Perturbative QCD in hadron collisions - ICTP – SAIFRSome of what goes into collider predictions...

Perturbative QCD in hadron collisions

Gavin Salam

CERN, LPTHE/CNRS (Paris) & Princeton University

IX Latin American Symposium on High Energy Physics (SILAFAE 2012)Sao Paolo, Brazil, 10–14 December 2012

An exciting past 24 months

Higgs(-like) discovery

tt asymmetry

W + dijet CDF anomaly

Exclusion of swathes of SUSY, etc.

. . .

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) Perturbative QCD in hadron collisions SILAFAE 2012-12-10 2 / 35

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.


What a perturbative series should look like

E.g. QCD corrections to e+e− → hadrons cross section:

R = 1 + 0.32αs + 0.14α2s − 0.41α3

s − 0.82α4s

keep in mind αs(mZ ) ≃ 0.118


What it looks like at hadron colliders

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

1 + 2αs looks like a reasonable series




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

1 + C × αs, with quite large C ≃ 5

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 −→ C = 50 ?!! Often driven by new topologies


The NLO revolutionand 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

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]1991: NLO gg → Higgs [Dawson; Djouadi, Spira & Zerwas]

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]1988: NLO dijets [Aversa et al]1993: 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]2011/12: NLO WWjj [Rocket: Melia et al; GoSaM+MadX Greiner et al] [unitarity]2011: NLO Z+4j [BlackHat+Sherpa: Ita et al] [unitarity]2011/12: NLO 4j [BlackHat/NGluons+Sherpa: Bern et al; Badger 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

Example of widelyused data-drivenbkgd estimates

Combine best oftheory knowledgewith best of exper-imental knowledge.


Merging NLO and showersand the CDF W + dijet anomaly


Remember the CDF W+dijet excess?

]2 [GeV/cjjM100 200

)2E

vent

s/(8

GeV

/c

0

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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, extending their applicabilitye.g. MENLOPS, MINLO, FxFx merging, Sherpa merging, UNLOPS, . . .

One 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

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

100 200



]2 [GeV/cjjM100 200

)2E

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]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

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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

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100 200

aMC@NLOuncertainties: −→−→−→



]2 [GeV/cjjM100 200

)2E

vent

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/c

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]2 [GeV/cjjM100 200

)2E

vent

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GeV

/c

0

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200

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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, (tt)

✗ 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


Most groundbreaking new NNLO calculation of past years:

qq → tt

Baernreuther, Czakon and Mitov 2012

First NNLO calculation with coloured particles in the initialand final state. Its new techniques may help open the way

to many other important NNLO calculations.


LO, NLO , NNLO res

Baernreuther, Czakon & Mitov NNLO qq → tt cross-section

NNLO: yet not always reassuring

New in 2011: NNLO γγ

LO

NLO

NNLO

Catani, Cieri, de Florian, Ferrera & Grazzini

Some key processes see large orgiant NLO/NNLO corrections.

Can’t help but wonder if we’remissing something,

especially in the gg → H case.


One series that’s ugly: gluon fusion Higgs cross section

For 8 TeV pp collisions, mH = 125 GeV:

σgg→H = 6.8 pb(

1 + 9.9αs + 36α2s + · · ·

)

= 6.8 pb (1 + 1.23 + 0.56 + · · · ) = 19.0 pb

for µR = µF = 12mH , αs(µR) = 0.124

σgg→H = 5.6 pb(

1 + 11.4αs + 63α2s + · · ·

)

= 5.6 pb (1 + 1.27 + 0.79 + · · · ) = 17.2 pb

for µR = µF = mH , αs(µR) = 0.112

There are explanations: threshold logarithms, π2 terms from analyticcontinuation. A problem is perhaps that there are too many explanations. . .

Baglio & Djouadi have raised the convergence issue before


Consequences of a bad series

Everything else you try about (gluon-fusion) Higgs production suffers as aresult of the original bad series: e.g. jet veto efficiency

FIXED ORDER PREDICTION

ε(p

t,ve

to)

pt,veto [GeV]

Higgs production (mH = 125 GeV), NNLO

pp, 7 TeVmH/4 < µR,F < mH

MSTW2008 NNLO PDFsanti-kt, R = 0.5

scheme a

scheme b

scheme c

0

0.2

0.4

0.6

0.8

1

10 100


Consequences of a bad series

Everything else you try about (gluon-fusion) Higgs production suffers as aresult of the original bad series: e.g. jet veto efficiency

FIXED ORDER PREDICTION

ε(p

t,ve

to)

pt,veto [GeV]

Higgs production (mH = 125 GeV), NNLO

pp, 7 TeVmH/4 < µR,F < mH

MSTW2008 NNLO PDFsanti-kt, R = 0.5

scheme a

scheme b

scheme c

0

0.2

0.4

0.6

0.8

1

10 100

RESUMMED PREDICTION

ε(p t

,vet

o)

gg → H, mH = 125 GeV

NNLO

NNLL+NNLO

HqT-rescaled POWHEG + Pythia 0.2

0.4

0.6

0.8

1

pp, 8 TeVmH /4 < µR,F , Q < mH , schemes a,b,cMSTW2008 NNLO PDFsanti-kt, R = 0.5Pythia partons, Perugia 2011 tune

ε(p t

,vet

o) /

ε cen

tral

(pt,v

eto)

pt,veto [GeV]

0.8

0.9

1

1.1

1.2

10 20 30 50 70 100

Banfi, Monni, GPS & Zanderighi ’12

see also Becher & Neubert ’12Gavin Salam (CERN) Perturbative QCD in hadron collisions SILAFAE 2012-12-10 25 / 35

Looking at data differently


H → bb (57% of decays) v. hard to see

Best hope is pp → W±H (and ZH), W±→ ℓ±ν, H → bb.

e,µ

b

νb

H

W




pp → WH → ℓνbb + bkgds

ATLAS TDR 1999

Conclusion (ATLAS TDR):

“The extraction of a signal from H → bbdecays in the WH channel will be verydifficult at the LHC, even under the mostoptimistic assumptions [...]”

