The new algorithm handles stars which are not detected in all bands. However, it needs a training set of stars which both covers the entire color range and has all colors for the stars. The red stars in Xiaohui's simulation do not have u measurements, and presented problems for creating the locus fit.
I have (more or less) successfully run the fifth simulation through the QSO target selection code. I was able to twiddle the parameters to get about the same efficiency and completeness that I got before we put the red stars in, but I have a few reservations about the fitting procedure. This simulation is different from previous simulations in that Xiaohui put in a limiting magnitude (mostly in the u' filter) instead of the simulated magnitude if the magnitude was fainter than our detection limit on the 2.5 meter. The selection algorithm has been modified to recognize an object as a star if there is any way to extrapolate it into the locus, given the known limits in its colors. For instance, if the object is not detected in u, then we know that u-g > ulimit-g. If we can find any value of u-g in this range which falls inside our stellar locus fit, then it is assumed to be a star.
I had a few problems running this simulation through; the problems point out the need for special photometric data to tune the locus parameters.
I could not separate the stars out by magnitude, and make a different
locus for each magnitude range. This is because for the fainter stars the
redder stars were limits. So, I could not fit the red end of the locus.
I need the red end of the locus to be in the correct position so that when
I project the limits back to the locus the projected point is within the
locus width. So, I generated only one locus fit, using stars at 15
This is the figure of merit:
The new algorithm handles stars which are not detected in all bands.
However, it needs a training set of stars which both covers the entire
color range and has all colors for the stars. The red stars in Xiaohui's
simulation do not have u measurements, and presented problems for
creating the locus fit.
# targets/#objects brighter than 20. # objects
Targets selected (by type): 1 41/6558 6558
2 78/4700 4700
3 0/0 0
4 0/0 0
5 0/0 0
6 0/0 0
7 0/0 0
8 57/58 58
9 14/16 16
10 211/213 213
-----------------
401/11545 11545
QSO completeness (z): -10 - 1 85/85 85
1 - 1.5 49/49 49
1.5 - 2 32/32 32
2 - 2.5 24/24 24
2.5 - 3 14/16 16
3 - 3.5 6/6 6
3.5 - 4 1/1 1
4 - 6 0/0 0
6 - 10 0/0 0
-----------------
211/213 213
QSO completeness (m): -10 - 15 0/0 0
15 - 16 1/1 1
16 - 17 1/1 1
17 - 18 20/20 20
18 - 19 91/92 92
19 - 20 98/99 99
20 - 30 0/0 0
-----------------
211/213 213
The bottom line is that we get 99% completeness, with all of the missing
QSOs in the 2.5 - 3.5 redshift range. In this range, the completeness
drops to 88%. The efficiency is 53%. Of the selected candidates, 53% are
QSOs, 14% are NELGs, 4% are white dwarfs, and 30% are galactic stars. This
assumes that the simulations are a fair representation of the sky, and
that I didn't cheat too much by using the same data to fit the locus.