ProtoDUNE SP ADC Calibration Introduction ProtoDUNE SP TPC ADC Calibration Linearity and NL Measurements Note: Slides updated since 8/15/18 presentation due to mistakes Moving Forward caught by David Adams Richie Diurba (Minnesota) diurb001@umn.edu
Goals ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward • Calibrate the ADCs for the entire detector. • Measure gains, offsets and NL for each channel. FELIX data was not available for APA3 so it will not be included and neither will a few bad channels on the first APA.
pyADCCalib ProtoDUNE SP ADC Calibration Introduction A pyROOT package to calibrate all ADCs from raw data to linearity plots Linearity and NL Measurements • Takes raw data and runs LAr using RunRawDecoder.fcl. Moving Forward • Finds peaks and troughs by scanning over decoded data. • Compiles these peaks across different DAC settings to make a calibration linear fit. • Measures NL and creates summary plots Methodology for scanning function can be found in last talk.
Dataset ProtoDUNE SP ADC Calibration Introduction Linearity and NL Thanks to Flavio and Karol, datasets were made Friday and Saturday. Measurements Moving Forward • gain=14 mV/fC, shaping time=2 us • Made runs with DAC settings 2, 3, 4, 5, 6, and 7. • Each DAC step is 21.4 ke. • For labeling purposes, the highest DAC setting run is used to label datasets. Thanks to Tom for telling me to update my RunRawDecoder.fcl
Sample Plot ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3282 linear fit for channel 7664
Sample Plot ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3282 linear fit for channel 13000 Did two separate fits to minimize DNL. DB team says this is ok!
Gain Measurements ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3282 summary plot for gains with collection channels (left) and induction channels (right)
Gain Measurements ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3258 summary plot for gains with collection channels (left) and induction channels (right)
Gain Comparisons ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward • Run 3282: 144.6 e/count for collection, 140.4 e/count for induction. • Run 3258: 143.1 e/count for collection, 139.0 e/count for induction. Has a 3% uncertainty, so any discrepancy is expected.
DNL ProtoDUNE SP Differential non-linearity defined as the residuals ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3282 DNL measurements with collection channels (left) and induction channels (right)
DNL ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward Run 3258 DNL measurements with collection channels (left) and induction channels (right)
INL Histogram of endpoint INL, due to plotting errors I am only doing collection for ProtoDUNE SP ADC Calibration Run 3282. Introduction Linearity and NL Measurements Moving Forward INL measurements for collection channels for runs ending with 3282. Note: Ignore the abs on the stat box.
Conclusion ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Moving Forward • Gain measurements is approx. 144 e/count for collection channels and 140 e/count for induction channels. • DNL residuals measured to be approx. 4 counts, meets BNL expectations.
Moving Forward ProtoDUNE SP ADC Calibration Introduction Linearity and NL Measurements Jon’s presentation should inform DB requirements. Moving Forward • Clean code so it can be used during runs and fix INL plots. • Bad channel metric. Preliminary considering anything with a DNL above 10 counts is bad.
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