIM

Charged Particles (|K|<1.0, PT>0.5 GeV/c)

Back-to-Back 30 < ET(jet#1) < 70 GeV HERWIG

PTmaxT "Jet#1"

Region PTmaxT > 2.0 GeV/c (not included)

For PTmaxT > 2.0 GeV both PYTHIA and HERWIG produce

slightly too many “associated”

particles in the direction of PTmaxT!

But HERWIG (without multiple parton interactions) produces

too few particles in the direction opposite of PTmaxT!

PTmaxT > 2 GeV/c

Colour correlations

hp_⊥i(n_ch) is very sensitive to colour flow

p p

long strings to remnants ⇒ much n_ch/interaction ⇒ hp_⊥i(n_ch) ∼ flat

p p

short strings (more central) ⇒ less n_ch/interaction ⇒ hp_⊥i(n_ch) rising

KITP Collider Workshop February 17, 2004

Rick Field - Florida/CDF Page 35

“ “ Transverse” < Transverse” < p p _{T T} > versus > versus

“Transverse”

“Transverse” N N chg chg

Jet #1 Direction 'I

“Toward”

“Transverse” “Transverse”

“Away”

Jet #1 Direction 'I

“Toward”

“Transverse” “Transverse”

“Away”

Jet #2 Direction

¨ Shows <p_T> versus N^chg in the “transverse” region (p_T > 0.5 GeV/c, |K| < 1) for

“Leading Jet” and “Back-to-Back” events with 30 < E_T(jet#1) < 70 GeV compared with

“min-bias” collisions.

“Leading Jet”

“Back-to-Back”

¨ Look at the <p_T> of particles in the “transverse” region (p_T > 0.5 GeV/c, |K| < 1) versus the number of particles in the “transverse” region: <p_T> vs N^chg.

Min-Bias

"Transverse" Average PT versus Nchg

0.5 1.0 1.5 2.0

0 2 4 6 8 10 12 14 16 18 20 22

Number of Charged Particles

Average PT (GeV/c)

CDF Run 2 Preliminary

data uncorrected theory + CDFSIM

Charged Particles (|K|<1.0, PT>0.5 GeV/c) PYTHIA Tune A 1.96 TeV

Min-Bias

Leading Jet 30 < ET(jet#1) < 70 GeV

Back-to-Back 30 < ET(jet#1) < 70 GeV

Energy dependence of p _⊥min and p _⊥0

Larger collision energy

⇒ probe parton (≈ gluon) density at smaller x

⇒ smaller colour screening length d

⇒ larger p_⊥min or p_⊥0 Post-HERA PDF fits steeper at small x

⇒ stronger energy dependence

For a long time PYTHIA default (Tune A, old model), tied to CTEQ 5L, was

p_⊥min(s) = 2.0 GeV

 E_CM 1.8 TeV

_0.16

In recent years debate in the range 0.20 – 0.30 ⇒ slower increase

5^thNovember 2004 Minimum-bias and the Underlying Event at the LHC

A. M. Moraes

LHC predictions: pp collisions at ¥s = 14 TeV

0 2 4 6 8 10

10² 10³ 10⁴ 10⁵

PYTHIA6.214 - tuned PYTHIA6.214 - default PHOJET1.12

pp interactions-

UA5 and CDF data

dN chg/dȘatȘ=0

¥s (GeV)

•PYTHIAmodels favour ln²(s);

•PHOJETsuggests a ln(s) dependence.

LHC

2 4 6 8 10 12

0 10 20 30 40 50

CDF data

PYTHIA6.214 - tuned

PHOJET1.12 LHC

Tevatron

x1.5 x 3

dN_chg/dȘ ~ 30

dN_chg/dȘ ~ 15

Central Region

(min-bias dN_chg/dȘ ~ 7)

Transverse < N chg>

P_t(leading jet in GeV)

5^thNovember 2004 Minimum-bias and the Underlying Event at the LHC

A. M. Moraes

LHC predictions: JIMMY4.1 Tunings A and B vs.

PYTHIA6.214 – ATLAS Tuning (DC2)

5 10 15 20

0 10 20 30 40 50

CDF data

JIMMY4.1 - Tuning A JIMMY4.1 - Tuning B

PYTHIA6.214 - ATLAS Tuning

Transverse < N chg>

P_t (leading jet in GeV) Tevatron LHC

x 4

x 5

x 3

dN _ch /dη vs. Monte Carlo

! 

Pythia D6T and Perugia-0 match neither INEL, NSD or INEL>0 at any energy

! 

