Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä...

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Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008

Transcript of Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä...

Page 1: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

Lecture IV: Jet finding techniques and results

Marco van LeeuwenUtrecht University

Jyväskylä Summer School 2008

Page 2: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Parton energy from -jet and jet reconstruction

Qualitatively:

)/()( , jethadrTjetshadrT

EpDEPdEdN

dpdN

`known’ from e+e-knownpQCDxPDF

extract

Full deconvolution large uncertainties (+ not transparent)

Fix/measure Ejet to take one factor out

Two approaches: -jet- Jet reconstruction

Second-generation measurements at RHIC – first generation at LHC?

Page 3: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Perturbative QCD processes

• Hadron production• Heavy flavours• Jet production

– e+e- → jets – p(bar)+p → jets

• Direct photon production

Measurem

ent difficulty

The

ory

diff

icul

ty

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Fixing the parton energy with -jet eventsT. Renk, PRC74, 034906

-jet: know jet energy sensitive to P(E)

RAA insensitive to P(E)

Nuclear modification factor

Away-side spectra in -jet

E = 15 GeV

Away-side spectra for -jet are sensitive to P(E)

Input energy loss distribution

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-jet in Au+Au

Use shower shape in EMCal to form 0 sample and -rich sample

Combinatorial subtraction to obtain direct- sample

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STAR Preliminary

IAA(zT) =DAA (zT)

Dpp (zT)

Direct- recoil suppression

Large suppression for away-side: factor 3-5

Results agree with model predictions

Uncertainties still sizable Some improvements expected for final resultsFuture improvements with increased RHIC luminosity

J. Frantz, H

ard Probes 2008

A. H

amed, H

ard Probes 2008

8 < ET, < 16 GeV

ET,

2 < pTassoc < 10 GeV

Page 7: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Jet reconstruction algorithms

Two categories of jet algorithms:

• Sequential recombination kT, anti-kT, Durham

– Define distance measure, e.g. dij = min(pTi,pTj)*Rij

– Cluster closest

• Cone– Draw Cone radius R around starting point

– Iterate until stable ,jet = <,>particles

For a complete discussion, see: http://www.lpthe.jussieu.fr/~salam/teaching/PhD-courses.html

Sum particles inside jet Different prescriptions exist, most natural: E-scheme, sum 4-vectors

Jet is an object defined by jet algorithmIf parameters are right, may approximate parton

Page 8: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Collinear and infrared safetyIllustration by G

. Salam

Jets should not be sensitive to soft effects (hadronisation and E-loss)

- Collinear safe- Infrared safe

Page 9: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Collinear safety

Note also: detector effects, such as splitting clusters in calorimeter (0 decay)

Illustration by G. S

alam

Page 10: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Infrared safety

Infrared safety also implies robustness against soft background in heavy ion collisions

Illustration by G. S

alam

Page 11: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Clustering algorithms – kT algorithm

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kT algorithm

• Calculate – For every particle i: distance to beam

– For every pair i,j : distance

• Find minimal d

– If diB, i is a jet

– If dij, combine i and j

• Repeat until only jets

Various distance measures have been used, e.g. Jade, Durham, Cambridge/Aachen

Current standard choice:

2,itiB pd

2

22,

2, ),min(

R

Rppd ij

jtitij

Page 13: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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kT algorithm demo

Page 14: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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kT algorithm properties

• Everything ends up in jets• kT-jets irregular shape

– Measure area with ‘ghost particles’

• kT-algo starts with soft stuff– ‘background’ clusters first, affects jet

• Infrared and collinear safe• Naïve implementation slow (N3). Not necessary

Fastjet

Alternative: anti-kT

2,

1

itiB pd

2

2

2,

2,

1,

1min

R

R

ppd ij

jtitij

Page 15: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Cone algorithm

• Jets defined as cone• Iterate until stable:

(,)Cone = <,>particles in cone

• Starting points for cones, seeds, e.g. highest pT particles

• Split-merge prescription for overlapping cones

Page 16: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Cone algorithm demo

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IR safety is subtle, but important

G. S

alam, arX

iv:0906.1833

Page 18: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Seedless cone

Limiting cases occur when two particles are on the edge of the cone

1D: slide cone over particles and search for stable coneKey observation: content of cone only changes when the cone boundary touches a particle

Extension to 2D (,)

Page 19: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Split-merge procedure

• Overlapping cones unavoidable• Solution: split-merge procedure

Evaluate Pt1, Pt,shared

– If Pt,shared/Pt1> f merge jets

– Else split jets (e.g. assign Pt,shared to closest jet or split Pt,shared according to Pt1/Pt2)

Jet1 Jet2

Merge: Ptshared large fraction of Pt1

Jet1 Jet2

Split: Ptshared small fraction of Pt1

f = 0.5 … 0.75

Page 20: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Note on recombination schemes

ET-weighted averaging:Simple

Not boost-invariant for massive particles

Most unambiguous scheme: E-scheme, add 4-vectors

Boost-invariantNeeds particle masses (e.g. assign pion mass)Generates massive jets

