Defining jets at the LHC
Gregory Soyez
Brookhaven National Laboratory
in collaboration with G. Salam, M. Cacciari and J. Rojo
arXiv:0704:0292, arXiv:0802:1189, arXiv:0810.1304
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 1
Unavoidable theory
QCD probability for gluon emission (angle θ and ⊥-mom. kt):
dP ∝ αs
dθ
θ
dkt
kt
Two divergences:
θ ≈ 0
collinear
pt
kt ≪ pt
soft
Divergences cancelled by virtual corrections
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 2
Motivation: why QCD?
Lot of QCD in the final-state at the LHC
QCD studies: e.g. t → bqq
new physics:
H → bb
Z ′ → qq
SUSY → QCD
backgrounds: e.g. gg → bb, ...
⇒ Huge effort to compute multileg/NLO processes in pQCD (∼ 100 M$)
This talk: how to avoid wasting that effort, in the optimal way
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 3
Motivation: why jets
Collinear divergence ⇒ QCD produces “jetty” showers
Example: LEP (OPAL) events
2 jets 3 jets
“Jets” ≡ bunch of collimated particles ∼= hard partons
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 4
Motivation: why jets
Collinear divergence ⇒ QCD produces “jetty” showers
“Jets” ≡ bunch of collimated particles ∼= hard partons
BUT
a “parton” is an ambiguous concept (NLO)
“collinear” has some arbitraryness
2 jets 3 jets ? jets
⇒ Different jet definitions
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 4
20th century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 5
20th century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
Idea: undo the showering
Successivelyb find the closest pair of particlesb recombine them
Distance:kt:b di,j = min(k2
t,i, k2t,j)(∆φ2
i,j + ∆y2i,j)
Cam/Aachen:b di,j = ∆φ2
i,j + ∆y2i,j
stop at a distance R
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 5
20th century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
Idea: dominant flow of energy
Stable cone (radius R):sum of particles in the cone pointstowards the cone centre
All these are iterative cones:b start from a seedb iterate until stable
seeds = {particles, midpoints}
blJet ≡ stable coneblmodulo overlapping
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 5
20th century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
Cone with split-merge
Split/merge if the overlap issmaller/larger than a threshold f
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 5
20th century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
Cone with progressive removal
Successivelyb iterate from hardest particleb call that a jet (remove particles)
Basic property:blhard circular jets
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 5
21st century: how does that picture change?
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 6
QCD divergences
Ingredient: QCD soft and collinear divergencies
LO NLO(virt) NLO(real)∞ ∞
∞ (from soft gluons) cancel
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 7
QCD divergences
Ingredient: QCD soft and collinear divergencies
LO NLO(virt) NLO(real)∞ ∞
Consider an extra (NLO) soft gluon
Assume LO gives 2 jets ⇒ NLO(virt) gives 2 jets
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 7
QCD divergences
Ingredient: QCD soft and collinear divergencies
LO NLO(virt) NLO(real)∞ ∞
Consider an extra (NLO) soft gluon
Assume LO gives 2 jets ⇒ NLO(virt) gives 2 jets
NLO(real) gives 2 jets ⇒ ∞ cancel ⇒ finite jet cross-section
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 7
QCD divergences
Ingredient: QCD soft and collinear divergencies
LO NLO(virt) NLO(real)∞ ∞
Consider an extra (NLO) soft gluon
Assume LO gives 2 jets ⇒ NLO(virt) gives 2 jets
NLO(real) gives 2 jets ⇒ ∞ cancel ⇒ finite jet cross-sectionNLO(real) gives 1 jets ⇒ ∞ do not cancel ⇒ infinite jet cross-section
