QCD in hadron collisions - CERNSome of what goes into collider predictions event underlying π, K,...

QCD in hadron collisions

Gavin Salam

CERN, Princeton University & LPTHE/CNRS (Paris)

XXVI Rencontres de Physique de la Vallee d’AosteLa Thuile, Italy, February 26 – March 3 2012

An exciting past 18 months

tt asymmetry

W + dijet CDF anomaly

Exclusion of swathes of SUSY, etc.

Higgs Hints

. . .

This talk: examine recent collider-QCD developments andthe role they’re playing in some of these “headline” topics,

as well as touch on some open problems

Gavin Salam (CERN/Princeton/CNRS) QCD in hadron collisions La Thuile 2012-02-28 2 / 22

Some of what goes into collider predictions

eventunderlying

π, K, p, etc.hadronisation

shower

u

proton proton

τ + τ −

H

u

u

hardproc.


Some of what goes into collider predictions

eventunderlying


shower

u

proton proton

τ + τ −

H

u

u

hardproc.

αn + αn+1 + ...

τ + τ −

H

u

u

hardproc.


The hard process is where we use pQCD expansion in αs

Consider LO, NLO and their ratio K =NLO

LO

0.001

0.01

0.1

1

10

100

1000

200 400 600 800 1000 1200 1400

dσ/d

p t [p

b/G

eV]

pt [GeV]

pp, 14 TeVFastNLO, kt R=0.7

LO

NLO

NLO/LO ≃ 1.2

Adapted from Rubin, GPS & Sapeta ’10

Look at p t ofquark or gluon (jets)

gluon

proton proton

quark

K of 1.2 is compatible with being 1 +O (αs)




LO

10-2

10-1

1

101

102

103

104

200 400 600 800 1000 1200 1400

dσ/d

p t,Z

[fb

/ 100

GeV

]

pt,Z [GeV]

pp, 14 TeV

LO

NLO

NLO/LO ≃ 1.5

MCFM


Look at p t ofZ−boson Z−boson

proton proton

quark

K of 1.5 is compatible with being 1 + C × αs, with quite large C

To date, no generalised understanding of size of C when in range 5− 10




LO

10-2

10-1

1

101

102

103

104

200 400 600 800 1000 1200 1400

dσ/d

p t,j1

[fb

/ 100

GeV

]

pt,j1 [GeV]

pp, 14 TeV

LO

NLO

NLO/LO ≃ 5

MCFM


Look at p t ofquark (jet) Z−boson

proton proton

quark

1 + Cαs −→ K = 5 ?!! Often driven by new topologies


The NLO revolution

and one way it’s being used


SUSY example: gluino pair production

Signal

~g

~g~g

~q

~q

χ0

χ0

g

q

q

q

q

g



Signal

~g

~g~g

~q

~q

χ0

χ0

g

q

q

q

q

g

ET/

ET/

jet

jet

jet

jet



Signal Background

~g

~g~g

~q

~q

χ0

χ0

g

q

q

q

q

g

ET/

ET/

jet

jet

jet

jet

g

q

g

ν

ν−

g

q

q

Z



Signal Background

~g

~g~g

~q

~q

χ0

χ0

g

q

q

q

q

g

ET/

ET/

jet

jet

jet

jet

g

q

g

ν

ν−

g

q

q

ZET/

jet jet

jet

jet



Signal Background

~g

~g~g

~q

~q

χ0

χ0

g

q

q

q

q

g

ET/

ET/

jet

jet

jet

jet

g

q

g

ν

ν−

g

q

q

ZET/

jet jet

jet

jet


Complexity of NLO calculation determinedby final-state multiplicity: a 2 → 5 process.

NLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timelineNLO timeline

1980 1985 1990 1995 2000 2005 2010


1980 1985 1990 1995 2000 2005 2010

2→

1

1979: NLO Drell-Yan [Altarelli, Ellis & Martinelli]

http://dx.doi.org/10.1016/0550-3213(79)90116-0


1980 1985 1990 1995 2000 2005 2010

2→

1

2→

2

1987: NLO high-pt photoproduction [Aurenche et al]1988: NLO bb, tt [Nason et al]1993: dijets, Vj [JETRAD, Giele, Glover & Kosower]

http://dx.doi.org/10.1016/0550-3213(87)90453-6


1980 1985 1990 1995 2000 2005 2010

2→

1

2→

2

2→

3

1998: NLO Wbb [MCFM: Ellis & Veseli]2000: NLO Zbb [MCFM: Campbell & Ellis]2001: NLO 3j [NLOJet++: Nagy]· · ·

2007: NLO tt j [Dittmaier, Uwer & Weinzierl ’07]· · ·

http://arxiv.org/abs/hep-ph/9810489





1980 1985 1990 1995 2000 2005 2010

2→

1

2→

2

2→

3

2→

4(W

/Z+3j,ttbb,ttjj,...)


