Two analyses, look for a signal, meaure the fractions of 1/9 and 4/9 MIP events to 1 MIP events.

To look for the signal, need to see the "Bumps" in uncorrected distributions of the average MIP signal from the WITNESS counters. May need some cuts, but data is pretty clean anyway.

To quote the fractions, need 3 numbers from the DATA samples

• Number of 1/9 MIP events
• Number of 4/9 MIP events
• Number of 1 MIP events corrected for the single MIP trigger efficiency
These numbers could be the number of events seen in windows near +/- 0.1 MIPs around the 1/9, 4/9 and 1.0 bins.

## To measure the integrated luminosity in single MIP events

Use the scalers which counted the T1&T2&T3&T4 counts. As the cut off for the DATA events eats in to the MIP signal - we can get the number of MIPs from the scalers. The T1&T2&T3&T4 scaler was recorded per spill (and per run). This count is proportional to the number of MIPs seen by the experiment. The constant of proportionality can be measured for the MIP runs and applied to the DATA runs to measure the number of MIPs seen per run. We can also fold in the computer busy to this luminosity.

### Uncorrected plot

Simply plot the average of the WITNESS counters in MIPS for all the data runs. There are no "bad events". Do we need to define the fiducial volume, cut on the "hole" scintillator ? (asking for a signal in each of the WITNESS counters is enough).
Cuts
• All WITNESS scintillators must be > .05 MIPS (to remove noise) whats the probablity of getting 0 for a MIP ? Counter efficiency is the probability of a Poisson fluctuation of the number of photo-electrons down to 0.
• Only take counters < 1.2 into the average- otherwisre the overflows can be seen as 7 distinct bumps in the average plot.
#
Total Number of DATA events
7 Witness Counters > 0.05 MIP
Average of WITNESS counters between 0.90 and 1.20

# Method to extract the Luminosity in MIPS

• Measure the number of MIPs in the MIP runs.
• Count the value of
```L = TRIGGERS W/O COMPUTER BUSY * T1&T2&T3&T4
--------------------------
TRIGGERS
```
For each spill, and sum for each run, to get the integrated luminosity per run.
• Count the number of MIPs per MIP run, and calculate the conversion factor to get the luminosity into number of MIPs for each DATA run.

#### MIPS runs

155,231 Events, Mean 1.038.

#### DATA runs

417,108 events, Mean=0.499

# To Do

• Explain tail on MIPs plot - photon showers ?
• Explain bumps on DATA plot - detector posn dependent ?
• Most of the PASS events are from the 1st 2 runs, before the detector was moved down 15'' from the beam line
• The last run was exceptionally clean - when detector was furthest from the beam line
• Group the Data runs together to find where the bumps are coming from.
• Calculate # MIPs in MIPs plot
• Sum all values to get conversion factors - normalised MIPs
• Why arent the T1&T2&T3&T4 numbers the same as the W/O Busy numbers in the MIPs runs ?

#### DATA runs for runs over 17

121,594 events, Mean=0.528

Removing the first 2 runs - when the detector was moved down, away from the beam line, there are fewer events which pass the cuts compared to the number of events in the runs. The distribution now has fewer bumps in it - mainly a bump at 1MIP, a central mound at 0.5 MIPs, and a small shoulder at .1 MIP.