Page 21: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Current best jet algorithms

• Only three good choices:– kT algorithm (sequential recombination, non-

circular jets)– Anti-kT algoritm (sequential recombination, circular

jets)– SISCone algorithm (Infrared Safe Cone)

+ some minor variations: Durham algo, differentcombination schemes

These are all available in the FastJet package:http://www.lpthe.jussieu.fr/~salam/fastjet/

Really no excuse to use anything else (and potentially run into trouble)

Page 22: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Speed matters

At LHC, multiplicities are largeA lot has been gained from improving implementations

G. S

alam, arX

iv:0906.1833

Page 23: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Relating jets and single hadrons

High-pT hadrons from jet fragmentation

Qualitatively: )/( ,, jetThadrT

jetsThadrT

ppDdpdN

dpdN

Single hadrons are suppressed:

- Suppression of jet yield (out-of-cone radiation) RAAjets < 1

- Modification of fragment distribution (in-cone radiation) softening of fragmentation function and/or broadening of jet structure

Page 24: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Jet finding in heavy ion events

η

p t p

er g

rid c

ell [

GeV

]

STAR preliminary~ 21 GeV

FastJet:Cacciari, Salam and Soyez; arXiv: 0802.1188http://rhig.physics.yale.edu/~putschke/Ahijf/A_Heavy_Ion_Jet-Finder.html

Jets clearly visible in heavy ion events at RHIC

Use different algorithms to estimate systematic uncertainties:• Cone-type algorithms

simple cone, iterative cone, infrared safe SISCone

• Sequential recombination algorithmskT, Cambridge, inverse kT

Combinatorial backgroundNeeds to be subtracted

Page 25: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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p+p Au+Au central

STAR Preliminary

Jet spectra

STAR Preliminary

Note kinematic reach out to 50 GeV

• Jet energy depends on R, affects spectra• kT, anti-kT give similar results

Take ratios to compare p+p, Au+Au

Page 26: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Jet RAA at RHIC

Jet RAA >> 0.2 (hadron RAA)

Jet finding recovers most of the energy loss measure of initial parton energy

M. P

loskon, ST

AR

, QM

09

Some dependence on jet-algorithm? Under study…

Page 27: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Radius dependence

RAA depends on jet radius:Small R jet is single hadron

M. P

loskon, ST

AR

, QM

09

Jet broadening due to E-loss?

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Fragmentation functions

STAR Preliminary

pt,rec(AuAu)>25 GeV20<pt,rec(AuAu)<25 GeV

Use recoil jet to avoid biases

Suppression of fragmentation also small (>> 0.2)

E. B

runa, ST

AR

, QM

09

Page 29: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Di-jet spectra

29

Ele

na B

run

a fo

r the S

TA

R C

olla

bora

tion

- Q

M0

9STAR PreliminarySTAR Preliminary

E. B

runa, ST

AR

, QM

09

Jet IAA

Away-side jet yield suppressed partons absorbed

... due to large path lentgh(trigger bias)

Page 30: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Emerging picture from jet results

• Jet RAA ~ 1 for sufficiently large R – unbiased parton selection

• Away side jet fragmentation ummodified – away-side jet emerges without E-loss

• Jet IAA ~ 0.2 – Many jets are absorded (large E-loss)

Study vs R, E to quantify P(E) and broadening

Page 31: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Modeling in-medium fragmentation

From C. Salgado

Page 32: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Sudakov prescription

From C. Salgado

Page 33: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Sudakov prescription

From C. Salgado

Page 34: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Sudakov MC implementation

Used by most MC event generators (PYTHIA, HERWIG)

From C. Salgado

Page 35: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Full MC event

From C. Salgado

Page 36: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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MC resultsQ-PYTHIA

N. A

rme

sto e

t al, a

rXiv:0

90

7.1

01

4

Softening of fragmentation(pT-spectra)

Broadening

Caveat: all plot are parton-level. Effect of hadronisation may be large

Page 37: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Summary

• Jet-finding, -jet to fix parton energy Sensitivity to P(E), jet broadening

• -hadron results agree with predictionNeed more statistics for P(E)

• Jet-algorithm requirements: Infrared and Collinear safe

• Jet results from RHIC:– Can recover full parton energy (R=0.4)– Indicate large broadening

– Away-side jet IAA ~ 0.2, jet absorption?

• Full event MC genartors are being developed important reference/benchmark for jet-analyses

Page 38: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Extra slides

Page 39: Lecture IV: Jet finding techniques and results Marco van Leeuwen Utrecht University Jyväskylä Summer School 2008.

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Direct- recoil yields

A. H

amed, H

ard Probes 2008

Run 4 p+p/Au+Au @ 200 GeV

M. N

guyen, Quark M

atter 2006

Direct-–jet measurements being pursued by STAR and PHENIXRequires large data samples

Suppression of away-side yield visible

Similar to di-hadrons, but now with selected parton energy