Discusión de Resultados

Photometry quality is dependent on the size of aperture used; the brighter a star is, the more easily the stellar point spread function (PSF) can be distinguished from the background level. For a brighter star the counts recorded in a larger aperture will be more dominated by the star than the background; the optimal aperture is larger. For dimmer stars the background dominates more easily and so a smaller

Table 3.1: Comparison of the number of stars per field observed with WASP-South before and after the lens change. The values given are the median and median square deviations for 108 fields observed with 200-mm lenses and 28 fields observed with the 85-mm lenses. Values have been rounded to the first significant figure of the median square deviation.

Stars in field 200-mm lens fields 85-mm lens fields

Total _{53000 ± 20000 30000 ± 5000} WASP magnitude < 13 _{11000 ± 5000 22000 ± 5000} WASP magnitude < 9 _{80 ± 40 800 ± 200} Precision < 1% _{2000 ± 700 1000 ± 200} -2.5 -2 -1.5 -1 -0.5 0 0.5 1 6 7 8 9 10 11 12 13 14 15 log(RMS) USNO-B R2 magnitude 85mm 200mm 85mm median 200 median

Figure 3.3: Log(RMS) vs USNO-B R2 catalogue magnitude for same nights and fields as Fig. 3.1.

aperture excludes the background variation more effectively; the optimal aperture is smaller (Naylor 1998). While it would arguably produce better photometry, the WASP pipeline has never used a variable aperture radius based on the brightness of the star to be measured. With our focus shifted to brighter targets I investigated what change to the reduction aperture size, if any, would be most effective.

The pipeline optimised for 200-mm lens data used a reduction aperture with a radius of 3.5 pixels with two apertures with radii of 2.5 and 4.5 pixels to assess blending. I investigated apertures of 2.5, 3, 3.5, 4, 4.5 and 5 pixels by reducing data using the old 3.5 ± 1 pixel apertures and a new set of 4 ± 1 pixel apertures. The behaviour of precision as a function of magnitude is shown in Fig. 3.4 for each aperture considered. The apertures behave as expected; larger apertures perform better than smaller ones for brighter magnitudes and vice versa. The medians are calculated for bins half a magnitude wide. An offset in zero-point magnitude calibration between different apertures can cause a shift along the x axis. This would result in an apparent change in precision, log(RMS), which could lead to an interpretation that an aperture is performing better or worse than it is in reality. The offset value is recorded in the pipeline logs for each field. To ensure comparability, I removed the offset applied to each individual reduction and applied the mean of the offsets all the results.

Fig. 3.4 shows that aperture radii of 4 pixels, 4.5 pixels and 5 pixels all perform similarly well at WASP instrumental magnitudes brighter than 9. However, the perfor- mance of the apertures with radii of 4.5 pixels and 5 pixels falls off more rapidly than the aperture with a radius of 4 pixels. While the performance of the aperture with a radius of 3.5 pixels falls off less rapidly than the one with a radius of 4 pixels, the improvement is minimal at instrumental magnitudes brighter than 10. The project’s main focus is detecting planets orbiting bright stars, so we require better performance for brighter stars more than we need an aperture that performs optimally at all mag- nitudes. As a result, we decided to use a main reduction aperture radius of 4 pixels. The secondary apertures were kept at one pixel larger and smaller, i.e. radii of 3 pixels and 5 pixels.

-2.4 -2.2 -2 -1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 6 7 8 9 10 11 12 13 14 15 log(RMS) WASP magnitude 2.5 Pixels 3 Pixels 3.5 Pixels 4 Pixels 4.5 Pixels 5 Pixels

Figure 3.4: Graph showing RMS as a function of WASP instrumental magnitude after the switch to 85-mm lenses. Median lines computed from one good night for a field re- duced using 6 candidate apertures. These results demonstrate the expected behaviour; larger apertures result in lower RMS scatter for brighter stars.

3.3

‘Badsky’ Rejection Limit

Before aperture photometry is performed the pipeline creates a model of the sky back- ground flux. To assess only the background it places circular masks on the images at the positions of all the stars in the input catalogue. The mask radii are scaled propor- tional to the star’s brightness. Solar system planets are also masked from the fields. If the χ2 _{of the fit is high or a large proportion of the pixels are masked the frame} is labelled with ‘.badsky’ and not processed further. The purpose of this is to reject crowded frames or frames with cloud present that could affect the photometry. Fig. 3.5 shows the relationship between χ2 _{and the ratio of unmasked-to-masked pixels for} a field from a good night and a cloudy night. The new and old rejection limits are also shown. The data from the good night follows a coherent trend while the data from cloudy conditions does not. The old limits rejected data from the good night that appears consistent with the trend followed by the rest of the data from the good night. The previous rejection limits were a ratio of unmasked-to-masked pixels of 2 and a sky fit reduced χ2 _{of 5. The shift in the limits now accepts this coherent data without} accepting more cloudy data than before the change. The new limits are a ratio of 1 and a sky fit reduced χ2 _{of 4. For comparison, using the old rejection limits, the poor} quality night used in Fig. 3.5 would have had 1868 of its 6849 frames rejected. Using the new rejection limits 2111 of the 6849 frames from the poor quality night would be rejected. The new rejection limits are at least as stringent as the previous limits.