1980 1985 1990 1995 2000 2005 2010

2→

1

2→

2

2→

3

2→

4(W


2009: NLO W+3j [Rocket: Ellis, Melnikov & Zanderighi] [unitarity]2009: NLO W+3j [BlackHat+Sherpa: Berger et al] [unitarity]2009: NLO ttbb [Bredenstein et al] [traditional]2009: NLO ttbb [HELAC-NLO: Bevilacqua et al] [unitarity]2009: NLO qq → bbbb [Golem: Binoth et al] [traditional]2010: NLO tt jj [HELAC-NLO: Bevilacqua et al] [unitarity]2010: NLO Z+3j [BlackHat+Sherpa: Berger et al] [unitarity]. . .

http://arxiv.org/abs/0901.4101








1980 1985 1990 1995 2000 2005 2010

2→

1

2→

2

2→

3

2→

4(W


2→

5(W

+4j,Z+4j)

automation

2→

6(ee→

7j[LC])

2010: NLO W+4j [BlackHat+Sherpa: Berger et al] [unitarity]2011: NLO WWjj [Rocket: Melia et al] [unitarity]2011: NLO Z+4j [BlackHat+Sherpa: Ita et al] [unitarity]2011: NLO 4j [BlackHat+Sherpa: Bern et al] [unitarity]2011: first automation [MadNLO: Hirschi et al] [unitarity + feyn.diags]2011: first automation [Helac NLO: Bevilacqua et al] [unitarity]2011: first automation [GoSam: Cullen et al] [feyn.diags(+unitarity)]2011: e+e− → 7j [Becker et al, leading colour] [numerical loops]









W + 0,1,2,3,4 jets @NLO je

ts)

[pb]

jet

N≥(W

+

σ

1

10

210

310

410 + jetsνl→W

=7 TeVsData 2010, ALPGENSHERPAPYTHIABLACKHAT-SHERPA

-1Ldt=36 pb∫ jets, R=0.4Tanti-k

|<4.4jet y>30 GeV, |T

jetp

ATLAS

jets

) [p

b]je

tN≥

(W +

σ

1

10

210

310

410

jetNInclusive Jet Multiplicity,

0≥ 1≥ 2≥ 3≥ 4≥

The

ory/

Dat

a

0

1


0≥ 1≥ 2≥ 3≥ 4≥

The

ory/

Dat

a

0

1


0≥ 1≥ 2≥ 3≥ 4≥

The

ory/

Dat

a

0

1

Technical revolution has gonehand-in-hand with LHCmeasurements of thesecomplex processes.

Powerful validation of NLOapproach.

So do SUSY searches nowjust compare data to NLO?


Two plots from a CMS SUSY analysis

Data v. Monte Carlo backgrounds Data v. “data-driven” backgrounds

So where are the NLO predictions being used?


The CMS search did not estimate Z+jets bkgd from NLO. Instead used

dσZ+jets

dHT

=

(

dσγ+jets

dHT

)

data

×

(

dσZ+jets

dHT

/dσγ+jets

dHT

)

NLO

300 400 500 600 700 800 900 1000

HT

jet [ GeV ]

0

0.1

0.2

0.3

0.4

0.5

dσ (

Z+

2 je

ts)

/ dσ

(γ+

2 je

ts) LO

NLOME+PS

( Z + 2 jets + X ) / ( γ + 2 jets + X )

BlackHat+Sherpa

CMS Set 1

√s = 7 TeV

µR = µ

F = H

T

^ ’ / 2

Example of widelyused data-drivenbkgd estimates

Combine best oftheory knowledgewith best of exper-imental knowledge.


Merging NLO and showers

and the CDF W + dijet anomaly


Remember the CDF W+dijet excess?

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

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) -1CDF data (4.3 fbGaussian 2.5%WW+WZ 4.8%W+Jets 78.0%Top 6.3%

xxx

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Z+jets 2.8%QCD 5.1%

(c)


xxx

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Z+jets 2.8%QCD 5.1%

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

0

100

200

300

400

500

600

700

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

-50

0

50

100

150) -1Bkg Sub Data (4.3 fb

Gaussian

WW+WZ

) -1Bkg Sub Data (4.3 fb

Gaussian

WW+WZ

(a)


and the D0 W+dijet non-excess?

