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Conversion Factor | Fixed-Pattern Noise

 
HC PLOTS
conversion factor
fixed-pattern noise
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Parameters are measured for the 5 standard filters BVI Bessell and UR_SPECIAL FORS2 screen flats, and for the standard CCD modes (100Kps/high_gain/2x2 and 200Kps/low_gain/2x2).


Conversion Factor
Conversion Factor | Fixed-Pattern Noise

QC1_parameters

FITS key QC1 database: table, name definition class* HC_plot** more docu
QC.FLAT.CONAD fors2_scrflat..conad measured CONAD HC [docuSys coming]
*Class: KPI - instrument performance; HC - instrument health; CAL - calibration quality; ENG - engineering parameter
**There might be more than one.

Trending

The CONAD/GAIN conversion factor is trended here. The values are estimated from the FORS2 screen flats. For historical reasons (different control software) the CONAD and GAIN parameters are often confused. What is called CONAD here is really the GAIN parameter (units e-/adu).

Scoring&thresholds Conversion Factor

The CONAD/GAIN conversion factor is scored tightly with static thresholds following the median average of the current period. The requirement is stability over time.

History

2010-11-04 - 2010-12-01: The flat field lamp saturates the screen flats. Therefore there are no valid data for that time range.

The old pipeline in use until 2008-03-31 derived the CONAD somewhat differently: the whole readout port was divided into a chessboard of 16x16 boxes. For each one of these boxes, the median signal level from the first raw frame was divided by the variance in the difference frame scaled by 2. The median value of the 16x16 values obtained was the accepted value for the conversion factor.

For the old FORS2 CCD (until March 2002) the conversion factor was derived from a raw file as 100x100 pixels sigma, corrected for fixed-pattern contribution. The sigma was compared to the square-root of the signal averaged across 4 ports. The conversion factor was trended only for the R_SPECIAL filter.

Algorithm Conversion Factor

If the exposure time of the first two raw screen flat fields in the input set of frames is the same (within 4%), the difference frame is computed. Then, the whole readout port is divided into a chessboard of 16x16 boxes. For each one of these boxes, the median signal level from the first raw frame is divided by the variance in the difference frame scaled by 2. The median of the 16x16 values obtained is the conversion factor in e-/ADU. For historical reasons (different control software) the CONAD and GAIN parameters are often confused. What is called CONAD here is really the GAIN parameter (units e-/adu). The CONAD (units ADU/e-) can be calculated as the reciprocal mean of this value.


Fixed-Pattern Noise
Conversion Factor | Fixed-Pattern Noise

QC1_parameters

FITS key QC1 database: table, name definition class* HC_plot** more docu
QC.FLAT.FPN.REL fors2_scrflat..FPN_rel fixed pattern noise normalized by flux in same region HC [docuSys coming]
*Class: KPI - instrument performance; HC - instrument health; CAL - calibration quality; ENG - engineering parameter
**There might be more than one.

Trending

The fixed-pattern noise is trended here. It is dominated by the brick wall like pattern in the MIT-CCDs, due to the CCDs thinning procedure. It is particularly strong in U. The fixed-pattern noise is trended only for the B_BESSELL filter.

Scoring&thresholds Fixed-Pattern Noise

It is scored loosely with fixed thresholds following the median average of the current period. The requirement is stability over time.

History

2010-11-04 - 2010-12-01: The flat field lamp saturates the screen flats. Therefore there are no valid data for that time range.

For the old FORS2 CCD (until March 2002) following figures and table provide information gained from imaging screen flats:

parameter procedure applicable actual values plot (No. in plot)
efficiency E (ADU/s) media/exposure time master 10000 (BVR), 1000 (U) acrean flat 1a,b
photon noise sph (ADU) difference of 2 raw files, s in 100x100 window raw 100-150 ADU at 20000 ADU screan flat 2a
fixed-pattern noise sfp (ADU) total s in 100x100 window, subtract photon noise (squared under root) raw/master 100-150 ADU at 20000 ADU screan flat 2b
fractional port difference sAB (%) fractional s across ports A and B raw/master, 4 port only 20 - 25 % screan flat 3
photn noise vs. flux plot 2a vs. median raw scale as 0.5%*(signal/20000)^1/2 screen flat 4a
fixed-pattern noise vs. flux plot 2b vs. median, per filter raw/master scale as 0.5%*(signal/20000) screen flat 4b-f

Algorithm Fixed-Pattern Noise

The fixed-pattern noise is computed in the following way: The difference of two 100x100 sub-frames of the same master flat field image is determined. These two sub-frames are are shifted with respect to each other by 10 pixels in X- and Y-direction. The population standard deviation of the difference frame, divided by the square root of 2, minus the photon noise (geometrically subtracted) yields the fixed-pattern noise, which is then divided by the median of the respective region.


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