1. Study of the e + e   η  process at √s = 1 GeV (main systematic error in the e + e   e + e  η analysis) 09-02-2010

2. N. expected events = L σ (e + e   η  ) BR (         ) ε         Integrated luminosity L= 239.6 pb -1 σ (e + e   η , η        ) = 0.23 nb

3. 3 e + e -  e + e -  : systematics  Output  (  ) value always 15% lower than expected value  Spread among results from different    cuts ~ 11%  For a fixed    cut, the difference between p L and M miss 2 fits ~ 2%  With or without p T <100 MeV cut, related to the generated p T distribution for MC signal ~ 3%  1 (no p T cut) = 0.209 ± 0.003  2 (p T cut) = 0.196 ± 0.003  (e + e   e + e   s=1 GeV) = (50±2 stat ±9 syst ) pb

4. 4 TRIGGER, FILFO γγ filter (see KLOE Memo n.346), in detail: 2 tracks with opposite charge from a cylinder with ρ PCA < 8 cm, |z PCA |< 8 cm, ρ first-hit < 50 cm Analysis criteria at least 2 neutral prompt clusters with E clu > 15 MeV 100 MeV < Σ E γ < 900 MeV E γ 1 > 50 MeV 3 neutral prompt clusters “Electron likelihood” cut Cuts to reduce “pathological” background: –“Split tracks” cut  angle > 20 °  +  - mass < 425 MeV Event selection

5. √s= ∑ 3  E  + E   + E   ∑  p  + p  + p  = 0 (3  ) t  - |r  |/c = 0 (3  ) 15  variables : E,t,x,y,z for each  7 constraints: Lagrange multipliers method: Kinematic fit MC signal data Energy resolution γγ pairing

6. QED + “pathological” backgrounds data    e + e   e + e   e + e   “split” tracks “select” cut, “split” cut

7.  angle MC signaldata

8.      invariant  mass      SLSL

9.      invariant  mass      SLSL K + K      0    0, e   0  +  0 K S K L    0  0  + e 

10. A: M  +  - < 425 MeV B: |p  +|+|p  -| < 440 MeV C:  E  > 350 MeV   K+K-KSKLKSKL          N0N0 5.5 10 6 9.2 10 6 2.9 10 7 2.0 10 7 9.0 10 6 A 0.3100.66 10 -1 0.36 10 -3 0.12 10 -2 0.69 10 -2 AB 0.3100.43 10 -1 0.31 10 -3 0.11 10 -2 0.40 10 -2 AC 0.3050.35 10 -1 0.58 10 -4 0.70 10 -3 0.46 10 -2 ABC 0.3050.32 10 -1 0.55 10 -4 0.70 10 -3 0.37 10 -2 MC signal

11.        

12. 12 Kinematic fit MC signal      invariant mass  3 energy

13. M      (MeV)E  3 (MeV) e + e -   0 e + e -        e + e -     fit /d.o.f.= 193/169 N. final data = 172604  ~ 9%,    ~ 58%,  ~ 22% Fit (A)   fit /d.o.f.= 218/174

14. Fit (AB)   fit /d.o.f.= 170/169   fit /d.o.f.= 219/174 e + e -   0 e + e -        e + e -   M      (MeV)E  3 (MeV) N. final data = 115965  ~ 13%,    ~ 60%,  ~ 19%

15. Fit (AC)   fit /d.o.f.= 197/169   fit /d.o.f.= 226/174 e + e -   0 e + e -        e + e -   M      (MeV)E  3 (MeV) N. final data = 105973  ~ 14%,    ~ 54%,  ~ 24%

16. Fit (ABC)   fit /d.o.f.= 178/169   fit /d.o.f.= 222/174 e + e -   0 e + e -        e + e -   M      (MeV)E  3 (MeV) N. final data = 94939  ~ 15%,    ~ 55%,  ~ 21%

17. E3E3M  +  -   (nb) (A) 0.198 ± 0.0020.202 ± 0.002  (nb) (AB) 0.200 ± 0.0020.196 ± 0.002  (nb) (AC) 0.198 ± 0.0020.197 ± 0.002  (nb) (ABC) 0.198 ± 0.0020.196 ± 0.002 Results e + e   η  (         )

18. E3E3M  +  -   (nb) (A) 6.28 ± 0.096.60 ± 0.07  (nb) (AB) 6.70 ± 0.086.89 ± 0.11  (nb) (AC) 6.89 ± 0.117.02 ± 0.10  (nb) (ABC) 6.80 ± 0.116.93 ± 0.03 e + e      (         ) Spare slides