Geometric RSK correspondence, Whittaker functions and symmetrized random polymers
Neil O'Connell, Timo Sepp\"al\"ainen, Nikos Zygouras

TL;DR
This paper explores the geometric RSK correspondence's volume-preserving properties, its connection to Whittaker functions, and applications to random polymer models, providing new combinatorial frameworks and explicit probability distributions.
Contribution
It introduces a volume-preserving geometric RSK correspondence, links it to Whittaker functions, and applies it to analyze symmetric and triangular random polymer models.
Findings
The geometric RSK correspondence is volume preserving.
Explicit distribution formulas for polymer partition functions with inverse gamma weights.
New combinatorial proofs of Whittaker integral identities.
Abstract
We show that the geometric lifting of the RSK correspondence introduced by A.N. Kirillov (2001) is volume preserving with respect to a natural product measure on its domain, and that the integrand in Givental's integral formula for GL(n,R)-Whittaker functions arises naturally in this context. Apart from providing further evidence that Whittaker functions are the natural analogue of Schur polynomials in this setting, our results also provide a new `combinatorial' framework for the study of random polymers. When the input matrix consists of random inverse gamma distributed weights, the probability distribution of a polymer partition function constructed from these weights can be written down explicitly in terms of Whittaker functions. Next we restrict the geometric RSK mapping to symmetric matrices and show that the volume preserving property continues to hold. We determine the…
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