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0 0 5 5 Outline • Event selection & analysis • Background rejection • Efficiencies • Mass spectrum • Comparison data-MC • Branching ratio evaluation • Systematics • Comparison with SND and CMD 2 • Conclusions (Search for (Search for a a 0 ) ) P.Gauzzi Workshop on KLOE Physics La Biodola – May 23-25, 2001
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Page 1: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

0055

Outline • Event selection & analysis• Background rejection• Efficiencies• Mass spectrum• Comparison data-MC• Branching ratio evaluation• Systematics • Comparison with SND and CMD 2 • Conclusions

(Search for (Search for aa00))

P.Gauzzi

Workshop on KLOE Physics

La Biodola – May 23-25, 2001

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0

• Signal: (nb) expected (=1) a00 0.10 1700 000 0.037 630

• Background: e+e-0 00 0.74 12500 00 00 0.10 1700 f000 0.37 6300 e+e-00 5.6x10-3 100 3 16.3 3500* 000 13.4 6000*

• Cross-sections from PDG-2000; a0, f0, and 0 from Novosibirsk data• Large errors on cross sections 15% — 25 %* reconstructed as 5 photon events (acc. to MC)

Page 3: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Initial sample

• Runs 15174—17033 Ldt 17 pb-1

• Events from radiative stream (selected by nrfilt)• “ “ substream neu_min_5g (no tracks and at least 5 prompt )

• First selection 5 prompt photons ( t.w.= min(5 t, , 2 ns) ) > 21o for each photon total energy > 900 MeV (to reject background)

• Initial sample : 36979 events

(tr.+nrfilt+ 5 pr. photons) signal 53 % (3%) 2084 expected evts 00 53 % 10865 3 3500 000 6000

Page 4: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Analysis scheme• First kinematic fit: 30 parameters (E,x,y,z,t for each photon + X,Y,Z of the I.P., Ee+, Ee-) 9 constraints (energy and momentum conservation + T-L/c=0 for each photon) 9 ndf cut: 2/ndf < 10• Best photon pairing in the following hypotheses: 1) 0 2) 00 3) 0 00 ( mass , E0 in the selection 2) 4) 3 ( mass , Erad in the selection 2)

rejection 3 rejection• Second kinematic fit : 30 parameters, 11 constraints( 9 + and 0 masses for 1) or two 0 masses for 2) 3) ) For each event this fit is performed three times hyp. 1) , 2) and 3) cut: 2/ndf (hyp. 1) < 10 • Final cuts:

00 rejection 7 rejection

Page 5: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

MC samples

Samples used to study cuts and evaluate efficiencies : • a00 40000 evts • 0 (a0 “flat”) 45000 • e+e-0 00 80000• e+e-00 30000• 00 00 70000• 000 50000• f000 (old generation) 5000• 3 300000• 000 285000

• Cuts on the signal have been studied with 0 (a0 “flat”) in order to avoid introducing any bias on the unknown a0 shape

Page 6: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

a0 “flat”

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00 rejection

0 0

Second fit in the 000 hypothesis

= angle between the photon from and the 0 not coming from in the CoM system of (00)

0 0

00

f0 0 00

Page 8: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Sample composition

• Data– MC (without )

Agreement is not good, but expected number of events have large errors

signal = 48 % 824 expected evts 0+ f0 30 % 5719 00 37 % 635 000 3 x 10-3 736 ?

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Sample composition

Fit the MC distributions to data: 1) 1(+) + 2() + 3(f0)2) (+) fixed + 1(7) + 2() + 3(f0)

• Data– fit

• Data– fit

1) 1 1.25 2 3 0.8

2) 1 0.95 2 3 0.8

Page 10: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Sample composition

Check with the other variable of the scatter plot (E)

• Data– MC

With parametersfrom 1st fit

without 000

With parametersfrom 2nd fitwith 000

• Sizeable content of 000 • decrease 0 and f0 cross-sections by 20% (see Simona’s results)

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00 rejection

• Data– MC

• There are many events that have good probability to be both 00 and 0

2-2

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000 rejection

• Cluster of maximum energy

• Data– MC

• invariant mass after the elliptic cut

2 cut

• Data– MC 7

Emax (MeV)

M /

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Efficiencies

a00 27%

000 27%

e+e-00 27%

e+e-0 00 3.5 x 10-3

00 00 5%

f000 1.4 x 10-3 (depends on

the shape)

3 2 x 10-6

000 5 x 10-4

Page 14: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Mass spectrum

• Data: 666 events Backgrounds (MC)–– 00 (1293.7)–– 7 (11810)–– 00 (210.2)–– total (26810.7)

M (MeV)

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cos of rad.

