Solving pedestal problem Mauro Raggi Sapienza Universita’ di Roma

Observing no beam time run654 Observed the pedestal in events in between 2000-3000 and 9000-10000 when linac is switching from electrons to positrons Try to compare the prediction of Average of 100 samples to the average of all 1000 samples.

Different pedestal evaluation Average of 1000 sample much more stable within groups of events and in between the two samples. Shape of the red distribution (Avg100) much broader and with different shape in the two samples Average of 1000 better estimate of the pedestal! 2000<evt<3000 9000<evt<10000 Avg 1000 samples Avg 100 samples Avg 1000 samples Avg 100 samples

Effect on the charge Converted the difference into Charge to see if it was the right scale for Qped summing on 1000 samples: Qdiff=(-PedCh[7]+MeanCh[7])/(4096*1.)/50*1.e-9/1e-12*1000. Wow seems of the right scale!

Correct the effect Reconstruction Program Offline program Define a sample of pseudo pedestals by asking: abs(Avg100- Avg1000)<3 counts Fill histograms with Avg1000 Offline program Fit Avg1000 histogram with gaussian Get ped value in counts for each channel Reconstruction program Define a pedestal vector PedCh[ch] and fill it with fitted value SamRec[s] = (Double_t) (chn->GetSample(s)-PedCh[ch])/4096*1.; QCh[ch]+= - SamRec[s]/50*1E-9/1E-12; Residual effects The precision on the pedestal in counts is ~1/sqrt(12) cnt going to charge: charge we get for 1000s: 0.3/4096/50*1e-9/1E-12*1000 = 1.5 pC rms

No more double pedestal peak

Fitting the pedestal Ch QMax Qfit PedQ 0 = 1.375 1.54139

Zero of the pedestal distribution

Improving the correction Turn the Pedestal into a double variable You can bin the histogram well below the 1 count level thanks to the average and fit the pedestal distribution with a gaussian Use floating points values for the pedestal in the computation.

Pedestal fits for run 669 Ch hMax pedfit Ped 0 = 3769.65 3769.59 We most probably don’t need to fit at all the Histogram max works very well.

Improved pedestal fit run 669 Gaussian pedestal with average 1.3 pC sigma Mean pedestal is at zero with 0.2 pC precision!

Time stability tests run 669 Time dependent oscillations of the order of a fraction of a count can be observed. They reflect on different values of the pedestal in different runs. Further sub pC threshold in charge maybe achievable by following time variation inside the same run. Ch7 run 669

Pedestal zero run 661 Using pedestal calibration from 669 into 661 a worst quality of the pedestal 0 is obtained. Pedestal sigma still of the order of 1.5pC. Need run by run calibration of the to get the best zero alignment. Mandatory if a zero suppression has to be applied at LvL1

PED trend ch7 run 661 Real fit value 3766.34

Linearity

Total Charge 100 MeV after pedestal calibration Very good spectrum for the low energy photon with reasonable energy scaling. End point at around 20 MeV Low energy photon spectrum

Applying zero suppression Effect of a 5 pC ~4s zero suppression on each of the crystals produces a remarkable improvement of the resolution. With proper calibration of the pedestal zero suppression is a useful tool at low energy

Out of run pedestal distribution 2000<Nevt<4500 || 8000<Nevt <12000 || 32000<Nevt<33000 || 44500<Nevt <46500" Data coming from different times but still 1.1 pC rms Pedestal is stable in the same run!

Predicted co60 spectrum Co60 spectrum obtained by calculating response for 1.1 and 1.3 MeV photon with 13.8 pC/MeV introducing a fluctuation of 1/sqrt(100*E) on the photoelectron. Data pedestal Expected Co60 signal with 100 pe/MeV

Conclusion The average of 1000 samples in empty events provides a stable pedestal Stable in time Very small 1.3pC RMS (~100 KeV) and no double peak. The linearity seems good and the spectrum of low energy photons shows the expected drop with energy. end point of the spectrum around 20MeV. With new pedestal I expect that Co60 source can be used for calibration porpouse.