Pythia ATLAS-CSC and Phojet reasonably close with some deviations at 0.9 and 2.36 TeV

! 

Only ATLAS-CSC close at 7 TeV

Physics at LHC 2010, DESY-Hamburg, 09.06.10 Andrea Dainese 9

2.36 TeV

0.9 TeV 7 TeV

30

!"#$%&'()#$*+,&(-.,*/,0+0*&1(#2(3145678(9(:&;

Christophe Clement Physics at LHC, DESY, June 9th, 2010 ― ATLAS First Physics Results

Monte Carlo underestimates the track multiplicity seen in ATLAS

dN/dN _ch : vs. Monte Carlo

!  Phojet

"  provides a good description at 900 GeV

"  fails at 2.36 and 7 TeV

!  Pythia Atlas CSC

"  fails at 0.9 TeV

"  reasonably close at 2.36 and 7 TeV but deviations around 10-20

!  Pythia D6T and Perugia-0 far from the distribution at all energies

0.9 TeV 2.36 TeV 7 TeV

arXiv:1004.3034 arXiv:1004.3514

12 12

Physics at the LHC 2010, DESY-Hamburg, 09.06.10 Andrea Dainese 12

arXiv:1004.3034

Physics at LHC 2010, DESY-Hamburg, 09.06.10 Andrea Dainese 12 12

32

!"#$%&'(")*+,$"-*./0

Christophe Clement Physics at LHC, DESY, June 9th, 2010 ― ATLAS First Physics Results

leading track p_T

•  All MC tunes underestimate activity by 10-15% in plateau of transverse region Observed both for particle density and sum of track p_T

•  Increase of factor two in UE activity from 900 GeV to 7 TeV, comparable to MC prediction

•  Plateau at pTlead> 3 GeV at 900GeV and p_T^lead>5 GeV at 7 TeV

•  From plateau region ~2.5 charged particles per unit of η at 900 GeV and 5 particles at 7 TeV.

leading track p_T

UE&MB Working Group Meeting LPCC May 31, 2010

Rick Field – Florida/CDF/CMS Page 10

“ “ Transverse Transverse ” ” Charge Density Charge Density

PTmax Direction

∆φ∆φ

∆φ∆φ

“Toward”

“Transverse” “Transverse”

“Away”

PTmax Direction

∆φ∆φ∆φ

∆φ

“Toward”

“Transverse” “Transverse”

“Away”

LHC

900 GeV LHC

7 TeV 900 GeV ! 7 TeV

(UE increase ~ factor of 2)

! Ratio of the ATLAS preliminary data on the charged particle density in the “transverse” region for charged particles (p_T > 0.5 GeV/c, |ηηη| < 2.5) at 900 GeV and 7 TeVη as defined by PTmax

compared with PYTHIA Tune CW, DW, and ATLAS MC08.

~0.4 ! ~0.8

PARP(90) = 0.16

PARP(90) = 0.25

PARP(90) = 0.30

"Transverse" Charged Particle Density: dN/dηηηηdφφφφ

0.0 1.0 2.0 3.0

0 1 2 3 4 5 6 7 8 9 10 11 12

PTmax (GeV/c)

Ratio: 7 TeV/900 GeV

Charged Particles (|ηηηη|<2.5, PT>0.5 GeV/c) RDF Preliminary

ATLAS corrected data generator level theory

7 TeV / 900 GeV

Tune DW

ATLAS MC08 Tune CW

UE&MB Working Group Meeting LPCC May 31, 2010

Rick Field – Florida/CDF/CMS Page 21

UE Summary UE Summary

!The “underlying event” at 7 TeV and 900 GeV is almost what we expected! I expect that a PYTHIA 6 tune just slightly different than Tune DW will fit the UE data perfectly including the energy

dependence (Tune X1 is not bad!).

I also expect to see good PYTHIA 8 tune soon!

!“Min-Bias” is a whole different story!

Much more complicated due to diffraction!

!I will quickly show you some of my attempts (all failures) to fit the LHC

“min-bias” data.

Proton Proton

PT(hard)

Outgoing Parton

Outgoing Parton

Underlying Event Underlying Event

Initial-State Radiation

Final-State Radiation

PARP(90)

Color

Connections

PARP(82)

Diffraction

34

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Christophe Clement Physics at LHC, DESY, June 9th, 2010 ― ATLAS First Physics Results

Used for the tune

ATLAS UE data at 0.9 and 7 TeV

ATLAS charged particle densitites at 0.9 and 7 TeV CDF Run I underlying event analysis (leading jet) CDF Run I underlying event "Min-Max" analysis D0 Run II dijet angular correlations

CDF Run II Min bias CDF Run I Z pT

Result

This tune describes most of the MinBias and the UE data Significant improvement compared to pre-LHC tunes Biggest remaining deviation in

These deviations could not be removed Needs further investigtions

Diffraction

QM: diffraction is shadow of inelastic interactions (disturbed p wavefn).

