A $q$-Robinson-Schensted-Knuth Algorithm and a $q$-Polymer

  • Yuchen Pei
Keywords: Robinson-Schensted-Knuth algorithms, Macdonald polynomials, Basic hypergeometric series, Exactly solvable models


In Matveev-Petrov (2017) a $q$-deformed Robinson-Schensted-Knuth algorithm ($q$RSK) was introduced.In this article we give reformulations of this algorithm in terms of the Noumi-Yamada description, growth diagrams and local moves. We show that the algorithm is symmetric, namely the output tableaux pairs are swapped in a sense of distribution when the input matrix is transposed. We also formulate a $q$-polymer model based on the $q$RSK, prove the corresponding Burke property, which we use to show a strong law of large numbers for the partition function given stationary boundary conditions and $q$-geometric weights.We use the $q$-local moves to define a generalisation of the $q$RSK taking a Young diagram-shape of array as the input. We write down the joint distribution of partition functions in the space-like direction of the $q$-polymer in $q$-geometric environment, formulate a $q$-version of the multilayer polynuclear growth model ($q$PNG) and write down the joint distribution of the $q$-polymer partition functions at a fixed time.
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