jet performance in run2 at cms - uzh - physik-institutgrauco/boost16.pdf · jet performance in run2...

Jet Performance in Run2 at CMS

Jet reconstruction at CMSp

Silicon tracker

Electromagnetic calorimeter

Hadron calorimeter

Particle-Flow algorithm

identifies and reconstructseach particle by combining the

information from all thesubdetectors

Jet Algorithm(Anti-kT)

Particles, CaloTowers,PF, Tracks

GenJets,CaloJets, PFJets

Giorgia Rauco (University of Zurich) 2 / 14 BOOST 2016


Jet energy correctionsp

arXiv:1607.03663, CMS DP-2016/020

correct reconstructed jets back to particle level

L1(Pile-Up)Reconstructed jet

L2L3(pT ,η)

L2L3Residuals

(pT ,η)Calibrated jet

factorized approach:

1 L1: correction for average offset-energy from pile-up

2 L2L3: correction for (η,pT ) dependence of jet response

3 L2L3Residuals: correction for residual data-simulation differences

• applied on data only

New in Run2: PileUp Per Particle Identification (PUPPI), which assigning weights to PFparticle depending on the weighted pT sum of the particles surrounding it



Pile-up offset correctionspp

L1

(Pile-Up)Reconstructed jet

L2L3(pT ,η)

L2L3Residuals


100mm10mm,0.2

• hard jets from overlapping low-pT PU jets

real jet pile-up jet

• overall increase of the jet energy• corrected with hybrid jet area method

• data/simulation scale factors areextracted

• from Zero Bias data• with the Random Cone methodORC 〈η,〈ρ〉〉= 〈pT ,cone〉 [η,µ]

Zero Bias event



Simulated response correctionspp


L2L3

(pT ,η)

L2L3Residuals


100mm10mm,0.2MC truth corrections derived from QCD dijet events

• jet pT misreconstruted

• reco-level and gen-level jets are matched

• response defined in bin of pT ,ptcl and η as:

R(〈pT ,reco 〉 ,η) =〈pT ,reco 〉〈pT ,ptcl 〉

[pT ,ptcl ,η]

gen-jet

reco-jet

• stable response in barrelobtained

• stronger pT-dependence inendcaps and HF

• overall improvements from Run1in HF calibration thanks to HFdetector upgrade



Residual corrections with datapp


L2L3(pT ,η)

L2L3

Residuals


100mm10mm,0.2residuals data/MC scale factors for the dependency of the jet response:

100mm10mm,0.2

1. relative η-dependent corrections

• back-to-back dijets events(tag jet in the barrel, probe jet free to scan

the whole detector)

• response of probe jet relative totag jet(calibrate the response of a jet at a given η

to the one for jets in |η|<1.3)

good description of relative responsescale within tracker coverage





L2L3(pT ,η)

L2L3

Residuals



100mm10mm,0.2

2. absolute pT-dependent corrections

• pT -balance and ~/ET Projection

Fraction methods used

• a constant correction is derivedusing Z(µµ) + jet events

• response from multiple channels(γ/Z+jet and multijets) arecombined in a global fit





L2L3(pT ,η)

L2L3

Residuals



100mm10mm,0.2






pT -balance

γ,Z events: jet fully captures parton thatbalances reference object

Rabs =pjetT

pγ,ZT

dijet events: tag (central jet) and probeapproach

Rrel =2+〈B〉2−〈B〉

where B =pprobeT −ptagT

2





L2L3(pT ,η)

L2L3

Residuals



100mm10mm,0.2






MPF

~/ET solely due to jet mismeasurements

~pTγ,Z + ~pT

recoil = 0Rγ,Z ~pT

γ,Z +Rrecoil ~pTrecoil = −~/ET

Rrecoil = Rγ,Z +~/ET· ~pT

γ,Z

( ~pTγ,Z )2

≡ RMPF





L2L3(pT ,η)

L2L3

Residuals



100mm10mm,0.2






jet response ∼0.98 at low pT and∼1 at higher pT



Jet energy correction Uncertaintiesp

• classified in four broadcategories

1 pileup offset2 η-relative calibration of jet

energy scale3 pT -relative calibration of jet

energy scale:

most important at high pT4 jet flavour response5 (time dependence)

