Search for LFV at BaBar

Sept 25,2008Novosibirsk (Russia)

Marcello A. Giorgi 1

Search for LFV at BaBar

Marcello A. Giorgi(on behalf of Babar collaboration)

Università di Pisa & INFN Pisa

September 25,2008

http://www.unipi.it/princ.html



LFV in tau decayStandard Model allows LFV.

In charged leptons it can occur in loops with expected low branching fractions. Es: expected Br () <O (10-40)

Even less in 3 leptons

For this contribution

Observable lepton decays with FV will allow a clear indication of New Physics.

Many New Physis models predict strong enhancement of violating decays of muons and taus. In many models measurable and even quite large BR [O(10-8)] are expected.

a

c

b

But with all contributions becomes larger than

expect a c

c b




Some model predictions

In SUSY LFV decays are generated via slepton mixing




Tau factory

At e+e asymmetric B factories KEKB and PEPII the high luminosity allows huge pair data samples usable for LFV search in many channels.




Babar-PEPII Integrated Luminosity

e- e+

PEPII and KEKB are Asymmetric Factories at 10.58GeV center of mass Energy

Data sample used in the analysis is 376 fb-1, 346M pairsRecorded Luminosity 531fb-1488Mpairs on disk




3-1 PRONG selection

e- e+

e- e+

Babar lab. reference

system

Center of mass system

3 prong Q=+1

selection

1 prong Q=-1

selection

Hemisphere#1

Hemisphere#2

Thrus

t axis




Preselection Efficiency (%)Sample Trg selector 4 tracks Qtot=0 1-3 topology + Total

Signal MC

e-e+e- 99.5 89.6 98.5 42.8 37.6±0.1

-e+e- 99.5 89.9 98.8 41.8 38.6±0.1

e-+e- 99.5 89.7 98.7 43.9 38.7±0.1

e-+- 99.5 91.1 98.9 45.3 40.7±0.1

-e+- 99.6 90.9 99.0 45.3 40.6±0.1

-+- 99.7 92.3 99.0 47.0 42.7±0.1

Background MC

bb 98.5 39.2 65.1 0.35 0.18

cc 97.8 46.0 72.6 4.00 1.28

uds 97.9 52.2 80.2 5.50 2.11

95.1 77.1 98.4 15.92 11.5

Data

On-Peak 93.5 51.9 85.5 3.39 1.51

Off-Peak 93.8 52.4 86.1 3.86 1.72




Analysis Strategy (Of course blind analysis)

•The signal and background events are scattered in the plane where “Signal Boxes” (SB) are optimized for the lowest expected upper limit (UL). The area around SB, that includes sidebands needed for Bkg normalization on data, defines the large box (LB). •Different signal regions SB are used for different signal channel.•Resolution and radiative effects smear the M-E distributions of each signal channel in different way, and limits of SB in (M,E) plane are therefore separately optimized.•The expected Bkg is estimated from sidebands•Borders of LB are the same for all channels

2/)(

)()(

sEE

MMMcms

PDGINV

Definition of LB, SB in () plane

M1 M2

E2

E1

vs




Adding Particle Identification (PID)

•Bhabha and di-muon are modeled from control samples: PID efficiency same as for data•Average PID efficiency for Muons 65%•Average PID efficiency for electrons 81 %

Signal (MC) bb (MC) cc (MC) uds (MC) bkg

MC Data

e-e+e- 0.775 9.2 10-7 6.9 10-9 1.9 10-8 6.4 10-7 9.9 10-4

-e+e- 0.531 1.2 10-6 9.0 10-8 3.2 10-7 5.8 10-7 5.0 10-5

e-+e- 0.533 2.2 10-6 2.0 10-6 1.6 10-6 1.1 10-6 2.1 10-6

e-+- 0.368 8.7 10-7 2.0 10-6 5.9 10-6 7.2 10-6 8.0 10-6

-e+- 0.359 1.7 10-6 9.6 10-7 2.5 10-7 1.4 10-7 1.4 10-4

-+- 0.253 2.4 10-6 1.2 10-6 2.1 10-6 3.4 10-6 1.0 10-5

Low PID efficiency due to presence of soft (in channel 35 % muons are slow )

PID efficiency




Event Selection• Mass of 1-prong side (with missing momentum) 0.3 <m1pr (GeV)<3.0

for (e-e+e-) (-e+e-) 0.5 <m1pr (GeV)<2.5

• Momentum of 1-prong track p1cms <4.8 GeV

• No tracks in the 3 prong side identified as Kaons

• Total transverse momentum in the c.m.s. :

– pTcms>0.4GeV for (e-e+e-) and (e-+-)

– pTcms>0.2GeV for (-e+e-)

• To reject BhaBha in (e-e+e-) and (e-+-), one prong track should not be identified as electron.

• To reject di-muons in (-e+e-) and (-+-), one prong track should not be identified as muon.