Predominantly edge phenomenon ⇔ large impact parameter.

Regge theory: scattering by resonance exchange, predates QCD.

Pomeron: Regge trajectory of states with vacuum quantum numbers.

QCD interpretation: glueball state/ladder.

p

p

p

p

p

p

p

p

p

p

IP IP

IP

Regge theory predicts/parametrizes rate of diffractive interactions, but does not tell what diffractive events look like.

(. . . and actually the predicted rate rises too fast ⇒ eikonalization . . . )

Ingelman-Schlein (1984): Pomeron as hadron with partonic content Diffractive event = (Pomeron flux) × (IPp collision)

p p

IP p

pp → pX

Diffractive events can contain high-p_⊥ jets:

σ ∼

Z

f_IP/p(x_IP, t)

Z

f_i/IP(x_i, Q²)

Z

f_j/p(x_j, Q²)

Z

dˆσ_ij with M_X² = x_IPs and ˆs = x_ix_jM_X² .

f_IP/p(x_IP, t) ∼ 1

x_IP ⇒ dσ

dM_X² ∼ 1

M_X² ⇒ dσ

dygap ∼ constant Many issues, e.g.:

1) imperfect factorization f_i/p(x_IP, t, x_i, Q²) = f_IP/p(x_IP, t) f_i/IP(x_i, Q²) 2) poor knowledge of f_IP/p(x_IP, t) and f_i/IP(x_i, Q²)

3) parameters of multiple interactions framework 4) multipomeron topologies, . . .

Initiators and Remnants

p

g u s s u d

initiators:

in to hard interaction

beam remnants

Need to assign:

• correlated flavours

• correlated x_i = p_zi/p_ztot

• correlated primordial k_⊥i

• correlated colours

• correlated showers

• PDF after preceding MI/ISR activity:

0) Squeeze range 0 < x < 1 into 0 < x < 1 − ^P x_i (ISR: i 6= i_current) 1) Valence quarks: scale down by number already kicked out

2) Introduce companion quark q/q to each kicked-out sea quark q/q, with x based on assumed g → qq splitting

3) Gluon and other sea: rescale for total momentum conservation

Beam remnant physics

Colour flow connects hard scattering to beam remnants.

Can have consequences, e.g. in π⁻p

A(x_F) = #D⁻ − #D⁺

#D⁻ + #D⁺

-0.2 0 0.2 0.4 0.6 0.8 1 1.2

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 A(xF)

x_F Pair production (a)

All channels WA92, 350 GeV WA82, 340 GeV E791, 500 GeV E769, 250 GeV

(also B asymmetries at LHC, but small)

p⁺ π⁻

u u

c c

ud d

If low-mass string e.g.:

cd: D⁻, D^∗−

cud: Λ⁺_c , Σ⁺_c , Σ^∗+_c

⇒ flavour asymmetries

d c

s ssssssssss ss ss s sss ss s ss ss ss ss ss ss ss ss ss ss s ss ss ss ss ss s ss ss s ss ss ss s ss ss s ss ss s ss ss

s ss s

ss ss s ss ss s s

ss s ss s ss s ss s

s s ss s ss s s ss s

s s ss s s s ss s s ss

ss s s s ss s s s s ss

s s s s s s ss s s s s s

s sssssssssssssssssssssssssssss

D

Can give D ‘drag’ to larger x_F than c quark for any string mass

Summary Lecture 4

• Multiple interactions concept compelling; it has to exist at some level. •

⋆ By now, strong direct evidence, overwhelming indirect evidence ⋆

• Understanding of multiple interactions crucial for LHC precision physics •

• Many details uncertain •

⋆ p_⊥min/p_⊥0 cut-off ⋆

⋆ impact parameter picture ⋆

⋆ energy dependence ⋆

⋆ multiparton densities in incoming hadron ⋆

⋆ colour correlations between scatterings ⋆

⋆ interferences between showers ⋆

⋆ . . .⋆

• Above physics aspects must all be present, and more? • If a model is simple, it is wrong!

• So stay tuned for even more complicated models in the future. . . . •