1 / 29

Initial Analysis on PV1 13h Data

This analysis provides a preliminary understanding of PV1 data, including waveform patterns, threshold variation, and the need for synchronization between RO and HV events.

clifforddavis
Download Presentation

Initial Analysis on PV1 13h Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Initial Analysis on PV1 13h Data Claudio PPS meeting January 4, 2011

  2. Data Taking • PV1 overnight data acquired 13h 46’ 12” Dec10 21:24:09  Dec11 10:10:21 • Source + Plexiglas collimator on RO10 x HV20 • Gas mix: AR 99% + CF4 1% at 700 Torr • Investigated lines: RO 1013, HV 2023 • Two DRS4’s commonly triggered for RO/HV into two independent .XML files + trigger time from the scope controlled via LabView into a .txt file • All data into a TTree (new ROOT solving the XML engine breaking for long DAQ periods) • Initial data analysis on the ROOT TTree PV1 Data Analysis - Claudio

  3. Typical Event Waveforms rebuilt from data stored into the TTree Yiftah’s Hit definition: min (HV)<-190 mV + min (RO)<-50mV in this event HV20 x RO10 (source position) PV1 Data Analysis - Claudio

  4. Usual Plot: Counts/min Correctly max #count/min where the source was placed ! PV1 Data Analysis - Claudio

  5. Understanding Events • Next: events with unusual waveforms. Caveat: there is no synchronization between RO & HV readout lines (independent DRS4)  since the number of events in the two .xml files are different (by 1) you could see HV and RO signals unmatched (coming from different events). • Seen: large peaks, double hits, messy HV/RO waveforms, late second hit, ... PV1 Data Analysis - Claudio

  6. Possible Mismatch Hit on two different HV lines with single signal on RO lines Next event, single HV peak but two hits on two different RO lines PV1 Data Analysis - Claudio

  7. Wide RO Peak PV1 Data Analysis - Claudio

  8. Double Peaked RO hit PV1 Data Analysis - Claudio

  9. “Messy” HV PV1 Data Analysis - Claudio

  10. Double HV (Same Line) PV1 Data Analysis - Claudio

  11. Double RO (Same Line) The code currently handle this case as a single hit (N.B. event after the previous with 2 HV spikes) PV1 Data Analysis - Claudio

  12. Double HV (Different Line) PV1 Data Analysis - Claudio

  13. Double RO (Different Lines) The code currently handle this case as two hits (N.B. event after one with 2 HV spikes) PV1 Data Analysis - Claudio

  14. “Real” Double Hit PV1 Data Analysis - Claudio

  15. Late Second Hit PV1 Data Analysis - Claudio

  16. Understanding Data • The HV and RO cuts defining a Hit are somewhat arbitrary: can we choose better values ? • Answer: the next plot shows the minimum of each line RO/HV, starting from the smallest (index 0) • How the pixel measured counts per minute depends on this definition ? • Answer: the next series of CPM 3D plots show quantitatively the variation due to different cuts PV1 Data Analysis - Claudio

  17. Ordered Min RO and HV WHAT HAPPENED ? PV1 Data Analysis - Claudio

  18. EV 13071308 HV line 22 (yellow) went dead around 1:22 am ! PV1 Data Analysis - Claudio

  19. EV 1497 Same HV line 22 beck alive around 1:57 am for a single hit and dead again! PV1 Data Analysis - Claudio

  20. EV 1634  1635 HV line 22 (yellow) back alive around 2:30 am ! PV1 Data Analysis - Claudio

  21. EV 2312  2313 HV line 22 (yellow) went definitely dead around 5:06 am ! PV1 Data Analysis - Claudio

  22. CPM: HV Threshold Variation HV<-150 mV && RO<-50mV HV<-160 mV && RO<-50mV HV<-170 mV && RO<-50mV HV<-180 mV && RO<-50mV PV1 Data Analysis - Claudio

  23. CPM: HV Threshold Variation (2) HV<-190 mV && RO<-50mV HV<-200 mV && RO<-50mV As expected from the min HV graph, a cut between -150mV and -170 mV impacts the number of hits, in particular because of two periods where the typical HV peaks are reduced (by ~20 mV). Below -170 mV the number of hits per minute is more or less constant! PV1 Data Analysis - Claudio

  24. CPM: RO Threshold Variation HV<-150 mV && RO<-50mV HV<-150 mV && RO<-60mV HV<-150 mV && RO<-70mV HV<-150 mV && RO<-80mV PV1 Data Analysis - Claudio

  25. CPM: RO Threshold Variation (2) HV<-150 mV && RO<-90mV HV<-150 mV && RO<-100mV As expected from the min RO graph, a cut between -50mV and -100 mV do not impacts the number of hits! RO cut value -50 mV  -100 mV HV cut value -190 mV  -170 mV  -150 mV PV1 Data Analysis - Claudio

  26. CPM in Time (-100x-150 mV) X-axis= time [0,772’] Y-axis=CPM [0,7] PV1 Data Analysis - Claudio

  27. Hit RO Peak Voltage X-axis=V peak [-300,0] mV Y-axis (log) = #entries PV1 Data Analysis - Claudio

  28. Hit HV Peak Voltage X-axis=V peak [-300,0] mV Y-axis (log) = #entries PV1 Data Analysis - Claudio

  29. Conclusion • The synchronization of the RO and HV events is fundamental to understand the signal and the real number of hits. Solution: re-compile the DRS4 code with “an event time-stamp” in the .xml output (not optimal, to be tested) • The data analysis code should include automatic flagging of double hits, unusual patterns, ... (more plots) • Waveform study on a DAQ period with the same #RO and #HV events (already on hand and Ntuplized) PV1 Data Analysis - Claudio

More Related