• Pileup uncertainty dominantbelow 50 GeV

• Other important uncertainties:1 absolute scale within |η| <32 relative scale at |η| >3



Jet energy resolutionp

jet pT resolution:

width of response distributionJER = σ

(pT ,recopT ,ptcl

)extracted from MC simulation:

pT -asymmetry in dijet and pT -balancing in γ/Z + jets

resolution stable against pileup above jet pT =100 GeV andbetter than 10% (5%) resolution above 100 GeV (1 TeV)



Missing Transverse Energyp

CMS-JME-13-003, CMS DP-2016/017

Missing Transverse Energy (MET):

1 measure of momentum imbalance in the transverse plane

2 used to detect particles who don’t leave a signal in the detector (i.e. neutrinos)

3 crucial role in many physical analysis (i.e. SUSY and DM searches)

4 ~/ET = −∑~pT, sum over all observed final-state particles

(→ equal to the total ~pT of unobserved particles)



Scale and resolution measurementsp

Z /γ + jets events exploited:

• no genuine ~/ET is contained

• ~pT-balance between the vector boson and thehadronic system

• vector boson used as reference→measurescale and resolution of ~/ET

q̄ ′

q l−

l+

γ/Z

Z → e+e− Z → µ+µ− γ + jets



Resolutionp

~/ET resolution:

• geometrical approach used

• parametrization of the paralelland perpendicular recoils

~pT(γ/Z)

~/ET

~uT

u⊥

u||

parallel recoil perpendicolar recoil

• the resolutionincreases withincreasing pT

• the data and thesimulation curvesare in reasonableagreement foreach channel



Resolution with PUPP~/ETp

see Satoshi Hasegawa’s talk @BOOST2015 and CMS-DP-2015-034

PUPP~/ET: missing transverse energy (MET) determination using inputparticles from PUPPI algorithm

PUPPI provides better resolution, and it is stable with respect to pileup



Responsep

• ~/ET response is defined as themean of the parallel recoilcomponent of the recoil over theboson pT , −〈u||〉 /qT

• agreement between data andsimulation is reasonable for eachchannel

• ~/ET is fully able to recover thehadronic recoil activity from∼ 40 GeV



Conclusionsp

• latest jet energy scale and resolution measurement have beenpresented

• pile-up offset corrections from QCD dijet simulation• simulated jet response corrections extracted in function of η and T

determined from simulation• residual differences between data and simulation have been taken into

account too

• ~/ET scale and resolution have been measured• data agree with the expectations from the simulation

we can get the same performance with 25ns LHC running thanwe had with 50ns in Run 1



Questions?p

• Why is there a step in the absolutepT -dependent JEC?

• → Still under investigation. Most likelydue to HCAL noise rejectionpT -dependence for 25 ns out-of-timepile-up rejection.

• Why is there a bump in the JECuncertainties at about 150 GeV?

• → See previous answer.

• What about jet mass scale and jet massresolution?

• → Not approved in time. Hopefully forICHEP.

• Systematics?• →Work in progress.



ADDITIONAL MATERIAL



Random-Cone Methodp

the offset data/simulation scale factor is estimated from Zero Bias (ZB) dataand simulation using the Random Cone method

ZB has no energy deposition from hard interactions, so the averagetransverse momentum 〈pT ,cone〉(η) of particles in a randomly placed cone

centered at (η,φ) can be identified with the average offset due to pileup,ORC (η):

O(η,〈ρ〉) = 〈pT ,cone 〉 [η,µ]

For deriving the offset scale factor, the Random Cone measurement is fittedwith a quadratic function of ρ:

ORC = p0ρp1 + ρ2p2

finally, the offset scale factor is defined as:

SF =OdataRC (η,〈ρ〉)OMCRC (η,〈ρ〉)



Hybrid Jet Area Methodp

it uses the effective area of the jets multiplied by the average energy densityin the event to calculate the offset energy to be subtracted from the jets

