Outline:

(1) The data sample 2001 + 2002(2) Some news on the analysis method(3) Efficiency revised(4) Background revised(5) Data: spectrum + “phi-curve”(6) Data-MC comparison

with

2000 data 197 candidates / 16 pb-1

4 4 estimated background 19% efficiency

C.Bini D.Leone KLOE Memo 250 04/02KLOE Collab. Phys.Lett.B536 (2002)

spectrum + combined fit

(1) The data sample

“good” runs: luminosity value ok good s value (a) used in kin.fits (b) for “phi-curve” removed trigger problems (KLOE Memo 281)“peak” runs 1018< s <1021 MeV

2001: pb-1

full sample 140.4“good” runs 137.0“peak” runs 136.4

2002: pb-1

full sample 264.9“good” runs 260.8“peak” runs 245.2

Lum (nb-1 / 0.2 MeV) vs s

100 evts

100 evts

1 evt

1 evt

Full data sample 397.8 pb-1 “good” 381.6 pb-1 “peak”

(2) Some news on the analysis method

Kinematical fits are done numerically using MINUIT(“penalty function method”)

N

k

N

i

fit

iimeas

k

fit

k

meas

kC

xCx

xx

1 12

22 )(

)()(

N = number of measurements per event = 3X2 + 5X5 = 31Xk

meas = measured quantities (momenta, energies, positions, times)Xk

fit = parameters of the fitNC = number of constraints = 4 + 5 + (3)Ci = constraints (functions of the parameters)

i = arbitrary parameters (in principle )The result has not to depend on

MC

data

1/(MeV)

On data and Montecarlo samplesStudied the dependence:

Large “plateau” observed for data and Montecarlo:Small more events enter (mostly background)Large loss of events (MINUIT “crisis”)

values at “plateau center”

(3) Efficiency revised

Used MC with accele default (based on 2000)Corrections on data / MC for photons and tracks (based on 2000)Weighted M() distribution using the curve obtained from 2000 data

Cuts:• 2T from vertex ( R < X cm |Z| < Y cm) BPOS used• 5 photons ( > 10 MeV )• kin.fit 1 p(2) > 5%• at least 1 “good” combination• kin.fit 2 (on all “good” combinations) p(2) > 5%• E(rad) > 20 MeV

M() (MeV)

(4) Background revised

Expected background ~ few % from MC but checked with dataMain sources: final state (equiv.) MC available Leq

9.6 pb 580 e+e- 4.7 nb708.4 nb 30KSKL 50 nb 4.2KSKL

e20 nb 9.3

The KSKL final state are considered for KL decaying R < 25 cmResults of selection chain application:

2 events 11 events on the “peak” sample 1 KSKL event 41 events on the “peak” sampleNo events from other channels < 100 events(notice: 1 enters for an accidental; 1 for a splitting; the KSKL for a low energy photon lost)

Distribution of M() after kin.fit-1 (10 entries per event):MC expectations for signal and background

Same distribution from 2002 data sample after kin.fit-1:15358 events (only ~3000 of them are “good” signal events)

Try to describe the data distribution withSum of:

MC (signal + background + Ksn background).(solid) data

(dashed) MC sum

It works but:= x 4

Ksn = Ksn x 1.5Why ? Accidentals and splittings not at work in old MC ? Try with new MC

Conclusion:Estimated background between 51 and 105 events / 4200 candidates

In the worst case < 3%

(5) The data:

Number of events Events / L

2001 2002 2001 2002“good” sample 1424 2856 10.39 10.95“peak” sample 1422 2759 10.42 11.25

Assuming the same efficiency 2001 - 2002 10.42 0.28 vs. 11.25 0.21 Difference = 0.83 0.35

scan results:

Raw spectra: only “peak” samples

Comparison 2001-2002 (normalized to luminosity)

Spectrum 2001+2002 [4181 evts] compared to 2000 [197 evts] (normalized to luminosity and bin size)

Is it a spectrum compatible with a resonance ?Take away the signature of the radiative decay, plotting not N(M) but

3

..

2

)(

)(

)(

p

MN

Mfp

MN

ps

M(MeV)

Simple fit with Breit-Wigner

4)(

22 R

RMM

A

MR = 985 1 MeV(PDG 984.7 1.2 MeV)

R = 33 1 MeV(PDG 50 100 MeV)

Dalitz plot density distribution: M() vs. M()

Expected signalsfrom and a0 region

Distribution of M() (5 MeV bins) : signal of ?

(6) Data – MC comparison. (a) tracks and photon distributions

(b) 2 probability distributions: Fit-1 and Fit-2

(d) cosrad distribution: comparison with (1+ cosrad 2):

try fit with:A(1+x2)+B(1-x2)

If dist ~ (1+ cosrad 2) B=0data need B0 deviation from (1+ cosrad 2)

Solid = MCPoints = data 2002Curve = A(1+x2)

Conclusions:

(0) Some improvement to the data sample

(1) Work on new Montecarlo with: improved statistics

realistic background Understand 2001-2002 discrepancy1% estimate of background

(2) Track and photon data/MC efficiency

(3) Estimate of BR with more stable efficiency

(4) Fit as 1 year ago Compare with 5 photons analysis