A. Filter wheel calibration
B. Tot-to-PE
conversion using the occupancy method
C. Comparison
of occupancy pes and adc pes
D. PMT saturation
E. A
proposed explanation for the difference between occupancy and adc pes
I disconnected from the optical switch the optical
fiber which was collecting light coming from the filter wheel and which
was supplying light to the optical switch. I shined the (laser) light
coming from this fiber onto a 2-inch PMT. Triggering on laser light
detected by a photodiode which is located before the filter wheel, the
areas of the PMT pulses at a particular filter angle were measured using
the digital scope. The digital scope made a histogram of the areas,
and I measured the peak of the histogram. This was done for different
filter angles. When the light level going into the PMT was too high,
the light level was attenuated by using makeshift filters. Though
the absolute value of the PEs detected by the PMT was not known, it was
still possible to get a calibration curve by making several sets of measurements
which overlapped in filter angle. The final calibration curve was
obtained by minimizing the difference in log(area) where the different
data sets overlapped in filter angle. The resulting filter
wheel calibration curve is a plot of log(area) -- which is proportional
to optical density -- vs. filter angle. The slope of log(area) vs.
filter angle for 20 to 110 degrees (the dark part of the filter wheel)
measured through this method agrees with the slope
given by the occupancy method to within 5%.
There's more. I also have a profile
plot of occupancy PEs vs. adc PEs where the PEs were calculated using
high tot. The slope of the line drawn is 1.17, consistent with the
ratio obtained using the low tot.
I guess you are all familiar with the adc method of finding the PEs. Using shower data, an adc distribution is produced for each grid. The adc method makes a fit to the single-PE bump and defines this fit as 1.000... PE. However, the occupancy method will never define this bump as exactly one PE. The occupancy method will give a value slightly larger than one to correspond to this "single-PE" bump. What this value is depends on the effective occupancy that a PMT sees from the shower data. And if the two methods don't agree at one PE, I don't expect them to agree at any other PE.
One thing that Todd pointed out is that the adc distributions were obtained using a 100-tube trigger, which probably means that a tube is hit ~50 percent of the time. It is possible that this 100-tube trigger requirement can cause the effective occupancy seen by a tube to be large enough to shift the adc single-PE peak to slightly larger values. In other words, at a 100-tube trigger, the two-PE contamination of the single-PE bump might be significant enough to shift the fit to the adc peak slightly to the high side.
To check if the number of tubes in the trigger requirement affects the
adc distribution, I compared adc distributions
produced with a 100-tube trigger to adc distributions produced with
a 25-tube trigger. Check out the sample adc distributions for grid
1, grid
2, and grid
150 (a baffled tube -- no I don't mean that the tube is confused, just
that it's wearing a baffle :) ). The upper plot for each grid was
taken using a 100-tube trigger, while the lower plot was taken using a
25-tube trigger (Feb. 15, 1998, by Morgan and Andy). The two data
sets were taken on the same day, about ~5 hours apart. (Note the
shift in the adc distributions by ~5 counts. I have no idea what
caused this.) From the plots, it can be seen that for a 25-tube
trigger, the single-PE bump is not as well-defined as that for a 100-tube
trigger (with about the same number of events for the two distributions).
It can also be seen that the slope of the 25-tube trigger distribution
on the high side of the single-PE peak is steeper than the corresponding
slope for the 100-tube trigger distribution, indicating that there might
be a significant contribution from two-PEs in the 100-tube single-PE
bump.
At Todd's suggestion, I also investigated the effect of two-PE contamination on the single-PE peak of the laser calibration data. Look at the plots of the adc distributions for grid 1, for filter positions 20 to 40 degrees, filter positions 50 to 70 degrees, and filter positions 80 to 100 degrees. The plots give the occupancy of each distribution and the corresponding mean of the gaussian fitted to the peak of each distribution. Just so you can orient yourselves, for an occupancy of 0.85 (histogram 1090), there is ~24% probability for one-PE events, and ~27% probability for two-PE events. I have plotted adc counts minus pedestal (357.5 for this grid) as a function of occupancy. There are similar plots for grid 116, grid 6, and grid 134. The plots show that starting at an occupancy of about 20 to 30 percent, the fits to the peak shift as a function of occupancy, indicating that two-PE contamination of the single-PE peak causes shifts in the fits.
(The adc distributions for grid 116 are also available: filter 10 to 30, filter 40 to 60, filter 70 to 90, filter 100).
That's it. That's how I propose to explain the difference between the occupancy and adc pes. I think it all boils down to how the two methods define the adc "single-PE" bump. The adc method calls it 1.0000... PE; the occupancy method calls it, on the average, 1.17 PEs because of the occupancy of the shower data at a 100-tube trigger. What do you think?
I hope you're not as baffled as I am -- and I don't mean that I'm wearing a baffle!