Signal(MC) bb(MC) cc(MC) uds(MC) bkg

MC) Data

e-e+e- 68.6 48.6 13.8 9.21 0.13 0.215

-e+e- 72.3 60.3 38.1 35.7 8.12 1.7

e-+e- 94.3 79.2 23.7 50.9 90.1 40.0

e-+- 93.7 56.8 27.7 51.1 87.1 63.2

-e+- 71.7 57.8 21.6 45.4 65.5 0.7

-+- 77.2 50.0 21.8 50.7 71.7 18.3

Efficiency (%)




Backgrounds

qq (uds, cc) (bb negligible) uniform M,

E < 0 (MC)

backgrounds M < 0

E < 0 (MC)

Bhabha di-muonUniformM

E 0 (MC)

3l

Data candidates




Bidimensional Bkg EstimationHadronic (uds + cc) backgrounds estimated using a two-dimensional (M, E ) PDF as

product of two one-dimensional (PMh, PEh) PDF. To avoid correlations a choice of rotated variables is made (empirical parametrization):

PM’ is a bifurcated Gaussian. E0’ [and (E’)] , are free parameters. Tau backgrounds are estimated with a similar likelihood fit but with same

parameterization , but now 2 parameters : and (e-e+e-) and (e-+-) have large QED background contributions the estimation is done by

using a Reverse PID approach.Control sample is built with events in the great sideband (LB) passing selections,but PID in

1 prong side. PQED is defined as product of two one dimensional PDF on rotated variables PM’ and PE’ . PM’ is a third order polynomial while PE’ is a crystal ball function. A single rotation angle

is used .

EMEEMM )cos()sin(')sin()cos('




Expected EventsMC fit of PDF shapes of each Bkg component, then normalized on GS (data) extrapolated contribution to SBThe number of expected events in the signal region SB are estimated by

fitting Background PDF on data in the great sidebands [GS]=[LB-SB] and then integrating the resulting PDF in SB.

In sidebands the number of expected events is equal to the number of observed data events.

e-e+e- -e+e- e-+e- e-+- -e+- -+-

SB SB SB SB SB SB

Uds 0.41 0.25 0.53 0.49 0.41 0.29

QED 0.92 0 0.33 0 0.38 0

bkg

0 0.05 0.03 0.05 0.02 0.04

Total 1.53 0.30 0.89 0.54 0.81 0.33

),;,(),;,(log('' EiiEMiiMi

pEMPpEMPwL




Systematic Uncertainties• Uncertainties on Signal Efficiency

– Limited MC statistics introduce a 0.5-0.8% error in estimating efficiency (including phase space production model, ISR and FSR modeling)

– Uncertainties in branching fractions used in simulation of generic background introduce 0.9% error, luminosity and x-section contribute to 1% uncertainty.

– Tracking efficiency and resolution contribute in average 0.25% uncertainty /track, 1. % in total.

– Uncertainty on PID efficiency gives a contribution between 1.7% and 10.7% , uncertainty is larger for muons than for electrons.

• Uncertainties on Background Estimation– The estimated Background incorporates uncertainties from limited statistics on data

sidebands used fin the fit of Bkg PDF, from varying Bkg parametrisation and from MC statistics used in the fit of PDF of each bkg component.

– Other systematic uncertainties coming from two-photon contributions are found to be negligible

e-e+e- -e+e- e-+e- e-+- -e+- -+-

Uncertainties on Signal Selection Efficiency (%)

Total 2.7 7.9 6.3 8.7 7.4 12.6

Uncertainties on Expected Backgrounds (%)

Total 19.1 29.8 183 39.5 37.8 56.0


SB

LB



Calculating Upper Limit (UL)

Toy MC are produced varying Branching Fraction.The events fall part (“signal” ) inside the box and part (“background”) outside the box.BF is varied in the toy MC until the percentage of toy MonteCarlo observing less events than the number observed in the data (Nobs) is 10%. This defines the 90% CL UL

The expected UL is defined as the mean upper limit in assuming we observe a number of events distributed as expected Background.

),(),(expexpexp

0Obs

bkgN

Obs

bkgect

ULObs

bkgectectNnBNnPUL

UL is calculated using Cousins Highland Method [R.D. Cousins and V.L. Highland, Nucl.Instr.Meth.A 320,331 (1992)],and using the Barlow calculator [R.Barlow,Comput.Phys.Commun. 149,97(2002)]

LlllB NUL

2

1)(

90




Search for l-l+l-

• Efficiency ~ 5.5 -12.4 % depend on modes• Background events : 0.3 – 1.3 depend on

modes• Total Background = 4.2 ± 0.8 events• Observed events = 6 events• BR(l-l+l-) < (3.7-8.0) 10-8

@90% C.L.

Phys.Rev.Lett.99:251803,2007

NO SIGNALSOBSERVED

UL(108)




LFV prediction by model

Some predictions are already excluded by the present results.

??

Some can be tested soon by combined statistics of Babar and Belle




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Search for LFV at BaBar