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We combined all bias frames to create an average master bias frame for each night and each chip. After several tests we decided that the bias subtraction had to be performed in two steps; we first subtracted the overscan level by fitting a second order polynomial to the columns and then subtracted the overscan subtracted master bias frames. The second step successfully removed the remaining bias structures for chips 1, 2 and 4.

Chip 3 suffered from a few bad columns. These were removed by interpolation or by aligning and combining the images taken with a small offset. The rms noise level in the master bias frame was negligible compared to the rms noise in the science frames. Accurate flat field images were created from the science frames.

We have obtained 52 science images of the Coma area per chip per band for the B and r bands. For the U band we have 23 science images, including the empty fields. We constructed a B and r band master flat by scaling these images by the mode, rejecting the lowest 10 and highest 15 pixel values, followed by median filtering.

The U band master flats were constructed in the same way, but there we rejected the lowest five and highest 10 pixel values before median filtering. After flat fielding, approximately 2. Because of the overlap between neighbouring pointings, this has very little impact on our final mosaic. On average the images are very flat, with less than 0. Photometric calibration The ultimate aim was to obtain a homogeneous photometric scale over the whole area covered.

We dedicated the photometric anchor point to be chip 4 of pointing 11 Fig. This field was observed during the first night under photometric conditions at a time close to when the standards were taken. First, we determined the photometric offsets between the four chips of the WFC, using objects in overlapping regions between the two offset exposures for each pointing.

For the U band, the number of bright objects in overlapping areas was low. Therefore, we could not use objects to determine the offsets, because this would have given unreliable results. Instead, we used the sky level to determine photometric offsets. First, we made sky images by filtering out all objects of the science images in the same way as for the flat fields. Comparison of the mean sky levels of the sky images gave the offsets. The resulting offsets are listed in Table 1. Errors indicate the uncertainty in the mean of all the independent measurements.

The offsets depend on the passband, because the response curves of the four CCDs are not identical. Table 1. Open in new tab Download slide Photometric offsets relative to chip 4. We applied these offsets to bring all chips to the same scale. Only the first two nights were photometric and we proceeded by determining the photometric offsets between neighbouring pointings. The mean offset values are based on the eight or more brightest objects in the overlapping areas in order to guarantee a reliable determination.

We found differences of a few hundredths of a magnitude between fields taken at significantly different times airmasses, conditions in B and r up to more than a tenth of a magnitude in U. We mapped all the photometric offsets per pointing per band and scaled all pointings in such a way that the errors were spread over the total observed region and did not accumulate towards the edges of the covered area. This is shown for the r and U bands in the right hand panels of Fig.

Figure 3. Astrometric and magnitude scatter in the r and U bands for objects in overlapping regions. The circle denotes the astrometric accuracy. The photometric calibration was performed using Landolt standard stars. We did not have sufficient standard stars on all the chips to solve for the extinction coefficients so we set the extinction coefficients to constant values.

The zero points are listed in Table 3. Because Coma lies close to the galactic pole, the extinction is insignificant for our purposes 0. Hence, we did not apply extinction corrections. Table 2. Average extinction coefficients for La Palma. Table 3. Zero points ZP of chip 4 for night 1. Object catalogues The data volume is considerable and requires a fully automated pipeline for data handling.

After the standard reduction steps, the processed images were presented to software implemented at the Leiden Data Analysis Center LDAC for pipeline processing of overlapping images Deul The processing software is a series of programmes that, when run in a chain, derive source parameters for any given set of input frames of a given passband. Only the first step is an actual data reduction task in that it reduces the information to be processed from image data to catalogue data an object list.

All but the last of the following pipeline routines add information to the catalogue s increasing its size and information content. The final step merges the catalogues to create a multicolour object catalogue with astronomically meaningful source information. The pipeline processing is performed on the full data set. Along the way we must decide on values for various parameters. We describe the pipeline steps in more detail below.

Detection of objects We used SExtractor to automatically detect objects on each chip individually. The complete analysis of an image is achieved in six steps. First, a model of the sky background is built and parameters describing the global statistics are estimated. Then the image is background subtracted, filtered and thresholded. Detections are then deblended, cleaned, photometered, classified and written to the final catalogue. Objects were identified as the peaks in the background subtracted convolved images that were higher than a given threshold above the local background.

We used most of the standard SExtractor settings except for the memory parameters which had to be increased in order to detect the large cD galaxies successfully. SExtractor produced a catalogue for each image which was subsequently converted to a format suitable for pipeline reduction. As a first pipeline processing step, all information of the individual image source extractions plus all original fits image header information is combined into one single output catalogue per band. Astrometry Astrometric calibration was performed by pairing the input position catalogue USNO A2 with the extracted object information.

For multiple band processing intercolour pairing is done first and between frames in overlap, overlap pairing is performed as well. The derived astrometric solution is then applied to all the objects in the set of frames. Sky coordinates RA and Dec. The final precision of this calibration depends on the accuracy of the source extractions, input catalogue accuracies and the correctness of the functional description of the distortions.

We find as shown in the left hand panels of Fig. We have too much of it and too much of it requires external financing. With the failure of the balanced budget amendment in Congress and the US association with Mexican peso problems, the dollar is taking a pounding. Foreigners will not be wanting to purchase dollar denominated debt without a lot higher couponed rate of return.

There have also been many references I have read lately to a growing global liquidity squeeze. The next major California quake which a number of people have predicted for later this year would compound the problem if it occurs. Even without the California quake these things mean we will have more debt and more competition for the money to finance it.

This does not protend lower long rates. It is market driven and the supply of debt is exceeding the demand, especially with our trade deficit flooding the world with dollars which are rapidly becoming worth less

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