Target Selection: Quality and EfficiencyThe Sloan Digital Sky Survey uses its imaging data to select objects for spectroscopic followup. There is a description of the target selection algorithms in the EDR paper. Also compare the targetting algorithms page. Broadly speaking, targetted objects fall into three categories:
Note: Just because an object is targetted does not necessarily mean that it will be assigned a spectroscopic fiber. The tiling algorithm (see also Blanton et al. 2003) assigns targets to fibers; two fibers cannot be placed more closely than 55". This means that roughly 10% of all galaxy targets are not observed spectroscopically (somewhat less in the overlaps between plates). The majority of close pairs of galaxies are essentially at the same redshift, an approximation that works reasonably well for, e.g., correlation function studies (cf., Zehavi et al. 2002). Tiled targetsThe main galaxy sampleThis is described in some detail in Strauss et al. (2002); a briefer description is on the target selection algorithm page. In brief, it includes all galaxies with Petrosian r magnitude brighter than 17.77. Here and throughout target selection, magnitude limits are based on quantities corrected for Galactic reddening a la Schlegel, Finkbeiner, and Davis (1998). There is a Petrosian half-light surface brightness cut of 24.5 magnitudes in one square arcsec, which rejects less than 1% of all galaxies. There is also a cut in 3" fiber magnitude at g=15, r=15, and i=14.5 (to prevent saturation and cross-talk in the spectrographs). There are roughly 90 such targets per square degree. Bright galaxy magnitude limitsThe galaxy sample is limited at the bright end by the fiber magnitude limits, to avoid saturation and excessive cross-talk in the spectrographs. Similarly, the image deblending software had a tendency to occasionally shred large, bright galaxies with substructure, causing problems for galaxy target selection at the bright end (this problem is essentially fixed in the version of the pipeline that produced the "best" imaging reductions, but was not in place when the targetting and spectroscopy was carried out. These two effects together cause the spectroscopic sample to become noticeably incomplete for galaxies brighter than r=14.5 or so. We do plan eventually to supplement our galaxy catalog with redshifts from the literature for those bright galaxies for which we do not have redshifts. Faint galaxy magnitude limitThe galaxy target selection is magnitude-limited to a Galactic extinction-corrected Petrosian magnitude of r=17.77. However, this limiting magnitude has varied through the survey, between 17.5 and 17.77 (it turns out that one needs to survey an enormous region of sky to determine the number density of galaxies to a few percent accuracy!). The information on what magnitude limit is used in what region of sky is quite complex (as is the information on the exact geometry of the sky coverage). The safest thing to do at this point is to limit a galaxy spectroscopic sample for statistical studies to r=17.5. Galaxy target selection efficiencyThe galaxy target selection is very efficient. Only one percent of the objects targetted turn out not to be galaxies. This one percent is made up of close pairs of stars, and occasional sprays of scattered light. The signal-to-noise ratio in the spectra is such that reliable redshifts are available for essentially all galaxies, even those at quite low surface brightness levels. The Luminous Red Galaxy SampleThis sample is described by Eisenstein et al. (2001); a briefer description can be found on the target selection algorithm page. This targets the most luminous red galaxies at each redshift; for redshifts z>0.2, there are clean cuts in color-magnitude space that effectively isolate objects with the properties of Brightest Cluster Galaxies. There are two classes, flagged with the target bits GALAXY_RED and GALAXY_RED_II, respectively; they select a roughly volume-limited sample of objects with 0.2<z<0.38 (down to r(Petrosian) = 19.2), and a flux-limited sample (to r(Petrosian) = 19.5), which extends to z=0.55. There are roughly 12 objects targetted per square degree. The LRG sample comes in two parts: a roughly volume-limited subsample to z=0.38, and a flux-limited sample that extends to z=0.55 or so. The spectra are of high enough quality that only 1-2% of the objects targetted fail to have a redshift successfully measured. The color cuts that define the LRG sample break down for redshifts below 0.2. That's OK, all such objects are bright enough to be included in the main galaxy sample, but it is up to