Tevatron Method

• average pT in a jet cone due topile-up

• η-dependent average offset O(η)correction versus NPV

Coffset (NPV ,η,Eraw ) = 1− (NPV −1)OE (η)Eraw

Jet Area Method

• average pT density per unit jetarea

• it only uses ρ and Aj• η-independent

Coffset (ρ,Aj ,pT ,raw ) = 1−(ρ−ρUE )·Aj

pT ,raw

the Hybrid Jet Area Method imports η-dependence from Tevatron methodinto Jet Area Method

Chybrid (pT ,uncorr ,η,Aj ,ρ) = 1− [ρ0(η)+ρ·βη·(1+γ(η)·log(pT ,uncorr))]·AjpT ,uncorr



pT balancing and asymmetry methodsp

pT balancing

(for γ/Z events)

σ

pjet ,recoTpγ,recoT

= σ

pjet ,recoTpjet ,ptclT

⊕ σ p

jet ,ptclTpγ,partT

⊕ σ pγ,partT

pγ,recoT

σB = σpT

pT⊕ σUE+OOC+ISR+FSR ⊕ σgamma

after extrapolating the secondary jet activityto zero the effects of ISR and FSR become

negligible

σJER = σB · krad σPLI σγ

pT asymmetry

(for dijets events)

A =p1T−p

2T

p1T+p2

T

and its resolution is defined as

σA ·krad =σJER ,probe

2 ⊕ σJER ,tag2 ⊕σPLI ,dijet

and if both jets are in the same regionand share the same JER

σJER =√

2(σA · krad σPLI ,dijet )



pT balancing and MPF methodsp

pT -balance

jet fully captures parton that balancesreference object

RpT = 1−〈A〉1+〈A〉

where

A=pprobeT −ptagT

2paveT

MPF

~/ET solely due to jet mismeasurements

RMPF = 1−〈B〉1+〈B〉

where

B = 1 +~ET ,miss · ~pT

tag

2paveT ·| ~pTtag |



Jet energy resolution in forward regionp



Jet energy resolution data/MC scale factorsp

Resolution Data/MCscale factors of1.1-1.2 except for theEC-HF transitionregion around η=3



JEC with 2015 datap



Better HF calibrationp

thanks to the new HF detector had been upgraded (2013-2014)

|ηJet |0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Sim

ulat

ed je

t res

pons

e

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

(8 TeV)CMS

= 10 GeVT

p = 30 GeV

Tp

= 100 GeVT

p

= 400 GeVT

p = 2000 GeV

Tp

R = 0.5, PF+CHST2012 JES: Anti-k

Barrel Endcap ForwardBB EC1 EC2 HF

pT -dependence of HF is better calibrated



Jet energy correction uncertaintyp

• Pileup uncertaintydominant below 50 GeV

• absolute scale within|η| <3

• relative scale at |η| >3

• Minimum uncertainty of∼ 0.7% at pT = 300 GeVand |η| <3



JEC uncertainties in Run1p

(GeV)T

p20 100 200 1000

JEC

unc

erta

inty

(%

)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb

CMS Total uncertaintyExcl. flavor, timeAbsolute scaleRelative scale

=20)⟩µ⟨Pileup (Jet flavor (QCD)Time stability

R=0.5 PF+CHS| = 0

jetη|

(8 TeV)-119.7 fb

CMS

jetη

4− 2− 0 2 4JE

C u

ncer

tain

ty (

%)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb



R=0.5 PF+CHS = 30 GeV

Tp

(8 TeV)-119.7 fb

CMS

(GeV)T

p20 100 200 1000

JEC

unc

erta

inty

(%

)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb



R=0.5 PF+CHS| = 2.7

jetη|

(8 TeV)-119.7 fb

CMS

jetη

4− 2− 0 2 4

JEC

unc

erta

inty

(%

)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb



R=0.5 PF+CHS = 100 GeV

Tp

(8 TeV)-119.7 fb

CMS

(GeV)T

p20 100 200 1000

JEC

unc

erta

inty

(%

)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb



R=0.5 PF+CHS| = 3.5

jetη|

(8 TeV)-119.7 fb

CMS

jetη

4− 2− 0 2 4JE

C u

ncer

tain

ty (

%)

