LPSC - Grenoble Julien MOREL 1Z' e+e- discovery potential computation

Z' Z' ee++ee-- discovery potential discovery potential computationcomputation

Julien MOREL

ATLAS Exotics groupIN2P3 – CNRS - LPSC - Grenoble

18 / 09 / 2007 – CSC dilepton/diphoton

LPSC - Grenoble Julien MOREL 2Z' e+e- discovery potential computation

CSC full simulated Z’…CSC full simulated Z’…

Z’ χ e+e- a 1 TeV

7250 Z’ with MZ’ = 1 TeV et Mll>500GeV

DataSet = 5605

Généré

Reconstruit

Mll (GeV)

Invariante mass spectrumInvariante mass spectrum Electron energy spectrumElectron energy spectrum

LPSC - Grenoble Julien MOREL 3Z' e+e- discovery potential computation

di-electron invariant mass spectrum modelisationdi-electron invariant mass spectrum modelisation

Background modelisation (DY)Background modelisation (DY)

/ Z

f

f

, ,u d s

, ,u d s

DY

M

( )pdfG M

# E

ven

t/ 1

0 G

eV Normalisa

tion 1 fb-1

Gpdf depand on the pdf

Fit with a 6 parameters ad-hoc function (Χ2/ndf = 726/557)

Good modelisation between 300 GeV et 6 TeV

-DY Pythia-DY (modelisation)

(GeV)M

2

LPSC - Grenoble Julien MOREL 4Z' e+e- discovery potential computation

# E

vén

em

en

ts /

10 G

eV

Normalisation 1 fb-1

-Z’ χ généré officiel-Modélisation du Z’χ

(GeV)M

di-electron invariant mass spectrum modelisationdi-electron invariant mass spectrum modelisation

Signal modelisation (DY + Z’)Signal modelisation (DY + Z’)

'Z

f

f

, ,u d s

, ,u d s

( )pdfG M'Z DY

M M

( )pdfG M

Only 4 experimental parameters :

•The mass•The total decay width•A Z’ amplitude•An interference amplitude

Model independent parameterization

2

(GeV)M

# E

vén

em

en

ts /

10 G

eV

Normalisation 1 fb-1

-DY Pythia-Modélisation DY-Modélisation Z’ (M=3 TeV, Γ=20 GeV)

2 Re / 'Z Z

f

f

,u d

,u d/ 'Z Z

f

f

,u d

,u d

Modelisation of a big interference:

LPSC - Grenoble Julien MOREL 5Z' e+e- discovery potential computation

Z’ performences Z’ performences

Gaussian partGaussian part

~83 % of eventsσ~8.5 GeVμ~-2.4 GeV

Negative tailNegative tail

~0.4 % of eventsMay be a DY systematic

(M(Mgenegene – M – Mrecoreco)/ M)/ Mgenegene for 1 TeV Z’ for 1 TeV Z’

Positive tailPositive tail

~ 17 % of eventsInclude crack eventsNon negligible contribution

LPSC - Grenoble Julien MOREL 6Z' e+e- discovery potential computation

di-electron invariant mass spectrum modelisationdi-electron invariant mass spectrum modelisation

Cross check with full simulated 1 TeV ZCross check with full simulated 1 TeV Z’’

Normalisation 1 fb-1

# E

vén

em

en

ts /

1 G

eV

-Z’ χ reco (CSC simulation)-DY reco (modelisation)-Z’ χ reco (modelisation)

(GeV)M

'Observed spectrum ( ) = Resolution( ) Efficiency( )ZM M MM

Taking into account the resolution and efficiencyTaking into account the resolution and efficiency

LPSC - Grenoble Julien MOREL 7Z' e+e- discovery potential computation

di-electron invariant mass spectrum modelisationdi-electron invariant mass spectrum modelisation

Cross check with full simulated 7 TeV ZCross check with full simulated 7 TeV Z’ ’ (private production)(private production)

-Z’ χ Reco (full simulation)-Z’ χ Reco (modelisation)

(GeV)M (GeV)M

# E

ven

t/ 1

0 G

eV

# E

ven

t/ 1

0 G

eV

-Z’ χ Gene (CSC simulation)-Z’ χ Gene (modelisation)

Fit of generation Reco modelisation from gene fit

LPSC - Grenoble Julien MOREL 8Z' e+e- discovery potential computation

di-electron invariant mass spectrum modelisationdi-electron invariant mass spectrum modelisation

We can modelise many Z’ at different massWe can modelise many Z’ at different mass

-Z’ χ Gene Efficiency-Z’ χ Reco (modelisation)

(GeV)M

Generation with pythiaFit the generated shape with our parameterizationInclude the resolution and efficiency

LPSC - Grenoble Julien MOREL 9Z' e+e- discovery potential computation

ZEUS NLO + NLOMRST NLO + NLOCTEQ NLO + NLO

CTEQ LO + LO

Systematic incertaintiesSystematic incertainties

LHAPDF/CTEQ error sets

NLO calculationNLO calculation

Effect : Cross section + 20 to 34 %Mclimit implementation -0% , +20%

PDF incertaintiesPDF incertainties

4 à 8 %

Mclimit implementation 5%F.Heinemann

F.Heinemann

LPSC - Grenoble Julien MOREL 10Z' e+e- discovery potential computation

Using MCLimit for 2 TeV Z’ exampleUsing MCLimit for 2 TeV Z’ example

Les résultats de MCLimitLes résultats de MCLimit

H0 = DY , H1 = 2 TeV Z’H0 = DY , H1 = 2 TeV Z’

Mass = 2 TeV

Width = 24.3 GeV

Ampl. Z’ = 499

Ampl. Interference = -793

Normalisation 1 fb-1

# E

ven

t/ 1

0 G

eV

-Z’ reco (modelisation)-DY reco (modelisation)-Pseudo data

(GeV)M

Few events

Hypo DY

Hypo Z’

5000 pseudo exp.Lumi = 1 fb-1 Using Lumi5s() :Using Lumi5s() : We need

0.37 fb-1 are enought to discover this Z’.

With 5000 pseudo exp. results may fluctuate a bit.

Need more calculation-2lnQ

fit from generation

fit from generation

LPSC - Grenoble Julien MOREL 11Z' e+e- discovery potential computation

Discovery potentiel Discovery potentiel

CMS ResultCMS Result

Etude de la découverte du Z’ via :Etude de la découverte du Z’ via :6 models: SSM, LRM, ALRM, χ, ψ, η3 differentes masses : 1, 3, 5 TeV

Preliminary discovery limit

For Z’ Chi

Z’ mass (TeV)

Int

lum

i (f

b-1)

ATLAS preliminaryATLAS preliminary

~5 fb-1 for 3 TeV~5 fb-1 for 3 TeV

LPSC - Grenoble Julien MOREL 12Z' e+e- discovery potential computation

Luis result on 4 decembre 2007 fit based Luis result on 4 decembre 2007 fit based approcheapproche