individual scientists to pull such a sample out (i.e., based on luminosities and colors). There have been small changes in the LRG target selection criteria from DR1 to DR2/DR3. The Quasar sampleThis sample is described in Richards et al. (2002); a briefer description can be found in the target selection algorithm page. Quasar candidates are defined as objects with colors distinct from those of ordinary stars (which form almost a one-dimensional distribution in SDSS color space). Certain regions of color space are explicitly excluded, as they are contaminated by rarer types of stars: hot white dwarfs, A stars, and M dwarf/white dwarf pairs. The algorithm does not explicitly require objects be unresolved in the region of color space in which ultraviolet excess objects lie (this allows resolved Seyfert galaxies to be targetted), but redder objects (i.e., those with z>3, reddened by the Lyman alpha forest) must be stellar. Magnitude limitsThe sample is magnitude-limited to a PSF magnitude of i=19.1 in the ultraviolet excess region of color space, and i=20.2 elsewhere. Roughly 18 objects per square degree are targetted; of order 2/3 of these are in fact quasars. In addition, unresolved objects brighter than i=19.1 with counterparts in the FIRST radio survey are also targetted. Very few of these are not already selected by the color algorithm described above. There is a bright limit of i=15 for similar reasons as in the galaxy target selection Quasar target selection changesQuasar target selection has also evolved somewhat, due both to changes in the targetting algorithm itself, and improvements in the photometric pipeline; quasar target selection was the focus of a great deal of fine-tuning during SDSS commissioning. None of the DR1 data use the very latest version of the target selection algorithm, as described in the Richards et al. (2002) paper. As a consequence, the quasar targetting efficiency in the data themselves varies a fair amount. With the current versions of the selection algorithm and the imaging pipeline, the selection is clean: roughly 2/3 of the targets are indeed quasars, and essentially all the contamination is there for astrophysical reasons (principally compact star-forming galaxies, A and F stars, white dwarfs, and late M stars). However, with old versions of the imaging pipeline, stars tended to scatter out of the stellar locus when the seeing changed rapidly, contaminating the quasar selection and reducing the efficiency of the code. As a consequence, there are plates, fortunately relatively few, with quasar target selection efficiency as low as 30%. Quasar selection completenessThe completeness of the quasar selection algorithm depends somewhat on redshift. In particular, the completeness is low for 2.4<z<2.9, where the quasar and stellar loci cross; it is similarly low at redshifts around 3.5 and 4.5. These incompletenesses are more severe in previous versions of the code than at present. Quasar spectrum signal-to-noiseThe signal-to-noise ratio of the quasar spectra is high, and the redshift accuracy, based on extensive tests, is similarly high, of order 99%. The exceptions are astrophysically interesting: BL Lacertae objects (notoriously difficult to distinguish spectroscopically from very hot stars) and extreme Broad Absorption Line quasars (see the paper by Hall et al. 2002) are the most important. Users of the spectra should be sure to pay close attention to the flags indicating uncertainty in redshift determination. Brown dwarf candidatesThese represent fewer than one object per square degree; they are targetted by their very red colors in i-z, and relatively blue colors in r-i. Other targetsThe other categories of scientific targets are assigned spectroscopic fibers when fibers are available, following a cleanly defined set of priorities. See the discussion of target priorities in the EDR paper. Among these are: Optical counterparts to ROSAT sourcesThese include quasars and AGN (including some BL Lacs), some cataclysmic variables, and other unusual classes of objects. Optical counterparts to FIRST radio sourcesThese go fainter than the quasar sample and do not have the restriction that the object be unresolved. Stars chosen by their unusual colorsThese usually extend to magnitude limits fainter than the quasar sample. Among these are objects with colors of blue horizontal branch stars and white dwarfs. Again, these classes of objects are observed spectroscopically only when fibers are available, and therefore are not complete on the sky in any sense of the term. Target Selection References
Last modified: Tue Mar 9 11:37:05 CST 2004 |