Investigations into matching on extremely dense stellar fields (N stars of order 1k) has revealed the following:
Using saturated stars is not recommended. Due to the high density of stars a large faction of the brightest N stars will be saturated if they are not specifically removed. This can cause outright failures to match or cause the matcher to wander after finding an initial match due to the centroid of the saturated object not being precise enough on subsequent match/WCS fit iterations. If attempting to match on dense stellar fields, it is recommended that the isGood flag be substituted in place of the isUsable flag.
The starting match criteria and subsequent softening loops in both the stack and Python matchers are insufficient to remove false positives in the matching process. Specifically in the stack matcher the variable maxOffsetPix is not part of an the iterative process, that is searching for small matches first and then subsequently softening the max search distance allowed. Finding a suitable starting point for the matchers through statistics computed on the reference/source catalog or tightening tolerances when presented with a large number of reference objects may be required. It also my be worth pursuing changing the number of bright stars used to create a pattern to alleviate this false positive problem. How to figure out what complexity of pattern to match on the fly for a given density if stars is an open question.
A possible solution to back off of the "optimistic" part of optimistic pattern matcher is to find several pattern matches from the brightest N stars and return the best match.