On KP-integrable skew Hurwitz $\tau$-functions and their $\beta$-deformations
A. Mironov, V. Mishnyakov, A. Morozov, A. Popolitov, Wei-Zhong Zhao

TL;DR
This paper extends the formalism of cut-and-join operators to describe a broad class of KP-integrable skew Hurwitz tau-functions, including new interpolating WLZZ models, with detailed proofs, generalizations, and beta-deformations.
Contribution
It introduces a comprehensive framework for skew Hurwitz tau-functions, generalizes to multi-matrix models, and proposes beta-deformations, connecting various integrable models via W-representations.
Findings
Identified a family of KP-integrable skew Hurwitz tau-functions.
Connected WLZZ models to matrix models and Calogero-Sutherland Hamiltonians.
Proposed beta-deformation of matrix models for these tau-functions.
Abstract
We extend the old formalism of cut-and-join operators in the theory of Hurwitz -functions to description of a wide family of KP-integrable {\it skew} Hurwitz -functions, which include, in particular, the newly discovered interpolating WLZZ models. Recently, the simplest of them was related to a superintegrable two-matrix model with two potentials and one external matrix field. Now we provide detailed proofs, and a generalization to a multi-matrix representation, and propose the deformation of the matrix model as well. The general interpolating WLZZ model is generated by a -representation given by a sum of operators from a one-parametric commutative sub-family (a commutative subalgebra of ). Different commutative families are related by cut-and-join rotations. Two of these sub-families (`vertical' and `45-degree') turn out to be nothing but the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFuzzy and Soft Set Theory · Approximation Theory and Sequence Spaces · Fuzzy Systems and Optimization