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 7
QCD divergences
Ingredient: QCD soft and collinear divergencies
LO NLO(virt) NLO(real)∞ ∞
For pQCD to make sense, the (hard) jets should not change when
one has a soft emission i.e. adds a very soft gluon
one has a collinear splittingi.e. replaces one parton by two at the same place (η, φ)
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 7
IR (un)safety? JetClu and Atlas Cone
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 8
IR (un)safety? JetClu and Atlas Cone
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
Stable cones found
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 8
IR (un)safety? JetClu and Atlas Cone
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
2 jets 1 jet
A soft gluon changed the number of jets⇒ IR unsafety of JetClu and the ATLAS Cone
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 8
IR (un)safety? JetClu and Atlas Cone
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
2 jets 1 jet
MidPointseed
A soft gluon changed the number of jets⇒ IR unsafety of JetClu and the ATLAS Cone
Fixed by MidPoint
[Blazey et al., 00]
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 8
IR (un)safety? MidPoint
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 9
IR (un)safety? MidPoint
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
Stable cones found
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 9
IR (un)safety? MidPoint
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
2 jets 1 jet
A soft gluon changed the number of jets⇒ IR unsafety of MidPoint (1 order in αs later than JetClu)
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 9
IR (un)safety? MidPoint
-1 0 1 2 30
100
200
300
400pt
φ -1 0 1 2 30
100
200
300
400pt
φ
2 jets 1 jet
missed stable cone
Solution: be sure to find all stable cones
SISCone: Seedless Infrared-Safe Cone algorithmhttp://projects.hepforge.org/siscone
[G.Salam, G.S., 07]
Idea: enumerate enclosures by enumerating pairs of particles
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 9
Collinear (un)safety? the CMS iterative cone
-1 0 1 20
100
200
300
400pt
φ -1 0 1 20
100
200
300
400pt
φ
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 10
Collinear (un)safety? the CMS iterative cone
-1 0 1 20
100
200
300
400pt
φ
1st seed
-1 0 1 20
100
200
300
400pt
φ
1st seed 2nd seed
1 jet 2 jets
A colinear splitting changed the number of jets⇒ Collinear unsafety of the CMS iterative cone
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 10
Anti- kt
Come back to recombination-type algorithms:
dij = min(k2pt,i, k
2pt,j)
(
∆φ2ij + ∆η2
ij
)
p = 1: kt algorithm
p = 0: Aachen/Cambridge algorithm
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 11
Anti- kt
Come back to recombination-type algorithms:
dij = min(k2pt,i, k
2pt,j)
(
∆φ2ij + ∆η2
ij
)
p = 1: kt algorithm
p = 0: Aachen/Cambridge algorithm
p = −1: anti-kt algorithm [M.Cacciari, G.Salam, G.S., 08]
Why should that be related to the iterative cone ?!?
“large kt ⇒ small distance”i.e. hard partons “eat” everything up to a distance R
i.e. circular/regular jets, jet borders unmodified by soft radiation
infrared and collinear safe
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 11
21st century jet finders
Recombination: Cone:kt algorithm
Cambridge/Aachen alg.
anti-kt algorithm
a
CDF JetClu
CDF MidPoint
D0 (run II) Cone
PxCone
ATLAS Cone
CMS Iterative Cone
PyCell/CellJet
GetJet
SISCone
4 availablesafe algorithms
All accessible from FastJethttp://www.fastjet.fr [M.Cacciari, G.Salam, G.S.]
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 12
Physical impact
MidPoint/CMS iterative cone unsafe at O(α4s) (or O(αewα3
s))
IRC-safe until
Physical observable JetClu/ATLAS cone MidPoint/CMS it. cone SISCone/recomb.
