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

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

8 M4R2 Low efficiency due to two dead channels

9 Q4M4R2H1 2 Dead channels

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 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 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 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 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 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 Spare slides from the old presentations

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

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