Parabolic Catalan numbers count flagged Schur functions; Convexity of   tableau sets for Demazure characters
  Shuffles are n-multipermutations with suit multiplicities given by a subset R of {1,..,n-1}. Their inverses are ordered partitions of {1,..,n} whose block sizes derive from R. These "R-permutations" depict the min length coset reps for the quotient of S_n by the parabolic subgroup W_J, with J the complement of R. We refer to those that blockwise avoid the pattern 312 as "312-avoiding R-permutations" and define the "parabolic R-Catalan number" to be the number of them. Let lambda be a partition of N with at most n parts whose set of shape column lengths less than n is R. We show that the number of flagged Schur functions formed on the shape of lambda is this parabolic R-Catalan number, and list over a dozen other phenomena that are enumerated by it. Let pi be an R-permutation. We view the Demazure character (key polynomial) indexed by (lambda,pi) as the sum of the content weight monomials for our "pi-Demazure" semistandard tableaux of shape lambda with entries from {1,..,n}. We show that the set of these tableaux is convex in Z^N if and only if pi is a 312-avoiding R-permutation. A flagged Schur function is the sum of the content weight monomials for the semistandard tableaux of shape lambda whose entries are row-wise bounded by a given weakly increasing n-tuple. We consider general row bound sums for which the bounds may be any n-tuple. Reiner and Shimozono and then Postnikov and Stanley obtained results concerning coincidences between flagged Schur functions and Demazure characters: when lambda is strict, the flagged Schur functions exactly coincide with the 312-avoiding Demazure characters. For general lambda we introduce precise indexing sets of n-tuple bounds for the row bound sums. This and our convexity results are used to sharpen their coincidence results, to extend them to general row bound sums, and to show they hold at the deeper level of coinciding underlying tableau sets. 
Robert A. Proctor and Matthew J. Willis
math.CO