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MPPC Measurements at LSU

MPPC Measurements at LSU. Brandon Hartfiel LSU Hardware Group Thomas Kutter, Jessica Brinson, Jason Goon, Jinmeng Liu, Jaroslaw Nowak Sam Reid January 2009 Collaboration Meeting. TFB Darkrate.

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MPPC Measurements at LSU

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  1. MPPC Measurementsat LSU Brandon Hartfiel LSU Hardware GroupThomas Kutter, Jessica Brinson,Jason Goon, Jinmeng Liu, Jaroslaw Nowak Sam Reid January 2009 Collaboration Meeting

  2. TFB Darkrate • We measure darkrate using the TFB. We integrate randomly triggered 250ns gates, fit the pedestal and 1pe to determine the .5 pe level and then count the number of events below .5 pe. We then calculate the • darkrate by • pedestal fraction= exp(-darkrate * gate width) • This calculation assumes that the pulses are randomly distributed in time. Afterpulses are not. Assuming the time distribution of afterpulses is • distributed as an exponential, we can calculate the expected difference between our darkrate method and the threshold crossing rate • ALTERNATE METHOD We also measure the darkrate using the fit values of the pedestal and 1 pe (with 2pe background) instead of using a cut at .5 pe

  3. at 25 C and nominal bias Simple Simulation at 700kHz Thermal rate. No deadtime. No recharge Time TFB Darkrate our rate / threshold crossing rate slope = .86 our TFB rate tau purple limits match Hamamatsu rate afterpulse creation probability all profile plots have RMS errorbars Comparing 20C to 25C cut method fit method darkrate (kHz) 4.2 +/- .4 % per degree Temperature changes are defined as 8.9% per 100mV bias voltage - nominal Relative change per degree C

  4. Scalar Darkrate • A threshold crossing rate is taken for 40 sensors at .5pe with 26ns deadtime (determined by the width of our preamp output) LSU data ratio in purple LSU TFB rate/ LSU scalar rate tau Our Scalar Rate Hamamatsu rate Now the slope is .94 The ratio of slopes for the 2 LSU measurements is .915 afterpulse creation probability black lines are the results from page 12

  5. Gain • The TFB gain is calibrated using the internal calibration system • with the sensors biased at 60V. We appear to have made a mistake • as our gains are consistently 25% high. • Gain is measured between the pedestal and 1pe in LED runs with • and average of 2.5 pe per event • ALTERNATE METHOD We also measure the gain from dark spectra

  6. at 25C and nominal bias Gain sigma 2.9% gain Comparing 20C to 25C 7.7% per 100mV gain -3.7 +/- .2 % per degree LED run Dark run bias voltage - nominal Relative change per degree C

  7. Crosstalk + Afterpulses • Random trigger dark ADC spectra – Pedestal, 1pe and 2pe are fit with Gaussians. • Pedestal fraction is used to predict the 1pe fraction. A deficit implies an excess of • > 1pe events which could be either afterpulses or crosstalk • ALTERNATE METHOD The LED run ADC spectra are fit using a poisson function • modified to includea probability that each original pulse create one crosstalk • or afterpulse.

  8. Crosstalk +Afterpulses 25 C and nominal bias sigma 6.5% relative probability of creating a new pulse Comparing 20C to 25C CT + AP creation probability dark runs LED runs -6.9 +/- .5 % relative per degree 14.9% relative per 100 mV bias voltage - nominal Relative change per degree C

  9. Relative PDE • Three reference sensors are included with every run and always kept at • their nominal bias voltage • The LED ADC spectra are fit using the poisson + AP+ CT function. • The average number of pe is divided by the average for the 3 reference • sensors.

  10. at 25C and nominal bias Relative PDE sigma 3.3% pe / pe of reference sensors Comparing 20C to 25C relative pde -1.3 +/- .4 % per degree 6.0% per 100mV bias-nominal Relative change per degree C

  11. Afterpulses Only (example TA8088 25C) .5 pe threshold crossing rate is measured with different deadtimes after the pulses. This is compared to the expected rate if the pulses were not correlated in time. kHz/ns rate kHz afterpulse rate 138kHz tau = 80 ns black - data derivative of the difference red – fit to expectation if pulses are random in time seen rate=real rate/(1+deadtime*real rate) time since original pulse (ns) deadtime (ns)

  12. Afterpulses Only The “afterpulse probability” is the integral of the fit on the right of the previous page, starting at 0 ns, divided by the intersection of the red line with the y-axis on the left plot. It does not consider the possibility of afterpulses of afterpulses and so is an overestimation of the actual probability. ap creation probability sensor number tau COMPARE WITH PAGE 4 sensor number

  13. afterpulse vs temperature relative change per degree sensor number

  14. Afterpulses vs Bias Voltage for 3 MPPCs 4.5% absolute per 100mV afterpulse probability Bias-Nominal Tau Bias-Nominal

  15. Conversion factors LSU/INR note: these correction are large because different units were used e.g. number of electrons vs number of ADC bins

  16. EXTRA SLIDES

  17. Our Reference Sensors21.5C and Hamamatsu nominal bias

  18. Sensors we received from INR25C and Hamamatsu nominal bias

  19. 1.5 pe and 2.5 pe scalar rates

  20. results vs position dark/hamamatsu dark gain relative pde CT+AP

  21. TA8097 vs day between dec 13 and dec 20 a bad channel was dropping all voltages by .08 this has been corrected for on all other plots

  22. TA8160 vs day between dec 13 and dec 20 a bad channel was dropping all voltages by .08 this has been corrected for on all other plots

  23. TA8120 vs day between dec 13 and dec 20 a bad channel was dropping all voltages by .08 this has been corrected for on all other plots

  24. Bad Sensors • Sensor TE5020 was dropped into an unaccessible place • 11 sensors failed to meet our cuts at least twice. • Some fraction of these failures are probably due to • human error, but we decided to put these aside just • to be safe • one had the wrong bias voltage • two had very bad fits • two have PDE ~35% too high • 6 were only 15% different from normal

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