Combinatorial Structures in Random Matrix Theory Predictions for $L$-Functions
Helen Riedtmann

TL;DR
This paper explores algebraic combinatorics, specifically a new operation called overlap on partitions, to analyze random matrix theory predictions for the statistical behavior of L-functions, including asymptotic formulas for characteristic polynomial averages.
Contribution
It introduces the overlap operation on partitions, proves new identities for Littlewood-Schur functions, and generalizes formulas for averages of characteristic polynomial ratios over the unitary group.
Findings
Proved two overlap identities for Littlewood-Schur functions.
Derived an asymptotic formula for averages of mixed ratios of characteristic polynomials.
Provided combinatorial tools that may lead to new number theoretic proofs.
Abstract
Our results can be viewed as applications of algebraic combinatorics in random matrix theory. These applications are motivated by the predictive power of random matrix theory for the statistical behavior of the celebrated Riemann -function (and -functions in general), which was discovered by Montgomery (with regard to zeros of -functions) and by Keating and Snaith (with regard to values of -functions). The first results revolve around a new operation on partitions, which we call overlap. We prove two overlap identities for so-called Littlewood-Schur functions. The first overlap identity represents the Littlewood-Schur function as a sum over subsets of , while the second overlap identity essentially represents as a sum over pairs of partitions whose overlap equals . Both identities are derived by applying Laplace…
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Taxonomy
TopicsAdvanced Combinatorial Mathematics · Analytic Number Theory Research · Advanced Mathematical Identities
