Plot 5 scores: 1|
data source:	crires_detmon (QC1 database)
dataset:	counts_max	•
average:	none
thresholds:	none
N_data plotted:	49
[click on plot for closeup]

Plot 6 scores: 1|
data source:	crires_detmon (QC1 database)
dataset:	counts_max	•
average:	none
thresholds:	none
N_data plotted:	49
[click on plot for closeup]

Plot 7 scores: 1|
data source:	crires_detmon (QC1 database)
dataset:	counts_max	•
average:	none
thresholds:	none
N_data plotted:	49
[click on plot for closeup]

Plot 8 scores: 1|
data source:	crires_detmon (QC1 database)
dataset:	counts_max	•
average:	none
thresholds:	none
N_data plotted:	49
[click on plot for closeup]

Trending plot for non-linearity measurements of the CRIRES detector.

Data are taken from detector monitoring calibrations which are series of flat fields with increasing DITs and corresponding darks. A second order polynomial is fit to the data (flux vs. exposure time for each pixel). The trending shows the average effective non-linearity at 6000 ADU and the maximum exposure level (in ADU) from the frame with the highest DIT. Effective non-linearity is the difference between the flux predicted at 6000 ADU by the linear term and the flux obtained from the polynomial, normalized by the polynomial flux.

The average effective non-linearity should be less than 0.1. In order to correctly calculate this parameter, the maximum flux should be above 6000 ADU on all detectors. It should also be below 12000 ADU because the CRIRES array becomes highly non-linear above.