0

1

2

3

4

5

6 (8 TeV)-119.7 fb



R=0.5 PF+CHS = 1000 GeV

Tp

(8 TeV)-119.7 fb

CMS



JER in Run1p

(GeV)T, ptcl

p20 30 100 200 1000

JER

00.05

0.10.150.2

0.250.3

0.350.4

0.450.5 (8 TeV)CMS Simulation

, R=0.5 (PF+CHS)TAnti-k|<1.3η|=0µ

< 10µ ≤0 < 20µ ≤10 < 30µ ≤20 < 40µ ≤30


< 10µ ≤0 < 20µ ≤10 < 30µ ≤20 < 40µ ≤30

(GeV)T, ptcl

p20 30 100 200 1000

JER

00.05

0.10.150.2

0.250.3

0.350.4

0.450.5 (8 TeV)CMS Simulation


< 10µ ≤0 < 20µ ≤10 < 30µ ≤20 < 40µ ≤30


< 10µ ≤0 < 20µ ≤10 < 30µ ≤20 < 40µ ≤30



JEC in Run1p

-5 -4 -3 -2 -1 0 1 2 3 4 5

(G

eV)

⟩µ⟨ / ⟩

T,of

fset

p⟨

0.2

0.4

0.6

0.8

1PhotonsEM depositsNeutral hadronsHadronic depositsUnassoc. charged hadronsCharged hadrons

PhotonsEM depositsNeutral hadronsHadronic depositsUnassoc. charged hadronsCharged hadrons

R=0.5TAnti-k

> = 19µ<

Markers: Data, Histograms: MC

(8 TeV)-119.7 fb

CMS

η -5 -4 -3 -2 -1 0 1 2 3 4 5

Dat

a/M

C

1

1.2PFPF+CHSPFPF+CHS

|η|0 1 2 3 4 5

Rel

ativ

e co

rrec

tion

0.98

1

1.02

1.04

1.06

1.08

1.1

1.12

1.14

1.16

1.18

(jet)T

p

60 GeV

120 GeV

240 GeV

480 GeV

(8 TeV)-119.7 fb

CMS R=0.5 PF+CHSTAnti-k

(GeV)T

p40 100 200 1000

Pos

t-fit

jet r

espo

nse

(rat

io)

0.94

0.96

0.98

1

1.02

1.04

1.06

1.08 (8 TeV)-119.7 fb

CMS

balT

p

MPFMultijet+jetγ

ee)+jet→Z()+jetµµ→Z(

JES unc.

| < 1.3η| 0→ < 0.3 α

After global fit = 107.5 / 92dof / N2χ



PF jet compositionp

(GeV)T

p40 100 200 1000 2000

PF

ene

rgy

frac

tion

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

(8 TeV)-119.7 fbCMS

Charged pileupCharged hadronsPhotonsNeutral hadronsLeptons

| < 1.3η| R=0.5TAnti-k

Markers: DataHistogram: MC

(GeV)T

p40 100 200 1000 2000

Dat

a-M

C (

%)

2−

0

2 η5− 4− 3− 2− 1− 0 1 2 3 4 5

PF

ene

rgy

frac

tion

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

(8 TeV)-119.7 fbCMS

Charged pileupCharged hadronsPhotonsNeutral hadronsLeptonsForward hadronsForward photons

< 74 GeVT

56 < p R=0.5TAnti-k

Markers: DataHistogram: MC

η5− 4− 3− 2− 1− 0 1 2 3 4 5

Dat

a-M

C (

%)

4−

2−

0

2

4



Anomalous ~/ETp

~/ET distributions for eventspassing the dijet selection

without cleaning algorithmsapplied (open markers), withcleaning algorithms applied

(filled markers), and simulatedevents (filled histograms).



MET geometrical approachp

~pT(γ/Z)

~/ET

~uT

u⊥

u|| - ~pT: Z/γ transverse momentum- ~uT: hadronic recoil

~pT + ~uT + ~/ET = 0

parallel component perpendicular component



PUPP~/ETp

Good agreement between data and MC was seen in both.The stable performance of PUPPI was confirmed with data.



How puppi worksp

from Satoshi Hasegawa’s talk @BOOST2015


jet performance in run2 at cms - uzh - physik-institutgrauco/boost16.pdf · jet performance in run2...

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