# Pedestal histograms for one complete run, for all four ranges of this CFE. Repeat this for a neighboring CFE.

## GemConditionsWord==32 for r0264694008 and CalXtalID(14,4,0) using POS sides only

Mean/RMS for adcp0 is 582.102277 / 77.870177

Mean/RMS for adcp1 is 231.229641 / 59.862071

Mean/RMS for adcp2 is 512.500579 / 7.685434

Mean/RMS for adcp3 is 204.602856 / 0.998327

Gaussian fitting is difficult to make converge, hence the fit is constrained in the interval mean-2*rms,mean+2*rms

Mean/RMS for adcp0 is 582.102277 / 77.87017 Gaussian fit mean RMS 581.153117 5.609077

Mean/RMS for adcp1 is 231.229641 / 59.86207 Gaussian fit mean RMS 230.686616 0.829612

Mean/RMS for adcp2 is 512.500579 / 7.685434 Gaussian fit mean RMS 512.871404 3.383572

Mean/RMS for adcp3 is 204.602856 / 0.998327 Gaussian fit mean RMS 205.084367 0.602602

*adjacent channel

# 2D histogram (or scatterplot) of pedestal v. time since previous readout for all four ranges of this CFE for one complete run. Start with the x1 ranges. Stop if it's obviously uninteresting. Repeat this for a neighboring CFE.

All 4 ranges versus DeltaEventTime. There is a noticeable deltatime-dependent effect, with the pedestal becoming smaller when deltat increases.

*adjacent channel

# Time series of pedestal for all four ranges of this CFE for one complete run. Start with the x1 ranges. Stop if it's obviously uninteresting.

All 4 ranges versus trigger time. No noticeable time-dependent effect.

# Comparison of LEX1 in noisy and quiet run for LEX1

left: noisy, right: quiet

No noticeable differences in the pedestal fits. Note however that on the raw histograms:

noisy RMS is 34.672148

clean RMS is 2.030238

There are a few upper and lower outliers in the "noisy" run so when I cut lex1 to >100 and <1000 I get

noisy RMS is 2.137363

clean RMS is 2.030238

# Comparison of cut on distribution statistics

Noisy run

Mean/RMS for adcn0 is 522.198370 / 45.660070

Mean/RMS for adcn1 is 198.362319 / 22.961862

Mean/RMS for adcn2 is 430.747800 / 4.349292

Mean/RMS for adcn3 is 212.980719 / 0.604945

Mean/RMS for adcp0 is 581.069746 / 45.380801

Mean/RMS for adcp1 is 230.566253 / 34.672148

Mean/RMS for adcp2 is 512.517857 / 5.275627

Mean/RMS for adcp3 is 204.628235 / 0.779602

Not noisy run

Mean/RMS for adcn0 is 521.426602 / 15.194472

Mean/RMS for adcn1 is 198.049501 / 2.361731

Mean/RMS for adcn2 is 430.746586 / 3.423744

Mean/RMS for adcn3 is 212.976366 / 0.519290

Mean/RMS for adcp0 is 580.000000 / 15.111143

Mean/RMS for adcp1 is 229.865940 / 2.030238

Mean/RMS for adcp2 is 512.040047 / 3.405283

Mean/RMS for adcp3 is 204.285058 / 0.539917

Noisy with cut on adc<1000

Mean/RMS for adcn0 is 521.471715 / 11.076650

Mean/RMS for adcn1 is 198.102498 / 2.370902

Mean/RMS for adcn2 is 430.747800 / 4.349292

Mean/RMS for adcn3 is 212.980719 / 0.604945

Mean/RMS for adcp0 is 580.307742 / 13.940864

Mean/RMS for adcp1 is 230.175100 / 4.464143

Mean/RMS for adcp2 is 512.517857 / 5.275627

Mean/RMS for adcp3 is 204.628235 / 0.779602

Not noisy with cut on adc<1000

Mean/RMS for adcn0 is 521.294550 / 9.904404

Mean/RMS for adcn1 is 198.049501 / 2.361731

Mean/RMS for adcn2 is 430.746586 / 3.423744

Mean/RMS for adcn3 is 212.976366 / 0.519290

Mean/RMS for adcp0 is 579.878661 / 10.781662

Mean/RMS for adcp1 is 229.865940 / 2.030238

Mean/RMS for adcp2 is 512.040047 / 3.405283

Mean/RMS for adcp3 is 204.285058 / 0.539917