1. 14/02/2007 Paolo Walter Cattaneo 1 1.Trigger analysis 2.Muon rate 3.Q distribution 4.Baseline 5.Pulse shape 6.Z measurement 7.Att measurement OUTLINE

2. 14/02/2007 Paolo Walter Cattaneo 2 Trigger Data Charge vs Amplitude PMT Key for the Trigger System using pulse height with no information about pulse charge (RUN 236,237,239) Amplitude (a.u.) Charge (a.u.)

3. 14/02/2007 Paolo Walter Cattaneo 3 Charge Inner vs Outer We observe that charge distributions are different between inner and outer PMTs (RUN 236, 237, 239). Charge Inner PMTs Charge Outer PMTs Q (a.u.)

4. 14/02/2007 Paolo Walter Cattaneo 4 Comparison with MC Data DATA MONTECARLO Measured charge distribution for inner PMTs the Montecarlo one are in agreement, as well as the outer ones Q (a.u.)

5. 14/02/2007 Paolo Walter Cattaneo 5 Low energy events on PMT spectrum Bar 16 (first of upstream TC) Outer PMT Bar 19 (fourth of upstream TC) Outer PMT Data Montecarlo Q (a.u.) RUN 236, 237, 239

6. 14/02/2007 Paolo Walter Cattaneo 6 TRG vs DRS height pulse correlation Key for Type3 boards and LXe acquisition, we can see a good linearity until 0.6 mV (0.1 V on DRS  0.4 V on TRG) (RUN 236, 237, 239). (V)

7. 14/02/2007 Paolo Walter Cattaneo 7 We used MC computed acceptance to convert experimental trigger rate to stopped muon rate. Muon rate vs beam intensity MC acceptance including cuts  4.2 % MC acceptance including cuts  3.7 %

8. 14/02/2007 Paolo Walter Cattaneo 8 Bar number 11, run 154 Bar number 6, run 154 Calibrated by superimposing charge peak position of MC events on experimental data Charge distribution (1) Red = Data Black = MC

9. 14/02/2007 Paolo Walter Cattaneo 9 Charge distribution (2) Data wider probably for difficulties of individual software calibration Run 154 Low Intensity Run 236 High Intensity Red = Data Black = MC Charge All bars together

10. 14/02/2007 Paolo Walter Cattaneo 10 Run 154 Low Intensity Red = Data Black = MC Run 236 High Intensity Number of hit bar per event

11. 14/02/2007 Paolo Walter Cattaneo 11 Number of hits on each bar Down stream Up stream Run 154 Low Intensity Run 236 High Intensity 10* KHz KHz

12. In COBRA, with and without Beam; acquisition with oscilloscope of waveform from PMs with single bar triggering, and evaluation of charge ratio for each pulse, with no selection of impact position; distribution of log(Qin/Qout) for each bar reflects event distribution on each bar; width of the distribution is inversely proportional to attenuation length of bar => clue to the applicability of position reconstruction by means of “charge division” Position reconstruction by means of charge ratio – PSI setup charge distribution on a bar from cosmic rays

13. waveform analysis - continue Beam turned on: event distribution on 4 US bars most of the events are on the inner part of the detector; needed calibration of each bar to determine impact point. Inner PMTOuter PMT

14. CAMAC results – position correlations correlation between adjacent bars, distribution of charge ratio on bar 1 for selected impact position on bar 0

15. CAMAC results – position correlations correlation between adjacent bars: US TC (left) and DS TC(right); curves are fit to the data

16. 14/02/2007 Paolo Walter Cattaneo 16 Baseline & noise analysis 1 Search signal pulse Search pulse in the region Fix regionjust before pulse calculate baselineuse database value no yes low threshold Threshold ? Range ? How stable ? How often ? ● averaging ● did not try fitting

17. 14/02/2007 Paolo Walter Cattaneo 17 Baseline & noise analysis 2: Stability Noise level 0.6 ~ 1mV Baseline fluctuation in a run ~0.3mV Baseline shift  with change of beam intensity  with change of trigger type Baseline is stable among same condition runs  We need baseline value in database each run condition. TC no TC high NaI no TC no TC low NaI low NaI high NaI no NaI high baseline fluctuation Baseline run in database already in database for all run

18. 14/02/2007 Paolo Walter Cattaneo 18 Pulse shape of PMT signal Made one template waveform for all channel. Fitting seem to work well ● Not yet making template for each channel ● Feed back to simulation parameter. Use timing extracted by the fit for following analysis.

19. 14/02/2007 Paolo Walter Cattaneo 19 First Look at Beam data Michel positron from beam, TC trigger  2GHz sampling data, high intensity beam (#79,80,81) ● Trigger related pulses are located 120~150 nsec in DRS window.  Trigger latency ~370 nsec, enough for baseline calculation. ● Pulse height : peak ~60mV, tail with Landau Distribution. about 2.2% pulses are saturated. Pulse Timing Distribution Pulse Height Distribution saturated trigger pulse accidental BG all channels 100ns 200ns

20. 14/02/2007 Paolo Walter Cattaneo 20 Z reconstruction Reconstruct z-position by time difference of both side PMTs Roughly estimate ● Effective light velocity (width) ● Relative time pedestal (center) Preliminary

21. 14/02/2007 Paolo Walter Cattaneo 21 Z position correction Effective velocity ~ 15 cm/ns Time pedestals in database Preliminary

22. 14/02/2007 Paolo Walter Cattaneo 22 Relative gain estimation Using spectra, estimated relative gain. Pulse height after correction by position ● Fit with Landau distribution ● Compare the MPV Preliminary

23. 14/02/2007 Paolo Walter Cattaneo 23 Height ratio If pulse height ratio is mainly determined by attenuation length, ● Roughly extracted effective attenuation length  Att ~ 96 cm Preliminary log(H0/H1) = z*2/Att Due to variety of solid angle