]2Dijet Mass [GeV/c0 50 100 150 200 250 300

)2E

ve

nts

/ (

10

Ge

V/c

0

200

400

600

800

1000

1200DataDibosonW+JetsZ+JetsTopMultijetsGaussian (4 pb)

2 = 145 GeV/cjjM

-1DØ, 4.3 fb

(a)

]2Dijet Mass [GeV/c0 50 100 150 200 250 300

)2E

ve

nts

/ (

10

Ge

V/c

-50

0

50

100

150

200

250

300Data - Bkgd

1 s.d.±Bkgd

DibosonGaussian (4 pb)

2 = 145 GeV/cjjM

-1DØ, 4.3 fb(b)

) = 0.5262χP(

CDF and DØ data are not being compared to NLO (=W+partons):

They are “detector-level” data and can only be compared tohadron-level calculations + detector simulation.

In this case hadron-level = Alpgen ⊗ Pythia


Perturbative expansion: for precision.Parton Showers (PS): for realism;

To combine them: must remove double counting

Tree-level (LO) + PSDifferent tree-level multiplicites (W, W+1j, W+2j, etc.) get combined

MLM/CKKW: Alpgen+Pythia/Herwig, MadGraph, Sherpa, . . .Fully automated


eventunderlying


shower

u

proton proton

τ + τ −

H

u

u

hardproc.

αn + αn+1 + ...

τ + τ −

H

u

u

hardproc.

⊗

eventunderlying


shower

u

proton proton

τ + τ −

H

u

u

hardproc.


shower

NLO + PS — MC@NLO, POWHEGGreater accuracy, but harder to perform than LO+PS:

NLO contains more physics than LO,so more double-counting with parton shower

Less “available” than tree+PS: until recently,➥ A single (low) multiplicity, e.g. W@NLO + PS

➥ Programmed manually for each process

Recently: move towards automation:

POWHEGBox: tt+jet, W+W++2j, . . .aMC@NLO (MadLoop + auto MC@NLO): W+2j, Z+2b, . . .

+ ideas for combining multiplicities, e.g. MENLOPS, . . .

A key application of this progress has been to the W+dijet anomaly


CDF & DØ use Alpgen (scaled): tree level QCD + parton shower

adapted from Frederix et al 1110.5502



NLO has substantial shape differences: should we worry?




NLO has substantial shape differences: should we worry?

NLO + parton shower (aMC@NLO) is close to Alpgen→ QCD under good control



Instead of data−MC ⇒ data/MC

]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

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Z+jets 2.8%QCD 5.1%

(c)


xxx

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Z+jets 2.8%QCD 5.1%

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

0

100

200

300

400

500

600

700

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data

CDF lνjj data (7.3 fb-1)MC = VV, V+j, ttbar, QCD

MC + Gaussian

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200



]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

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Z+jets 2.8%QCD 5.1%

(c)


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Z+jets 2.8%QCD 5.1%

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

0

100

200

300

400

500

600

700

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data


0.8

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1.1

1.2

1.3

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100 200



]2 [GeV/cjjM100 200

)2E

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Z+jets 2.8%QCD 5.1%

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

0

100

200

300

400

500

600

700

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data


0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200

aMC@NLOuncertainties: −→−→−→



]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

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Z+jets 2.8%QCD 5.1%

]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

0

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300

400

500

600

700

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data


0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200

aMC@NLOuncertainties: −→−→−→


“Anomaly” is a 10% effect(not clear it’s really a peak)

10% is clearly at limitof NLO accuracy

Going beyond limitations of NLO[two of the options]


High precision — NNLO — is crucial forkey processes, but not yet always available:

✓ W, Z, Higgs, γγ, VBF, VH

✗ V V , tt, inclusive jets, etc.

Important also to develop methods so thatwe’re less sensitive to limits on our precision.

Generally by finding ways to distinguish signalsfrom the background more efficiently, i.e.

increasing S/B .

