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Quality Control: Image flats
[ ESO ]
<instr> Quality Control:
Image flats

noise parameters | linearity
 
QC PLOTS
  CURRENT HISTORY
noise parameters
linearity, gain
QC1 database (advanced users): browse | plot
contamination
QC1 database (advanced users): browse | plot
   Click on CURRENT to see the current trending (Health Check).
   Click on HISTORY to see the historical evolution of the trending.


<Here you could have some general introduction, as in this example. This section is optional!>

Image flats (also called detector flats) are measured as technical calibrations every 4 weeks or so as part of the GIRAFFE calibration plan. While the ordinary, daily fibre flats mainly measure fibre characteristics, the image flats are exposures of the CCD by the flat field lamp without the fibre system. Hence, they are used to monitor detector characteristics like

  • CONAD (1/gain),
  • gain variations (px-to-px scale, 'fixed-pattern' noise),
  • linearity,
  • contamination.

<end of optional section>

top Noise parameters

<optional introductory comments>

Two kinds of small-scale fluctuations exist in any raw frame: photon noise, and fixed-pattern (gain) noise (the third source, read noise, is negligible here). While the photon noise can only be reduced but not removed totally, the gain noise is constant with time and can be entirely removed from science frames using gain maps derived from image flats.

<end of optional section>

QC1 parameters

<(Here you should provide information on QC1 parameters - possibly also some which are not trended - that goes beyond the information provided on the Daily Health Check Pages and the QC1 Database. You could provide it in a table, like in this example, or in a list) >

parameter QC1 database: table, name procedure
sph = photon noise giraffe_ccd, sigma_ph - subtract two raw input frames, measure sigma in difference frame, correct by sqrt(2)
- scales with
square root of signal 
sfp = gain (fixed-pattern) fluctuations giraffe_ccd, sigma_fp - take derivative of master frame (shifted by 1 px in both X and Y); measure sigma = sDeriv ; have sfp = sqrt(sDeriv2 - sph2)
- scales with signal

Trending

<(Here you should provide information for trending plots, that is not included in the comment section of the Daily Health Check Plots. There may be plots for which no information needs to be provided here.) >

The measured fixed-pattern noise of the GIRAFFE CCD is about 0.5% (Fig. 1 of the trending plot). It nicely follows a linear slope (Fig. 2 of the trending plot, and also the figure below). The measured photon noise follows a square-root law as expected.

The noise characteristics are not only relevant for Quality Control, but also interesting for data reduction purpose. Whenever it comes to obtain a good S/N, gain maps are used to remove the fixed pattern noise.

The penalty to pay is added photon noise, inherent in the image flats. For a single raw flat file obtained with a typical integration time of 220 sec, the turnover from the photon-noise into the gain noise regime is at exposure level 22000 ADU. This is visible in the figure below. For a master stacked from 2 raw frames, photon noise can be reduced by a factor of sqrt(2), and the turnover is at 11000 ADU. For a stack made of 3 frames, the critical exposure level is at 7000 ADU. This means: if high S/N is an issue, one should take care to use gain maps having sufficiently high exposure level everywhere. In principle it makes sense to attempt a gain noise correction only if the photon noise in the map is lower than the gain noise in the science data.

Some of the GIRAFFE setups have flat fields with rather high dynamics. E.g., a single LR 427.2 flat, being exposed at 110 sec, has parts with just 4000 ADU and other parts being almost saturated.

These issues are neglected by the Giraffe pipeline which accepts whatever input master flat is specified.

Noise properties of the GIRAFFE CCD, as measured in a series of image flats. Data have been bias subtracted. Flats have been taken in a series of exposure times between 1 and 220 seconds.

Fixed pattern noise follows a linear slope (red dots: measurements, broken line: fit).

Photon noise follows a square root law (blue dots: measurements in a single raw file; black broken line: fit).

The intersection between the linear and the square-root curve marks the regime useful for data reduction: data with higher exposure level are useful for gain noise removal, while data with lower exposure level are photon noise dominated.

The example plot here applies to a single raw file. Usually flats are combined from at least three raw files. Stacking reduces the photon noise by a factor sqrt(3), while the fixed-pattern noise is not affected by stacking. By co-adding, the intersection line between the two noise curves can be shifted towards lower values.


top Linearity

QC1 parameters

<(This is an example for a list instead of a table.)>

  • photon noise (QC1 database table giraffe_ccd, column sigma_ph)
    Here you can provide a longer explanation than in a table format.
  • fixed pattern noise (QC1 database table giraffe_ccd, column sigma_fp)
    Here you can provide a longer explanation than in a table format.

Trending

<(This is an example for using pop-up links instead of screen shots.)>

Detector linearity is derived from a sequence of image flats exposed between 1 and 220 secs. Their average exposure level is plotted against the exposure time in box 1. The fitted function (broken line) is used to derive residuals which are normalized to the mean and plotted vs. exposure time in box 3. The normalized residuals are less than one percent except at very low levels.

History

<(Here you can provide information about your instrument - e.g. changes of detector or other components that affect the trending).>

Below find a comparison between the image flats from 2003-04-28 (left) and 2004-06-06 (right). A contamination of about 7% has built up in window 4.

Monitoring contamination: Image flats from 2003-04-28 (left) and 2004-06-06 (right).

top

 
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