Inclusive jet cross section LO NLO any3-jet cross section none LO anyW/Z/H + 2 jet cross sect. none LO anyjet masses in 3 jets none none any
Example: (Midpoint-SISCone)/SISCone
0.00
0.05
0.10
0.15
50 100 150 200
dσm
idpo
int(
1)/d
p t /
dσS
ISC
one/
dpt −
1
pt [GeV]
pp √s = 14 TeV
R=0.7, f=0.5, |y|<0.7Pythia 6.4
(b) hadron-level (with UE)
hadron-level (no UE)
parton-level
Incl. cross-section: a few %
Masses in 3-jet events: ∼ 45%
0 10 20 30 40 50 60 70 80 90 100M (GeV)
0
0.1
0.2
0.3
0.4
0.5
rel.
diff.
for
dσ/d
M2 Mass spectrum of jet 2
midpoint(0) -- SISConeSISCone
NLOJetR=0.7, f=0.5∆ R23 < 1.4
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 13
Physical impact
MidPoint/CMS iterative cone unsafe at O(α4s) (or O(αewα3
s))
IRC-safe until
Physical observable JetClu/ATLAS cone MidPoint/CMS it. cone SISCone/recomb.
Inclusive jet cross section LO NLO any3-jet cross section none LO anyW/Z/H + 2 jet cross sect. none LO anyjet masses in 3 jets none none any
Huge theoretical effort to compute multileg/NLO processesThat can be wasted by using unappropriate tools.
Note: arXiv:0903.0814: W + 2 jets vs. LO QCD using CDF JetClu
arXiv:0903.1748: Z + 2 jets vs. NLO QCD using the D0runII cone
arXiv:0903.1801: Z + 2 jets vs. NLO QCD using the CMS iterative cone
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 13
Filtering using jet substructure
More refined clustering (“3rd generation of algorithms”)
Cambridge+Filtering algorithm:
Cluster with Aachen/Cambridge and radius R
For each jet, recluster it with Aachen/Cambridge and radius Rsub
keep only nsub hardest sub-jets of the initial jet
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 14
Filtering using jet substructure
More refined clustering (“3rd generation of algorithms”)
Cambridge+Filtering algorithm:
Cluster with Aachen/Cambridge and radius R
For each jet, recluster it with Aachen/Cambridge and radius Rsub
keep only nsub hardest sub-jets of the initial jet
Aim: remove the soft background
Properties:
Proven to improve jet reconstruction, in H → bb
[J.Butterworth, A.Davison, M.Rubin, G.Salam, 08]
Additional parameters that deserve appropriate studies
We will use the simplest choice: Rsub = R/2, nsub = 2
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 14
jet definitions = algorithm + parameters
Algorithm: kt, Aachen/Cam., anti- kt, SISCone, filtering?+ parameters: mainly R a
Which one to choose?
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 15
Underlying idea
Competition between
catching perturbative radiation
Out-of-cone radiation:
b 〈δpt〉 ∝ −∫
R
dθ
θ∼ − log(1/R)
not catching soft background radiation (underlying event)
〈δpt〉 ∼ Soft contents ∝ jet area ∼ R2
the coefficients depend on the algorithm
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 16
Jet optimisation study
We analyse 3 processes typical of kinematic reconstructions:
Z ′ → qq →2 jets and H → gg →2 jets:simple environment: identify 2 jets and reconstruct MZ′,H
source of monochromatic quark/gluon jetsscale dependence: mass of the Z′/H varied between 100 GeV and 4 TeVficticious narrow Z′, H
tt → W+bW−b → qqbqqb →6 jets:complex environment: identify 6 jets and reconstruct 2 topbalance between reconstruction efficiency and identification
with
the 5 IRC-safe algorithms: kt, Cambridge, anti-kt, SISCone, Cam+filtering
jet radius varied between 0.1 and 1.5
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 17
Reconstruction quality (1)
Measure of the jet reconstruction efficiency:
Forget about measures related to parton-jet matching
Forget about fits depending on the shape of the peak
⇒ maximise the signal over background ratio (S/√
B)a narrower peak is better.
