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Related papers: Generation of Matrix Models by W-operators

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A general group element for the fundamental representation of SU(3) is expressed as a second order polynomial in the hermitian generating matrix H, with coefficients consisting of elementary trigonometric functions dependent on the sole…

Representation Theory · Mathematics 2016-01-11 Thomas L. Curtright , Cosmas K. Zachos

We study the representability problem for torsion-free arithmetic matroids. By using a new operation called "reduction" and a "signed Hermite normal form", we provide and implement an algorithm to compute all the representations, up to…

Combinatorics · Mathematics 2023-03-08 Roberto Pagaria , Giovanni Paolini

We construct the supersymmetric $\beta$ and $(q,t)$-deformed Hurwitz-Kontsevich partition functions through $W$-representations and present the corresponding character expansions with respect to the Jack and Macdonald superpolynomials,…

High Energy Physics - Theory · Physics 2023-09-06 Rui Wang , Fan Liu , Min-Li Li , Wei-Zhong Zhao

This paper considers two frequently used matrix representations -- what we call the $\chi$- and $\mathcal{S}$-matrices -- of a quantum operation and their applications. The matrices defined with respect to an arbitrary operator basis, that…

Quantum Physics · Physics 2007-05-23 Yoshihiro Nambu , Kazuo Nakamura

Our goal is to find a matrix model with $BMS_3$ constraints built in. These constraints are imposed through Loop equations. We solve them using a free field realisation of the algebra and write down the partition function in eigenvalue…

High Energy Physics - Theory · Physics 2024-06-25 Arindam Bhattacharjee , Neetu

The aim of this paper is to show some examples of matrix-valued orthogonal functions on the real line which are simultaneously eigenfunctions of a second-order differential operator of Schr\"{o}dinger type and an integral operator of…

Functional Analysis · Mathematics 2011-10-21 Manuel D. de la Iglesia

Correlators in topological theories are given by the values of a linear form on the products of operators from a commutative associative algebra (CAA). As a corollary, partition functions of topological theory always satisfy the generalized…

High Energy Physics - Theory · Physics 2015-05-30 A. Mironov , A. Morozov , S. Natanzon

We relate Nekrasov partition functions, with arbitrary values of $\epsilon_1,\epsilon_2$ parameters, to matrix models for $\beta$-ensembles. We find matrix models encoding the instanton part of Nekrasov partition functions, whose measure,…

High Energy Physics - Theory · Physics 2010-04-30 Piotr Sułkowski

In this paper, we introduce the generating functions of partition sequences. Partition sequences have a one-to-one correspondence with partitions. Therefore, the generating function has no multiplicity and appears meaningless initially.…

Combinatorics · Mathematics 2025-04-16 Masanori Ando

We introduce a dbar-formulation of the orthogonal polynomials on the complex plane, and hence of the related normal matrix model, which is expected to play the same role as the Riemann-Hilbert formalism in the theory of orthogonal…

Classical Analysis and ODEs · Mathematics 2007-08-30 Alexander R. Its , Leon A. Takhtajan

We extend the old formalism of cut-and-join operators in the theory of Hurwitz $\tau$-functions to description of a wide family of KP-integrable {\it skew} Hurwitz $\tau$-functions, which include, in particular, the newly discovered…

High Energy Physics - Theory · Physics 2023-03-03 A. Mironov , V. Mishnyakov , A. Morozov , A. Popolitov , Wei-Zhong Zhao

We show that many important convex matrix functions can be represented as the partial infimal projection of the generalized matrix fractional (GMF) and a relatively simple convex function. This representation provides conditions under which…

Optimization and Control · Mathematics 2019-05-13 James V. Burke , Yuan Gao , Tim Hoheisel

We compute the partition and correlation generating functions for the Heisenberg intertwiner generalized vertex operator algebra on a genus $g$ Riemann surface in the Schottky uniformization. These are expressed in terms of differential…

Quantum Algebra · Mathematics 2020-06-03 Michael P. Tuite

Matrix models with continuous symmetry are powerful tools for studying quantum gravity and holography. Tensor models have also found applications in holographic quantum gravity. Matrix models with discrete permutation symmetry have been…

High Energy Physics - Theory · Physics 2023-12-15 George Barnes , Adrian Padellaro , Sanjaye Ramgoolam

For finding the numerical solution of operator equations in many applications a decomposition in subspaces is needed. Therefore, it is necessary to extend the known method of matrix representation to the utilization of fusion frames. In…

Functional Analysis · Mathematics 2020-07-14 Peter Balazs , Mitra Shamsabadi , Ali Akbar Arefijamaal , Chilles Gardon

Random matrices tend to be well conditioned, and we employ this well known property to advance matrix computations. We prove that our algorithms employing Gaussian random matrices are efficient, but in our tests the algorithms have…

Numerical Analysis · Mathematics 2012-10-30 Victor Y. Pan , Guoliang Qian , Ai-Long Zheng

We summarize the recent results about complete solvability of Hermitian and rectangular complex matrix models. Partition functions have very simple character expansions with coefficients made from dimensions of representation of the linear…

High Energy Physics - Theory · Physics 2017-08-11 A. Mironov , A. Morozov

Before we proposed an algebraic technics for the Hamiltonian approach to the evolution systems of partial differential equations, including systems with constraints. Here we further develop this approach and present the defining system of…

Mathematical Physics · Physics 2018-03-13 Victor Zharinov

A concise study of ternary and cubic algebras with $Z_3$ grading is presented. We discuss some underlying ideas leading to the conclusion that the discrete symmetry group of permutations of three objects, $S_3$, and its abelian subgroup…

Mathematical Physics · Physics 2022-01-14 Richard Kerner

Factorization machines and polynomial networks are supervised polynomial models based on an efficient low-rank decomposition. We extend these models to the multi-output setting, i.e., for learning vector-valued functions, with application…

Machine Learning · Statistics 2017-11-07 Mathieu Blondel , Vlad Niculae , Takuma Otsuka , Naonori Ueda