1. 1 M2-M5 Efficiency and Timing checks on 7TeV beam data Alessia, Roberta R.Santacesaria, April 23 rd, 2010- Muon Operation meeting@CERN

2. 2 Efficiency 7TeV data for M2-M5 Method reminder: - MuonTrackRec standalone reconstruction using 4 stations, - Look for Clusters in the 5 th station within 6  around the prediction, no time cut - Assume the found cluster multiplicity distribution is due to efficiency + poissonian background - Fit with this assumption TAEnoTAE HV=2650V~ 1Mevts ~17Mevts HV optimized~ 1Mevts~ 6Mevts Data samples

3. 3 Applied cuts General cuts: - require that at least one Tracker track extrapolated to M1 matches within 1  the M1 cluster belonging to the Muon standalone track - P(track)>8 GeV - to discard fake tracks due to combinatorial (in R1 essentially), require that the best matched Tracker track to Muon track on M1, extrapolated to M5, matches the M5 cluster within 1 . - for the analysis of M5 P(track)>15GeV, match of the Tracker track on M3 and M4 Fiducial volume cuts - 6  fiducial volume cut in the inner border of R1 - 6  fiducial volume cut in the left-right borders of M4R4 - In 2 regions a clear inefficient zone is identified and discarded to compute the “ pure” efficiency value

4. 4 Results M2 M3 M4 M5 Region HV=2650, noTAE HV Optim, noTAE  FV cuts applied on R1 and M4R4, bad zones of M3R2 and M4R2 excluded Statistical errors only, ~0.1 systematic error must be included, due to bg subtraction

5. 5 TAE events at 2650V and effect of bad zones HV=2650V, TAE FV cuts, bad zones excluded HV=2650V, TAE bad zones included  ~1% is lost on M3R2, 0.2% on M4R2 M2 M3 M4 M5 Region

6. 6 M3R2 inefficient chamber 16A3 A side With more statistics clearly visible that 1 FEB is inefficient on the Cathods in 1/8 of the chamber  Estimated efficiency 50% on those cathods

7. 7 M3R2 16A3 A side Beam 2010 TED 2010 Efficiency ~ 50% since a long time Also clearly visible by channel statistics

8. 8 M4R2 Low efficiency due to two dead channels

9. 9 Q4M4R2H1 2 Dead channels

10. 10 M4R4 Some FV cuts needed also on M4R4 right-left sides to reject fake tracks due to hits on left-right borders in M2 and M5 (calorimeters not perfect shielding)

11. 11 M2 M5 X illumination on R4 M2R4 M5R4 Some tracks are faked on M4 with a random noise on M3 and M1(easy) X(mm)

12. 12 R1 – Effect of Cleaning cuts and FV cuts HV=optimal, noTAE  cleaning cuts HV=optimal, noTAE  no cleaning cuts  ~1.5% lost on M3R1, ~0.5% on M4R1 HV=optimal, noTAE  no FV cuts  ~1.5% lost on M3R1, ~0.5% on M4R1 Region M2 M3 M4 M5

13. 13 Multiplicities at HV_optimal.vs.2650V settings Ratio of the average number of Pads (red) and Clusters (blue) HV_optimal/2650V for noTAE events (time centering for HV_optimal)  ~ larger  V corresponds to lower ratio (M2R1,M3R1), also Clusters change, even if less than Pads Region M1 M2 M3 M4 M5

14. 14 Check on timing: FEB timing in inner regions FEB average time on M2-M5 R1 regions M2R1 M3R1 M4R1M5R1 Inner regions seems to be well aligned, though there are some FEB’s 3-4 bins apart. To be better studied or….wait for huge statistics and align per channel? It is better to have more statistics anyway 4ns

15. 15 Conclusions -Absolute efficiency everywhere > 99% in 25ns in M2-M5 - Some FV cuts are needed on R1 to correct for limited precision of the prediction near the beampipe hole - At 7 TeV some cuts are necessary to reject “combinatorial” tracks expecially in R1. - Worth while to investigate the reason for low efficiency zones in M3R2 and M4R2, they are there since a long time - Timing needs some touching up, though efficiency is good enough. we have to decide whether go for channel-wise correction as soon as statistics available, or do one or more intermediate steps. To do a refined analysis (cross-talk, choice of the hit to be used, clean tracks…) O(50Mevts) events needed with a stable setting.

16. 16 Spare slides from the old presentations

17. 17 Efficiency calculation Number of clusters found within the defined windows in M4 R1 R3 R4 R2

18. 18 Reminder : efficiency calculation on M2-M5 From each histogram of the #Clusters within the tolerance, the efficiency  and the background probability P bg is extracted by fitting the following function: k=# of clusters If k>0 SUM [(1-  ) P bg k e -Pbg / k! +  P bg k-1 e -Pbg / k-1!] If k=0 SUM[ e -Pbg (1-  Where SUM = Sum of the entries  = Efficiency P bg = Background probability M4 In this way the event-correlated background is taken into account automatically since it is estimated in the vicinity of the track