NNLO: crucial for precision

New in 2010: NNLO VBF→H

σ (pb) at LHC√s = 7 TeV

scale choice:Q/4 ≤ µR,µF ≤ 4Q

LONLONNLO

10-1

1

10-1

1

σ(µR,µF)/σNNLO(Q)

0.92

0.96

1

1.04

1.08

100 150 200 250 300 350 400 450 500

mH(GeV)

Bolzoni, Maltoni, Moch & Zaro

New in 2011: NNLO WH (differential)

LO

NNLONLO

Ferrera, Grazzini & Tramontano


NNLO: yet not always reassuring

New in 2011: NNLO γγ

LO

NLO

NNLO

Catani et al

Higgs jet veto efficiency

analyses by Stewart & Tackmann ’12

+ Banfi, GPS & Zanderighi

using FeHiP/HNNLO


NNLO: yet not always reassuring

New in 2011: NNLO γγ

LO

NLO

NNLO

Catani et al

Higgs jet veto efficiency

analyses by Stewart & Tackmann ’12

+ Banfi, GPS & Zanderighi

using FeHiP/HNNLO


Some key processes see large or giant NLO/NNLO corrections.

Various techniques — threshold resummation, pt resummation,LoopSim — can improve situation.

Still, can’t help but wonder if we’re missing something,especially in the gg → H case.

Are we using all possible handles to analyse data?

A new sub-field has emerged, “Boost”, for finding boosted tops/Z/H/etc.

It’s teaching us that there are many ways of looking at events,and QCD can educate us about the “best” ways.

[GeV]jm0 20 40 60 80 100 120 140 160 180 200

−1

Eve

nts

/ 4 G

eV /

1 fb

0

100

200

300

400

500

600 R=0.4

[GeV]abcm0 20 40 60 80 100 120 140 160 180 200

−1

/ 10

0GeV

) *

Eve

nts

/ 5 G

eV /

1 fb

abc

(m

0

50

100

150

200

250

300

350

400R=0.7

kt jet alg. C/A jet algorithm

[Search for R-parity violating χ0→ qqq; Butterworth, Ellis, Raklev & GPS ’09]


Closing


0

0.2

0.4

0.6

0.8

1fr

actio

n of

AT

LAS

& C

MS

pap

ers

that

cite

them

Papers commonly cited by ATLAS and CMSas of 2012-02-18, from ’papers’, excluding self-citations

Plo

t by

GP

Sal

am b

ased

on

data

from

AT

LAS

, CM

S a

nd IN

SP

IRE

HE

P

Pyth

ia 6

.4 M

CG

EAN

T4An

ti-k t

jet a

lg.

CTE

Q6

PDFs

MST

W20

08 P

DFs

CTE

Q6.

6 PD

FsH

erw

ig 6

MC

RPP

2010

ALPG

ENLO

* PD

FsM

C@

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JIM

MY

Mad

Gra

ph4

POW

HEG

(200

7)

FEW

Z N

NLO

CT1

0 PD

FsM

C@

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hea

vy-fl

avou

r

Her

wig

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of these 21 papers, 19 are QCD:the common denominator at LHC

today’s progress = tomorrow’sworkhorse

EXTRAS


NLO bottleneck: 1-loop part

TraditionalDraw all Feynman diagrams with 1loop. Work out formulae for them.

Work hard to reduce integrals toknown forms (+ tricks).

Recursive/unitarity methodsAssemble loop-diagrams from indi-vidual tree-level diagrams.

Build trees by sticking togethersimpler tree-level diagrams


NLO bottleneck: 1-loop part

TraditionalDraw all Feynman diagrams with 1loop. Work out formulae for them.

Work hard to reduce integrals toknown forms (+ tricks).

Recursive/unitarity methodsAssemble loop-diagrams from indi-vidual tree-level diagrams.

Build trees by sticking togethersimpler tree-level diagrams

Some main ideas:

Bern, Dixon & Kosower ’93[sewing together trees]

Britto, Cachazo & Feng ’04[on-shell complex loop momenta]

Ossola, Pittau & Papadopoulos ’06[handful of loop momentum choices givefull amplitude]


CDF Wjj: difference wrt MC v. ratio to MC

CDF difference

Dat

a -

MC

(E

vent

s/(8

GeV

/c2 ))

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data

CDF lνjj data (7.3 fb-1)

-150

-100

-50

0

50

100

150

200

100 200

CDF ratio

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data


0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200


Wjj ratio to MC, DØ v. CDF

DØ ratio

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data

D0 (4.3 fb-1)MC = VV, V+j, ttbar, QCD

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200

CDF ratio

Dat

a / M

C

Mjj [GeV/c2]

Data extracted from

CD

F plots w

ith aid of g3data


0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200


Experimental progress on boosted objects


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