1. Z cross-section with simultaneous fit Luca Lista for: Annapaola De Cosa, Michele De Gruttola, Salvatore Di Guida, Francesco Fabozzi, Pasquale Noli, Davide Piccolo (LNF)

2. Luca Lista, Gr-I 20082 Analysis strategy Z µµ two global muons, both matched to HLT primitive Z µµ two global muons, one matched to HLT primitive Z µsa 1 global + 1 stand-alone muons, global mu matched to HLT Z µtk 1 global muon + 1 track, muon matched to HLT Z µµ non-iso two global muons, at least one non-isolated, at least one matched to HLT Define five independent samples:

3. Luca Lista, Gr-I 20083 Data-driven di-muon mass PDF

4. Luca Lista, Gr-I 20084 MC Samples

5. Luca Lista, Gr-I 20085 Global fit approach Negligible background on Z µµ sample Assume identical di-muon peak shape for other samples –Fully data-diven model (no MC input!) –Except Z µsa, fitted with a gaussian, due to poorer resolution

6. Luca Lista, Gr-I 20086 Global fit results Nµµ = 3818 ± 64 Parameter Fit (%) Mc truth(%) ε HLT Fit = / Low statistics at 10 pb -1 !

7. Luca Lista, Gr-I 20087 Different luminosity scenarios

8. Luca Lista, Gr-I 20088 Cross section stability Cross section estimate uncorrected for kinematic efficiency

9. Luca Lista, Gr-I 20089 α = 0.75 Relevant calorimeters contribution Optimization of isolation selection

10. Luca Lista, Gr-I 200810 β = -0.75 Hcal more relevant than Ecal Optimization of isolation selection

11. Luca Lista, Gr-I 200811 First look at real data (Cosmics, of course…)

12. Luca Lista, Gr-I 200812 Ongoing improvements Apply optimized isolation –Background reduction of ~30 50 % –Reduced statistical error on by ~6% Extract peak shape for Z sa from data –Use Z, suppress track on one leg Use Extended Unbinned Max. Likelihood fit on low statistics sample Validate fit performances using a Toy MC Prepare abstract for winter conferences!