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Completeness magnitude limit of the OACDF catalogues

The completeness of the detected sample depends on the detection threshold, i.e. how many $\sigma$ must a source be above the background in order to be recognised as a source. The lower this threshold, the larger the number of fainter objects detected and, at the same time, the larger the number of spurious detections caused by noise spikes erroneously identified as sources. For each image in the OACDF dataset, we add a catalogue of simulated objects with known positions and magnitudes, extract a catalogue from the image, then match the output catalogue with the modelled population, and find the magnitude bin at which 50% of the input catalogue is lost.

This procedure, applied to the R-band mosaic of April 1999 with a simulated sample of 3000 objects fainter than R = 22, yielded a completeness limit of 24.6 (c.f. Figure 10).

Figure: Magnitude distributions in the R band for the OACDF2 mosaic of April 1999. The simulated sample, connected by the dotted line, is represented with squares, while the extracted sample is represented with triangles. The solid line represents the magnitude distribution of the modeled sample. The completeness limit is at 24.6.
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Figure: Histogram of detected sources and spurious detections (upper panel) and rate of spurious detections versus the R magnitude (lower panel).
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next up previous
Next: Spurious detections Up: Catalogue extraction Previous: Automatic candidate detections
Juan Alcala
2002-02-05