HRC#1 Bias Subtraction and Overscan Analysis (Jun 2000)

AUTHORS : A.R. Martel, G. Hartig, M. Sirianni, J. McCann

PURPOSE :

Our main goal is to determine the most effective method of subtracting a bias frame from HRC data frames for the June calibration campaign at BATC, correct for any residuals, and correlate the physical and virtual overscan levels and their residuals with different parameters such as the data count rates, exposure times, and filter wavelength.

DATA :

The bias frames and flat fields were acquired with SMS procedure JGCH27F as part of the dust filter search. The internal tungsten lamp T4 provided the illumination for the F330W, F344N, and PR200L filters and the D2 lamp for the F220W and F250W filters. All the images were recorded with HRC Build#1 and read-out with Amp C only. At the start of the SMS sequence, bias frame was acquired, followed by pairs of flat fields through each filter. The first flat-field of a given pair is obtained at the nominal filter position and the second image with a filter wheel offset of three steps.

METHOD :

We simply subtracted the bias frame from the individual flat fields. In Table 1, residual mean counts per pixel in the physical and virtual overscans are compiled (cols 7-12). The residual mean (and its standard deviation) of the leading physical overscan was calculated between columns 10-18 and over rows 10-1000 and from columns 1050-1058 and rows 10-1000 for the trailing overscan. The mean of the residual virtual overscan was evaluated from rows 1032-1042 and over columns 100-950. All means in the overscans were evaluated after clipping pixel values that deviate by more than 2.7 sigmas from the mean (cosmic ray hits and hot pixels). The minimum (MIN) and maximum (MAX) pixel values (cols 13-14) in the data regions were evaluated from the histogram of each image. The median (MED) (col. 15) was calculated with the msstat task in IRAF after constructing a pixel mask over the bad pixels/columns. In the tables, only the MIN and MAX of the first image (at the nominal position) of each pair are given since these are essentially the same for both images.

After subtraction of the bias frame, the final bias-corrected image was obtained by removing the mean of the residual of the trailing physical overscan (col. 7) since it exhibits significantly less structure than the leading physical overscan. This assumes that to first-order, the residual is constant over the trailing physical overscan.

RESULTS :

1. Overscan Structures

A straightforward subtraction of the bias frame greatly reduces the leading edge ramp in the leading physical overscan as well as the spike at the far edge of the trailing overscan but it does not remove the parallel CTE effects in the virtual overscan. This is apparent in the following figures extracted from the F220W frame (CSIJ00172234030_1.fits) after bias subtraction (CSIJ00172212400_1.fits).

A small, net, sometimes negative residual remains in the physical and virtual overscans after bias subtraction. The step at row 561 from the bad upper-right bad column is also introduced in the subtraction, in particular in the trailing physical overscan (Figure 9).

• Fig. 1 : F220W, Across Virtual Overscan (cols 100-950, rows 1000-1044)
• Fig. 2 : F220W, Across Virtual Overscan : Blow-up (cols 100-950, rows 1025-1044)
• Fig. 3 : F220W, Across Leading Physical Overscan (cols 1-30, rows 10-1010)
• Fig. 4 : F220W, Across Leading Physical Overscan : Blow-up (cols 1-19, rows 10-1010)
• Fig. 5 : F220W, Across Trailing Physical Overscan (cols 1030-1062, rows 10-1010)
• Fig. 6 : F220W, Across Trailing Physical Overscan : Blow-up (cols 1044-1062, rows 10-1010)

• Fig. 7 : F220W, Along Virtual Overscan (cols 1-1062, rows 1032-1042)
• Fig. 8 : F220W, Along Leading Physical Overscan (cols 10-18, rows 1-1044)
• Fig. 9 : F220W, Along Trailing Physical Overscan (cols 1050-1058, rows 1-1044)

2. Residuals and Correlations

The main difficulty in this analysis is the small number of data points. Only five filters were imaged with HRC and one of them (PR200L) is completely saturated and so is of no use. Moreover, two lamps were used (T4 for PR200L, F330W, and F344N and D2 for F220W and F250W) and so the data set essentially consists of two separate subsets.

a. Median Count Rates

For WFC, we found a strong correlation between the leading, trailing, and virtual overscan residuals with the median count rates of the data regions. Here, we verify if these correlations also hold for the HRC. The relevant quantities are tabulated in Table 1.

In Figs 10-12, we plot the residual count rate in the leading, trailing, and virtual overscans after bias subtraction as a function of the median count rate calculated in the flat field data region. The images of each flat field pair, the first at the nominal filter position and the other slightly offset from it, are treated separately in these plots, hence the obvious 'pairing' of the data points. Unlike the WFC data, no apparent correlation is observed in these figures, except perhaps for the virtual overscan residual (Fig. 12), where the two data points of the T4 lamp (for filters F330W and F344N) appear to correlate linearly. But with only two data points, this possible correlation can not be confirmed or pursued further.

• Fig. 10 : Leading Physical Overscan Residual vs Median Count Rate
• Fig.11 : Trailing Physical Overscan Residual vs Median Count Rate
• Fig. 12 : Virtual Overscan Residual vs Median Count Rate

CEI SPECIFICATIONS :

None.

CONCLUSION :

• The trailing physical overscan is better behaved than its leading counterpart and we therefore remove its mean residual from the bias-subtracted flat fields for the final, corrected image. The leading and virtual overscans are ignored.
• Unlike the WFC, no linear correlation is observed between the residual physical and virtual overscan count rates and the data region count rates in the flat field. A possible exception is the virtual overscan behavior when the flat is obtained with lamp T4 but the data is insufficient for further analysis and confirmation.

REFERENCES :

• Description of the HRC Build#1 detector (M. Sirianni).
• Description of the HRC filters (Z. Tsvetanov)