Results from f  h p 0 g with h  p + p - p 0

1. Results fromf h p0 gwithh  p+ p- p0 2000 data  197 candidates / 16 pb-1  4  4 estimated background  19% efficiency C.Bini D.Leone KLOE Memo 250 04/02 KLOE Collab. Phys.Lett.B536 (2002) Analysis of 2001 + 2002 data: The data sample The method revisited Results ( BR estimate) The fit

2. 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 2002 full sample140.4 264.9 “good” runs137.0 260.8 “peak” runs136.4 245.2 Full data sample  397.8 pb-1 “good”  381.6 pb-1 “peak” Lum (nb-1 / 0.2 MeV) vss

3. The Method (1 – kinematical fits) Selection procedure:  Look for 2 tracks + 5 photons  Kinematical fit 1 [ Etot = s , Ptot = PCM ]  p(c21) > 5%  Select combinations with p(c2comb) > 5%  Kinematical fit 2 [ M(g1g2)=M(p0) , M(g3g4)=M(p0) , M(p+p-g1g2)=M(h) ]  p(c22) > 5% and choose best combination  E(g5) > 20 MeV MC Both kinematical fits are done numerically Using MINUIT (penalty function method) data The results has not to depend on the li 1/l (MeV)

4. The Method (2 - linearity) • After kinematical fit 1: • Look at M(gg) and M(p+p-gg) • distributions • [10 entries per event] • Mass peaks found p0 h w Data 2001 134.3  0.1 548.5  0.6 780.3  0.5 Data 2002 134.45  0.08 547.2  0.4 780.2  0.4 PDG values 134.9766 547.30  0.12 782.57  0.12 Old MC 134.6  0.3 548.3  0.5 New MC 132.9  0.3 544.8  0.5

5. The Method (3) p(c2) distributions: data – MC comparison New MC (15/05/03)  good agreement using same resolution functions: s(E)/E = 5.7% / E s(t) = 55 ps / E  150 ps Old MC BUT serious linearity problems in new MC after second kin. fit [ M(hp0)meas – M(hp0)true ] (now should be ok) New MC

6. Results (1 – f line-shape + BR) Number of events 2001 2002 “good” sample 1424 2856 “peak” sample 1422 2759 • Comments: • 1 – we observe ~BW behaviour  • hpg come from f 2 – discrepancy 2001 – 2002 [ ~ 2 s.d. ] but different s distribution 3 – estimate of BR (“peak” sample) s(f) = 3.34 mbarn BR(hp+p-p0) = 22.6  0.4 % PDG 2002 etot = 19.1% N(bckg) = (2  1)% BR(fhp0g) = (7.45  0.11  0.19)x10-5

7. Results (2 – spectra) • M(hp0) spectrum  dynamics • of the decay  a0 contribution. • 2001 vs 2002 • 2001+2002 vs. 2000 • [5 MeV vs 36 MeV binning] • Comparison of L-normalized • spectra.

8. Results (3 – angular distribution) • Expected angular distribution of the • radiated photon: • ( 1 + cos2qg) if hp is J=0 • Efficiency not flat in cosqg • (from MC) • Spectrum described by A(1 + cos2qg) + B  Agreement data-MC (a0)

9. The fit Same combined fit done on 2000 data (Achasov function for a0 + rp) Free parameters: M(a0) g2(a0KK)/4p R=g(a0hp)/g(a0KK) BR(rp) Contributions to the c2 Data vs. fit “charged” spectrum “neutral” spectrum

10. The fit (results) Comments:  c2 / dof still not good  smearing of “charged” spectrum  BR(rp) compatible with 0: “expected” is BR ~ 0.4 x 10-5  M(a0) ok  a0 parameters in agreement with published fit

11. The Method (4 – efficiency) MC based efficiency + g eff. corrections + track eff. corrections (based on 2000 data and old MC) Overall efficiency vs. M(hp0) cosq(grad)

12. The Method (5 – background) The background is small ~ few %: 2t + 4/6 photons Results: (how many bckg events survive to the selection chain) 2 wp0 events  11 events on the “peak” sample 1 KSKL  p0p0 p+p-p0 event  41 events on the “peak” sample No events from other channels  < 100 events Check with distribution after fit-1: Describe M(p+p-gg) spectrum with Sum SIGNAL + BCKG

13. It works BUT: wp = wp x 4 Ksn = Ksn x 1.5 Estimated bckg Between 51 and 105 events / 4200 candidates: < 3% in the worst case This analysis needs “good” simulation of accidentals: Wait for new MC campaign