Journal of Mathematical Physics, Analysis, Geometry
2017, vol. 13, No 4, pp. 364-401     ( to contents , go back )

Fluctuations of Interlacing Sequences

Sasha Sodin

Tel Aviv University, School of Mathematical Sciences Tel Aviv, 69978, Israel
Queen Mary University of London, School of Mathematical Sciences London E1 4NS, United Kingdom

Received November 07, 2016


In a series of works published in the 1990s, Kerov put forth various applications of the circle of ideas centered at the Markov moment problem to the limiting shape of random continual diagrams arising in representation theory and spectral theory. We demonstrate on several examples that his approach is also adequate to study the fluctuations about the limiting shape.
In the random matrix setting, we compare two continual diagrams: one is constructed from the eigenvalues of the matrix and the critical points of its characteristic polynomial, whereas the second one is constructed from the eigenvalues of the matrix and those of its principal submatrix. The fluctuations of the latter diagram were recently studied by Erd}os and Schröder; we discuss the uctuations of the former, and compare the two limiting processes.
For Plancherel random partitions, the Markov correspondence establishes the equivalence between Kerov's central limit theorem for the Young diagram and the Ivanov-Olshanski central limit theorem for the transition measure. We outline a combinatorial proof of the latter, and compare the limiting process with the ones of random matrices.

Mathematics Subject Classification 2000: 60B20, 34L20, 05E10, 60F05, 44A60.
Key words: interlacing sequences, Markov moment problem, continual diagrams, random matrices, central limit theorem.

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