• Data: 666 events –– background (268 events)–– signal (MC) + background

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Comparison data-MC

2 of the first fit, ndf =9(without mass contraints)

2 of the second fit, ndf =11(with mass contraints)

• Data– MC

• Data– MC

Page 17: 0  5  Outline Event selection & analysis Background rejection Efficiencies Mass spectrum Comparison data-MC Branching ratio evaluation Systematics.

Comparison data-MC

• Data– MC

• Data– MC

M /

M /

• Pion and eta mass (before the second fit)

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Branching ratio

39% γγ)Br(η

produced 105.38Lσ ; 27%ε

10)0.050.71(γγ)Br(ηεLσ

BNγ)ηπBr(

7

4stat

0

M (MeV)

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a00• If interference in (a0+0) 0 is negligible (Achasov-Gubin: Phys.Rev.Lett.D63,094007)

• N(0) = 171 60(from cross-sect.) events

-400 10))0.14(syst.0.39(γ)ηπγaBr(

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a00

M (MeV)

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Efficiency

M (MeV)

bineach for )(MN

)(MN)ε(M

ηπreconstr.

ηπreconstr.

ηπ

cuts before

cutsafter

• Not corrected for photon detection efficiency

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Efficiency

M (MeV)

dBr/dM (MeV-1)

0.69ε

BN

γγ)Br(ηLσ

1γ)ηπBr(

ii

ii0

)B(NεN NεN jobsjj

1ijij

genjij

reci

• Next step:

M (MeV)

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QCAL veto

• Veto = hit in QCAL on time with the event• <(0)> does not change• ( 7) 3 x 10-4 (40% less)

564 events selected (102 rej.)

M (MeV)

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Systematics

γγ)Br(ηεN

BNγ)ηπBr( 0

• Background subtraction (main contribution): B = 118() + 150(others)

20% uncertainty on cross-sections Br/Br = 8%

uncertainty on to be evaluated

• Efficiency : uncertainty to be evaluated

• N : uncertainty on Ldt

“ on : 5% (from Kloe memo 234)

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Comparison with SND

• SND: 39 events with <> = 2.1% 2x107 (Phys. Lett. B 279 (2000),53) Br=(0.880.140.09)x10-

4 S/B 0.6• KLOE bckg subtracted and corrected for efficiencyS/B = 1.5

M (MeV)

dBr/dM (MeV-1)

• SND: from tab.1 of their paper

• KLOE spectrum before bckg subtraction, not corrected for eff.

(No normaliz.)

(Normalized)

M (MeV)

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Comparison with CMD-2

• CMD-2: after bckg subtraction; <> = 6% 1.9 x107 Br = (0.90 0.24 0.10) x 10-4 (Phys.Lett.B 462 (1999), 380)

• KLOE spectrum bckg subtracted

(Normalized)

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Conclusions

• Ldt 17 pb-1 from 2000 data analyzed• 666 events survive the selection • 268 background events estimated from MC• 398 signal events• Br(0) = (0.710.05(stat)) x 10-4

• good agreement between data and MC

• Efficiency as a function of M: need a better evaluation

• Systematics: bckgd. subtraction is dominant( 8%)

uncertainty on efficiencies to be evaluated

• Fit to the spectrum has to be performed in order to get the a0 parameters

• Comparison with the Novosibirsk results: our Br is 20% less, BUT: we have much more statistics, greater efficiency, better S/N ratio.

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Efficiencies

a00 27% 26.8%

000 27% 26.8%

e+e-00 26% 25.7%

e+e-0 00 3.5 x 10-3 3.4 x 10-3

00 00 5% 5%

f000 1.4 x 10-3 1.4 x 10-3

000 5.3 x 10-4 4.1 x 10-4

2/ndf<10 2/ndf<5

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2/ndf<5

000 63 (not bckg.)

e+e-00 8

e+e-0 00 37

00 00 83

f000 7

000 91

Expected events

Total. 226 9

1.297% ηγ)Br( ; 170284N(

10)0.05(0.68

ηγ)Br(N(

ε(ηγ)

ε

BNγ)ηπBr(

4stat

0

ηγ)

ηγ)

From data : N = 599 events

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000

Cut

e+e-0 00 26.8%

f000 2.7% 166

f000(f0g_neu4) 5.1% 314

00 00 8.0% 133

0 2.5% 37

5x10-4 226

From data : 3443 events

Total : 562 – 710

nb 0.650.61γ)ππσ(ωπ 000


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