Low efficiency, huge backgrounds, e.g. tt

NB: Evidence of this channel seen recently

at Tevatron, but similar difficulties

e,µ

b

νb

H

W




pp → WH → ℓνbb + bkgds

ATLAS TDR 1999

Conclusion (ATLAS TDR):

“The extraction of a signal from H → bbdecays in the WH channel will be verydifficult at the LHC, even under the mostoptimistic assumptions [...]”

Low efficiency, huge backgrounds, e.g. tt

Analysis of signal/bkgd suggests:

◮ Go to high pt (ptH , ptW > 200 GeV)◮ Lose 95% of signal, but more efficient?◮ Maybe kill tt & gain clarity?

W

H

bb

e,µ ν


pp → ZH → ννbb, @14TeV, mH=115GeV

Herwig 6.510 + Jimmy 4.31 + FastJet 2.3

Cluster event, C/A, R=1.2

Butterworth, Davison, Rubin & GPS ’08

also earlier work by Seymour; Butterworth et al




Fill it in, → show jets more clearly






Consider hardest jet, m = 150 GeV






split: m = 150 GeV, max(m1,m2)m

= 0.92 → repeat






split: m = 139 GeV, max(m1,m2)m

= 0.37 → mass drop






check: y12 ≃pt2pt1

≃ 0.7 → OK + 2 b-tags (anti-QCD)






Rfilt = 0.3






Rfilt = 0.3: take 3 hardest, m = 117 GeV






Rfilt = 0.3: take 3 hardest, m = 117 GeV




ATLAS and CMS H → bb are high-pt, but 2-jet based


Some taggers and jet-substructure observables

Jet Declustering

Jet Shapes

Matrix−Element

Seymour93

YSplitter

Mass−Drop+Filter

JHTopTagger TW

CMSTopTagger

N−subjettiness (TvT)

CoM N−subjettiness (Kim)

N−jettiness

HEPTopTagger(+ dipolarity)

Trimming

Pruning

Planar Flow

Twist

ATLASTopTagger

Templates

Shower Deconstruction

Qjets

EEC

Multi−variate tagger

apologies for omitted taggers, arguable links, etc.

[NB: many of the tools available in FastJet & SpartyJet]


Handles for distinguishing signal v. background

their colour (q v. g)

radiation offprongs sensitive to

z

(1−z)

boosted X

softer prong mom. fraction z

radiation off X sensitive to its colour charge

large−angle (>> 2m/pt)

g→gg(g) q→qg(g) g→bb H

→bb t→qqq

softer prong z soft soft hard hard hard

prong colour factors 2×CA CF+CA 2×CF 2×CF 3×CF

system colour factor CA CF CA 0 CF


Boosted Ws and tops in single jets: data!

W’s in a single jet

with Pruning + Mass Drop requirement

NB: combined in IR unsafe way. . .

tops in a single jet

with HEPTopTagger


Some BSM searches with jet-substructure techniques

A range of techniques being used for varied BSM scenarios


Closing


0

0.2

0.4

0.6

0.8

1fr

act

ion

of A

TL

AS

& C

MS

pa

pe

rs th

at ci

te th

em Papers commonly cited by ATLAS and CMS

as of 2012−06−28, from ’papers’, excluding self−citations

Plo

t b

y G

P S

ala

m b

ase

d o

n d

ata

fro

m A

TL

AS

, C

MS

an

d IN

SP

IRE

HE

P

Pyt

hia

6.4

MC

GE

AN

T4A

nti−

k t je

t alg

.C

TEQ

6 P

DFs

Her

wig

6 M

CA

LPG

EN

CTE

Q6.

6 P

DFs

MS

TW20

08 P

DFs

MC

@N

LOJI

MM

YR

PP

2010

LO*

PD

FsP

OW

HE

G (2

007)

Mad

Gra

ph4

MC

@N

LO h

eavy

−fla

vour

Fast

Jet

Her

wig

++ M

CC

T10

PD

FsFE

WZ

NN

LOC

L(s)

tech

niqu

eLH

C M

achi

neZ1

UE

Tun

eP

ythi

a 8.

1P

DF4

LHC


0

0.2

0.4

0.6

0.8

1fr

act

ion

of A

TL

AS

& C

MS

pa

pe

rs th

at ci

te th

em Papers commonly cited by ATLAS and CMS

as of 2012−06−28, from ’papers’, excluding self−citations

Plo

t b

y G

P S

ala

m b

ase

d o

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fro

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GE

AN

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Her

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6 M

CA

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Q6.

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MS

TW20

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DFs

MC

@N

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MM

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2010

LO*

PD

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Mad

Gra

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LO h

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Fast

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Her

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T10

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LHC

QCD

today’s progress in QCD = tomorrow’s workhorse


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


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

ATLAS

CMS

Pyt

hia

6.4

MC

GE

AN

T4

Ant

i-kt j

et a

lg.

CT

EQ

6 P

DF

s

MS

TW

2008

PD

Fs

CT

EQ

6.6

PD

Fs

Her

wig

6 M

C

RP

P20

10

ALP

GE

N

LO*

PD

Fs

MC

@N

LO

JIM

MY

Mad

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EG

(20

07)

FE

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eavy

-fla

vour

Her

wig

++

MC

Fas

tJet

Z1

UE

Tun

e

Pyt

hia

8.1


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