M2-M5 Efficiencyand Timing checks on 7TeV beam data

Alessia, Roberta

R.Santacesaria, April 23rd , 2010- Muon Operation meeting@CERN

2

Efficiency 7TeV data for M2-M5

Method reminder:

- MuonTrackRec standalone reconstruction using 4 stations,

- Look for Clusters in the 5th station within 6around the prediction, no time cut

- Assume the found cluster multiplicity distribution is due to efficiency + poissonian background

- Fit with this assumption

TAE noTAE

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

- 6fiducial volume cut in the inner border of R1 - 6fiducial 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 RegionHV=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 excludedHV=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 Cathodsin 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 tracksdue 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 cutsHV=optimal, noTAE no cleaning cuts ~1.5% lost on M3R1, ~0.5% on M4R1HV=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 regionsM2R1 M3R1

M4R1 M5R1

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-M5From each histogram of the #Clusters within the tolerance, the efficiency and the background probability Pbg is extracted by fitting the following function:

k=# of clusters

If k>0SUM [(1-) Pbg

k e -Pbg / k! + Pbg

k-1 e -Pbg / k-1!]

If k=0SUM[ e -Pbg

(1-

WhereSUM = Sum of the entries = EfficiencyP bg= Background probability

M4

In this way the event-correlated background is taken into account automaticallysince it is estimated in the vicinity of the track