1/N
dN
/dbi
n
dijet mass [GeV]
0
0.01
0.02
0.03
0.04
0.05
80 100 120
kt, R=1.0
Qwf=0.12 = 13.0 GeV
dijet mass [GeV]
80 100 120
kt, R=0.5
Qwf=0.12 = 8.3 GeV
qq 100 GeV
dijet mass [GeV]
80 100 120
SISCone, R=0.5, f=0.75Qw
f=0.12 = 7.4 GeV
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 18
Reconstruction quality (2)
Assuming a constant background,
quality measure −→ effective luminosity ratio
ρL(JD2/JD1) =L needed with JD2
L needed with JD1
=Qw
f=z(JD2)
Qwf=z(JD1)
e.g. ρL(JD2/JD1) = 2
⇔ JD2 requires 2 times the integrated luminosity of JD1
⇔ to achieve the same discriminative power.
Note: results cross-checked with 2 different definitions of the quality measure
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 19
Best choices
5
10
15
20
25
30
35
100
150 200
300
500 700
1000
2000
4000
Bes
t Qw f=
0.12
(G
eV)
M (GeV)
ktCam/Aa
anti-ktSISCone
C/A-filt
0.4
0.6
0.8
1
1.2
1.4
100
150 200
300
500 700 1000
2000
4000
Bes
t R (
from
Qw f=
0.12
)
M (GeV)
ktCam/Aa
anti-ktSISCone
C/A-filt
SISCone and Cam+filtering perform better
Rbest strongly depends on the mass
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 20
Quarks vs. gluons
5
10
15
20
25
30
35
100
150 200
300
500 700
1000
2000
4000
Bes
t Qw f=
0.12
(G
eV)
M (GeV)
ktCam/Aa
anti-ktSISCone
C/A-filt
0.4
0.6
0.8
1
1.2
1.4
100
150 200
300
500 700 1000
2000
4000
Bes
t R (
from
Qw f=
0.12
)
M (GeV)
ktCam/Aa
anti-ktSISCone
C/A-filt
10 20 30 40 50 60 70 80 90
100 110
100
150 200
300
500 700 1000
2000
4000
Bes
t Qw f=
0.13
(G
eV)
M (GeV)
gg
ktCam/Aa
anti-ktSISCone
C/A-filt
0.4
0.6
0.8
1
1.2
1.4
100
150 200
300
500 700 1000
2000
4000
Bes
t R (
from
Qw f=
0.13
)
M (GeV)
gg
ktCam/Aa
anti-ktSISCone
C/A-filt
Same conclusions for gluon jets with slightly larger R
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 21
Luminosity ratios
1
1.2
1.4
1.6
1.8
2
2.2
0.4 0.6 0.8 1 1.2 1.4
ρL
R
gg, 2 TeV
(kt,R) vs. (SISCone,Rbest)
Mandatory at the LHC:Not choosing the best alg.AND R can be very costlyfor new discoveries
Note: typical choice, R ∼ 0.5
1
1.2
1.4
1.6
1.8
2
2.2
0.4 0.6 0.8 1 1.2 1.4
ρL
R
gg, 2 TeV
(SISCone,R) vs. Best
best
100 GeVbest
1
1.2
1.4
1.6
1.8
2
2.2
0.4 0.6 0.8 1 1.2 1.4
ρL
R
qq, 100 GeV
(SISCone,R) vs. Best
best 2 TeVbest
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 22
Conclusions
New jet algorithms available
JetCluATLAS Cone
MidPointIterative Cone
SISCone
Anti-kt
X as fastX IRC safe
X regularX IRC safe
important for precision at the LHC!
