Quality Control and
Data Processing

HC PLOTS
Linearity
QC1 database (advanced users): browse | plot

Trending of detector monitoring is based on measurement of the QC1 parameters of Detector Linearity calibration data. They are obtained with a dedicated Health Check OB executed approximately once a monthly. The Detector Linearity OB consits of 10 sets of data - each set is one DARK and two Imaging FLAT FIELD frames taken with the same DIT. The DIT is gradulally increased from set to set to increase the flat flux level. The data are obtained with the Ks filter using the Nasmyth shutter as a source: its flux is then dependent on the ambient temperature as expected from the Planck law.

As of 2016-09-28 only the effective linearity is monitored. The conversion factor (conad/gain) measurements were found unreliable. The corresponding HC plot was taken off-line untill template and/or pipeline recipe are improved.

The monitored effective nonlinearity is a difference at 10 000 ADU between the flux obtained from the 2nd order polynomial fit of flux vs. exposure time and the flux predicted by the linear term only, normalized by the polynomial flux.

QC1_parameters

FITS key	QC1 database: table, name	definition	class*	HC_plot**	more docu
QC.LIN.EFF	hawki_detlin..qc_lin_eff	effective linearity	HC		[docuSys coming]
*Class: KPI - instrument performance; HC - instrument health; CAL - calibration quality; ENG - engineering parameter **There might be more than one.

Trending

The effective linearity is trended for each detector separately. Also, value averaged across all 4 chips and its standard deviation are monitored.

Scoring&thresholds Effective linearity

In general, the effective linearity is relatively stable. Outliers are likely to be due to variations in the flux level as there is no constant source of light available.

History

Date	event
mid-September 2014	indication of problem with non-linearity in all chips (followed in PPRS-05910); it was fixed and data taken on 2014-10-10 scored "green" again
August 2015	all parameters nominal after GRAAL installation
2016-09-28	Analysis of the detector monitoring data sets showed that the gain measurements cannot give reliable estimates. The QC_GAIN monitoring HC plot is taken off-line untill template and/or pipeline recipe is improved.

Algorithm Effective linearity

The effective non-linearity is the difference between the polynomial flux and the one predicted by the linear fit at user-defined flux level, normalized with the polynomial flux