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Related papers: Polynomial Ensembles and Recurrence Coefficients

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A recursion operator is an integro-differential operator which maps a generalized symmetry of a nonlinear PDE to a new symmetry. Therefore, the existence of a recursion operator guarantees that the PDE has infinitely many higher-order…

Exactly Solvable and Integrable Systems · Physics 2013-01-08 D. E. Baldwin , W. Hereman

We introduce and study a class of discrete particle ensembles that naturally arise in connection with classical random matrix ensembles, log-gases and Jack polynomials. Under technical assumptions on a general analytic potential we prove…

Probability · Mathematics 2022-07-20 Evgeni Dimitrov , Alisa Knizel

The $A_\infty$ T-system, also called the octahedron recurrence, is a dynamical recurrence relation. It can be realized as mutation in a coefficient-free cluster algebra (Kedem 2008, Di Francesco and Kedem 2009). We define T-systems with…

Combinatorics · Mathematics 2023-06-16 Panupong Vichitkunakorn

In general dimension, there is no known total polynomial algorithm for either convex hull or vertex enumeration, i.e. an algorithm whose complexity depends polynomially on the input and output sizes. It is thus important to identify…

Computational Geometry · Computer Science 2021-04-26 Ioannis Z. Emiris , Vissarion Fisikopoulos , Bernd Gärtner

We give a probabilistic introduction to determinantal and permanental point processes. Determinantal processes arise in physics (fermions, eigenvalues of random matrices) and in combinatorics (nonintersecting paths, random spanning trees).…

Probability · Mathematics 2016-08-16 J. Ben Hough , Manjunath Krishnapur , Yuval Peres , Bálint Virág

Correlation functions for matrix ensembles with orthogonal and unitarysymplectic rotation symmetry are more complicated to calculate than in the unitary case. The supersymmetry method and the orthogonal polynomials are two techniques to…

Mathematical Physics · Physics 2010-03-19 Mario Kieburg , Thomas Guhr

This paper puts forward a new generalized polynomial dimensional decomposition (PDD), referred to as GPDD, comprising hierarchically ordered measure-consistent multivariate orthogonal polynomials in dependent random variables. Unlike the…

Numerical Analysis · Mathematics 2018-10-30 Sharif Rahman

New iterative methods for solving linear equations are presented that are easy to use, generalize good existing methods, and appear to be faster. The new algorithms mix two kinds of linear recurrence formulas. Older methods have either high…

Numerical Analysis · Mathematics 2012-03-13 Joseph F. Grcar

In this work, the concept of quasi-type Kernel polynomials with respect to a moment functional is introduced. Difference equation satisfied by these polynomials along with the criterion for orthogonality conditions are discussed. The…

Spectral Theory · Mathematics 2023-01-31 Vikash Kumar , A. Swaminathan

We express the averages of products of characteristic polynomials for random matrix ensembles associated with compact symmetric spaces in terms of Jack polynomials or Heckman and Opdam's Jacobi polynomials depending on the root system of…

Probability · Mathematics 2009-11-11 Sho Matsumoto

In this paper we analyze several new methods for solving nonconvex optimization problems with the objective function formed as a sum of two terms: one is nonconvex and smooth, and another is convex but simple and its structure is known.…

Optimization and Control · Mathematics 2014-06-25 A. Patrascu , I. Necoara

These lectures provide an informal introduction into the notions and tools used to analyze statistical properties of eigenvalues of large random Hermitian matrices. After developing the general machinery of orthogonal polynomial method, we…

Mathematical Physics · Physics 2014-11-18 Yan V. Fyodorov

We analyze the density of roots of random polynomials where each complex coefficient is constructed of a random modulus and a fixed, deterministic phase. The density of roots is shown to possess a singular component only in the case for…

chao-dyn · Physics 2016-08-31 D. Braun , M. Kus , K. Zyczkowski

In these lecture notes we present some connections between random matrices, the asymmetric exclusion process, random tilings. These three apparently unrelated objects have (sometimes) a similar mathematical structure, an interlacing…

Mathematical Physics · Physics 2013-07-03 Patrik L. Ferrari

Recurrence coefficients of semi-classical orthogonal polynomials (orthogonal polynomials related to a weight function $w$ such that $w'/w$ is a rational function) are shown to be solutions of non linear differential equations with respect…

Classical Analysis and ODEs · Mathematics 2016-09-06 Alphonse P. Magnus

We continue our study on counting irreducible polynomials over a finite field with prescribed coefficients. We set up a general combinatorial framework using generating functions with coefficients from a group algebra which is generated by…

Combinatorics · Mathematics 2021-09-07 Zhicheng Gao , Simon Kuttner , Qiang Wang

We establish some new Tur\'an's type inequalities for orthogonal polynomials defined by a three-term recurrence with monotonic coefficients. As a corollary we deduce asymptotic bounds on the extreme zeros of orthogonal polynomials with…

Classical Analysis and ODEs · Mathematics 2011-01-18 Ilia Krasikov

In this paper, we study the expected value of the pair correlation statistics of randomized point configurations on the sphere, with the emphasis on point configurations generated by determinantal point processes. We study the cases of the…

Probability · Mathematics 2026-04-22 Maryna Manskova

We investigate the limiting behavior of discrete determinantal point processes (DPPs) towards continuous DPPs when the size of the set to sample from goes to infinity. We propose a non-asymptotic characterization of this limit in terms of…

Probability · Mathematics 2026-03-03 Hugo Jaquard , Nicolas Keriven

Random restart of a given algorithm produces many partitions to yield a consensus clustering. Ensemble methods such as consensus clustering have been recognized as more robust approaches for data clustering than single clustering…

Machine Learning · Statistics 2021-02-09 Serge Vicente , Alejandro Murua