Early discovery may rely on an optimal choice of a jet definition
SISCone and Camb/Aachen+filtering slightly preferred
Strong dependence on R: larger scales ↔ larger R
Available from FastJet (or SpartyJet)Check http://quality.fastjet.fr for interactive plots
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 23
Backup slides
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 24
Speed
0.001
0.01
0.1
1
10
100 1000 10000
run
time
(s)
N
CDF midpoint (s=0 GeV)
CDF midpoint (s=1 GeV)
KtJet
SISConekt (FastJet)
anti-kt (FastJet)
Recombination algorithms very fast [M. Cacciari, G. Salam, 06]
SISCone not slower than Midpoint (even with a 1 GeV seed threshold)
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 25
Optimisation - more results
1.0
1.5
2.0
ρ L
kt
ρ L fr
om Q
w f=z
C/A anti-kt SISCone
qq 100 GeV
C/A-filt
1.0
1.5
2.0
ρ L
qq 2 TeV
1.0
1.5
2.0
ρ L
gg 100 GeV
1.0
1.5
2.0
ρ L
gg 2 TeV
1.0
1.5
2.0
0.5 1.0 1.5
ρ L
R
0.5 1.0 1.5
R
0.5 1.0 1.5
R
0.5 1.0 1.5
R
0.5 1.0 1.5
top in tt
RGregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 26
Need for subtraction
Pileup ≈ uniform soft background that shifts jets to higher pt
0
0.005
0.01
0.015
0.02
60 80 100 120 140
1/N
dN
/dm
(G
eV-1
)
reconstructed Z’ mass (GeV)
MZ’=100 GeV
kt, R=Rbest
no PUlow-lumi PU
high-lumi PU
... that needs to be subtracted!
⇒ Using jet areas!
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 27
Pileup subtraction
Basic idea: [M.Cacciari, G.Salam, 08]
pt,subtracted = pt,jet − ρpileup × Areajet
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 28
Pileup subtraction
Basic idea: [M.Cacciari, G.Salam, 08]
pt,subtracted = pt,jet − ρpileup × Areajet
Jet area: [M.Cacciari, G.Salam, G.S., 08]
region where the jet catches infinitely soft particles (active/passive)
tractable analytically in pQCDExample: area corrections from QCD radiation
〈A(pt,1, R)〉 = A1 parton(R) +CF,A
πb0
log
(
αs(Q0)
αs(Rpt)
)
πR2 d
area 6= πR2
area scaling violations
d passive active
kt 0.5638 0.519
Cam 0.07918 0.0865
SISCone -0.06378 0.1246
anti-kt 0 0
just a shift
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 28
Pileup subtraction
Basic idea: [M.Cacciari, G.Salam, 08]
pt,subtracted = pt,jet − ρpileup × Areajet
Jet area: [M.Cacciari, G.Salam, G.S., 08]
region where the jet catches infinitely soft particles (active/passive)
tractable analytically in pQCD
Pileup density per unit area: ρpileup
e.g. estimated from the mediane.g. of pt,jet/Areajet
0
5
10
15
20
25
30
35
-4 -2 0 2 4
Pt,j
et /
Are
a jet
η
median
implemented in FastJeton an event-by-event basis
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 28
Subtraction at work
0
0.005
0.01
0.015
0.02
60 80 100 120 140
1/N
dN
/dm
(G
eV-1
)
reconstructed Z’ mass (GeV)
MZ’=100 GeV
kt, R=Rbest
no PUlow-lumi PU
high-lumi PU
0
0.005
0.01
0.015
0.02
60 80 100 120 140
1/N
dN
/dm
(G
eV-1
)
reconstructed Z’ mass (GeV)
MZ’=100 GeV
kt, R=0.5
no PUlow-lumi PU
high-lumi PU
subtractionblablablablabla
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 29
Optimisation - pileup
1.0
1.5
2.0
2.5
ρ L
kt
PU(0.25
)
PU-s
ubno
PU
C/A anti-kt SISConeqq 2 T
eVC/A-filt
1.0
1.5
2.0
2.5
ρ L
gg 100 GeV
1.0
1.5
2.0
2.5
0.5 1.0 1.5
ρ L
R
0.5 1.0 1.5
R
0.5 1.0 1.5
R
0.5 1.0 1.5
R
0.5 1.0 1.5
top in tt
R
Gregory Soyez LHC@BNL, BNL, Upton, NY, USA, March 16 2009 Jets at the LHC – p. 30