This week, on the coding side of things all was well. A python script to correctly determine the magnitude of our Sun was written. In future, we can extend the same script to stars to a distribution of G-type stars generated by us, and see if we get the same magnitudes out from the script as we put in. A script for analytical error was completed. However, since many of the errors we will be dealing with are not symmetrical about the mean, numerical errors will have to be used. Our chief error analyser is in the process of making a numerical error Python script.
There was also progress in the removal of galaxies from our CFHT CaHK catalogue. To do so we used the J & K filters. J and K are two filters with central wavelengths in the near-infrared. The J-K index can be used to distinguish between stars and galaxies because the redshift of an object effects the apparent magnitude of that object in the J and K filters more significantly than in other filters. To find a criterion by which to separate stars and galaxies, we plotted J-K against various combinations of other colour indices on the software TOPCAT. Using the TOPCAT subsets function, the number of galaxies retained and stars lost was found and then used to decide the most effective criterion. An example of this is shown below for a J-K against B-V plot. Stars were defined as having a redshift of zero, and an object in the catalogue was classed as a galaxy if it had z>0.1.
However, there are a few issues with our method. There are many galaxies below the line in figure 1, meaning our catalogue would still contain galaxies after the galaxy criterion was applied. Furthermore, many entries in the catalogue had a colour magnitude of +/-99.9 as there is no actual data on that colour magnitude. This is not good, as data points were flung out all over the plots. To try and resolve this we considered several alternatives. Firstly, a ratio of the apparent magnitude of an object in a 2” aperture and the apparent magnitude in a 3” aperture should be unity for point-like stars but not for galaxies. Although we soon dismissed this idea, as atmospheric seeing means not all stars are point-like and some galaxies are far enough away to appear point-like leading to lots of contamination. Secondly, we considered using the ‘Stellaricity’ data in the COSMOS catalogue. Stellaricity is a parameter that is equal to 0 for galaxies and 1 for stars. However, many entries in the catalogue have Stellaricity somewhere inbetween 0 and 1, and it is unclear how Stellaricity was quantified by COSMOS, so we cannot use Stellaricity.
Therefore, we must use the J-K method to remove galaxies and find the criterion that gives the highest completion (percentage of stars kept) and lowest contamination (percentage of galaxies kept). We will finalise results from this next week, as well as revise our estimate for the volume of the study region.