MAST first dealt with this problem when it introduced objects identified from the GALEX satellite. At that time we adopted a comparatively simple procedure by creating two tables of matches from the KIC and GALEX catalog and storing in our CasJobs tool. The first table was constructed using mutual 1:1 closest-object matches, and the second with matches that were not based on a broader cone search and for which the matches were not necessarily mutual or secondary. In the latter case possible secondary, tertiary, etc. (i.e., more distant) matches were made if the separations between coordinates was less than some designated value. Since then, MAST has added data from additional catalogs to build a more extensive Kepler Color Table. The larger number of catalogs introduced make our earlier procedure impractical because it would require adding many more fields to denote secondary etc. matches that would add more confusion than clarity to the matching results. Therefore, MAST has resorted to the more conservative mutual 1:1 match criterion between the catalogs. This criterion means that object "a" from Catalog A and object "b" from Catalog B are within a designated angular separation limit and that that a and b are both the closest in the sky to one another and the only matches. The limiting angular separation for catalogs matches is typically 1" but varies from catalog to catalog. We display the precise limits of our searches on KIC targets against other catalogs or the table in GOHelp Section 1 and Explanations & Caveats pages.
Although less likely to occur than with a more liberal criterion, false and missed matches can occur even with mutual a 1:1 matching criterion. A single catalog, including the KIC can have two entries closely situated together (perhaps an image artifact, perhaps not), and a false one whose position happens to lie close to the entry from the matching catalog. Second, one catalog may not go as deep in brightness as another, making the object with the shorter exposure hard to extract and compare with an image in a deeper surveyed catalog. Third, matching catalogs are themselves from images extracted from a montage of individual observations of overlapping areas of the sky. Under these conditions the same object can occasionally be assigned inaccurate coordinates whose errors are larger than the catalog’s the rejection criterion of duplicate matches; i.e., duplicate matches can occur for the same object in a given catalog.
Here are two examples of how matches can go wrong:
Consider first the example given on Part 2
of the CasJobs GOhelp page. This discusses the example of two apparent GALEX
objects matching to a particular KIC object, KIC7434250, if the mutual 1:1
match condition is ignored. In this case both FUV and NUV GALEX identifications
have been assigned coordinates each near the same KIC object, but these
coordinates are inaccurate because in both observations the object is
detected near the edges of the observation field, where the coordinates
are often inaccurate. In fact, the coordinates from one or both of them
are in error enough in this particular case that the GALEX catalog
recognizes them falsely as two separate GALEX objects. Since our matching
relies on assumed 1:1 mutual matches, the matching of Kepler KIC7434250
is not made, and our Color Table gives no matches.
This is an example of a missed match. It will be lost to researchers
searching for this match on the Target Search form. Note that this form
does not give information on the distances of objects from each of their
secondary matches, so the investigator has no clue that a match has been
missed. (The solution is to go to the more liberal KGMatch table in CasJobs,
This table does not require 1:1 matches, so the apparent dual matches
can be discovered.)
A second example follows of a double match that leads to a possible ambiguity but not to a missed object. If one searches on the coordinates (292.2301245, 37.589047) and broadens the search radius slightly to 0.03 arcminutes, the retrieval page shows two KIC objects (rows 1and 3) and one UKIRT object (row 2). This anomaly again occurs because of the requirement for 1:1 matching. This UKIRT object is very close to both KIC objects, so it cannot be matched uniquely to either of them. Our procedure causes the the UKIRT object as be recognized an independent object, probably incorrectly. An ambiguity in the match to KIC objects results. The alert user can then make the appropriate decisions. Note that is also possible that in this case one of the objects is false. However, this cannot be demonstrated because the two KIC entries have different KIC r magnitudes. As of this moment, the correct association for this UKIRT object appears in limbo.
These and other examples require user judgment calls, usually settled
by more information. One way of resolving these difficult cases
is to see if matches are found from additional catalogs. Users
should investigate such cases and be aware that their judgments
carry an element of risk.