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Related papers: Lanczos Meets Orthogonal Polynomials

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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

We establish a new perturbation theory for orthogonal polynomials using a Riemann--Hilbert approach and consider applications in numerical linear algebra and random matrix theory. This new approach shows that the orthogonal polynomials with…

Probability · Mathematics 2022-09-23 Xiucai Ding , Thomas Trogdon

The Lanczos method is one of the most powerful and fundamental techniques for solving an extremal symmetric eigenvalue problem. Convergence-based error estimates depend heavily on the eigenvalue gap. In practice, this gap is often…

Numerical Analysis · Mathematics 2020-09-17 John C. Urschel

The study of several naturally arising "nearest neighbours" random walks benefits from the study of the associated orthogonal polynomials and their orthogonality measure. I consider extensions of this approach to a larger class of random…

Probability · Mathematics 2007-05-23 F. Alberto Grunbaum

We show that a uniform quadrangulation, its largest 2-connected block, and its largest simple block jointly converge to the same Brownian map in distribution for the Gromov-Hausdorff-Prokhorov topology. We start by deriving a local limit…

Probability · Mathematics 2016-04-29 Louigi Addario-Berry , Yuting Wen

We extend the close interplay between continued fractions, orthogonal polynomials, and Gaussian quadrature rules to several variables in a special but natural setting which we characterize in terms of moment sequences. The crucial condition…

Classical Analysis and ODEs · Mathematics 2023-03-29 Tomas Sauer , Yuan Xu

For a broad class of unitary ensembles of random matrices we demonstrate the universal nature of the Janossy densities of eigenvalues near the spectral edge, providing a different formulation of the probability distributions of the limiting…

Probability · Mathematics 2008-04-08 Brian Rider , Xin Zhou

We study Krylov complexity in BMN Plane Wave Matrix Model at large mass deformation. We consider various consistent reductions of the matrix model that allow us to perform a Hamiltonian analysis which leads to different notions of the…

High Energy Physics - Theory · Physics 2026-05-26 Dibakar Roychowdhury

We consider polynomials that are defined as Wronskians of certain sets of Hermite polynomials. Our main result is a recurrence relation for these polynomials in terms of those of one or two degrees smaller, which generalizes the well-known…

Classical Analysis and ODEs · Mathematics 2018-05-17 Niels Bonneux , Marco Stevens

We relate the probability distribution of the work done on a statistical system under a sudden quench to the Lanczos coefficients corresponding to evolution under the post-quench Hamiltonian. Using the general relation between the moments…

Quantum Physics · Physics 2023-09-19 Kuntal Pal , Kunal Pal , Ankit Gill , Tapobrata Sarkar

Many scientific applications require the evaluation of the action of the matrix function over a vector and the most common methods for this task are those based on the Krylov subspace. Since the orthogonalization cost and memory requirement…

Numerical Analysis · Mathematics 2026-03-24 Nicolas L. Guidotti , Per-Gunnar Martinsson , Juan A. Acebrón , José Monteiro

There are several methods to treat ensembles of random matrices in symmetric spaces, circular matrices, chiral matrices and others. Orthogonal polynomials and the supersymmetry method are particular powerful techniques. Here, we present a…

Mathematical Physics · Physics 2014-11-20 Mario Kieburg , Thomas Guhr

We consider asymptotics of ratios of random characteristic polynomials associated with orthogonal polynomial ensembles. Under some natural conditions on the measure in the definition of the orthogonal polynomial ensemble we establish a…

Mathematical Physics · Physics 2012-01-04 Jonathan Breuer , Eugene Strahov

Spectral correlations in unitary invariant, non-Gaussian ensembles of large random matrices possessing an eigenvalue gap are studied within the framework of the orthogonal polynomial technique. Both local and global characteristics of…

Statistical Mechanics · Physics 2009-10-30 E. Kanzieper , V. Freilikher

Polynomial ensembles are a sub-class of probability measures within determinantal point processes. Examples include products of independent random matrices, with applications to Lyapunov exponents, and random matrices with an external…

Mathematical Physics · Physics 2020-11-11 Gernot Akemann , Eugene Strahov , Tim R. Würfel

Recent work has shown that the (block) Lanczos algorithm can be used to extract approximate energy spectra and matrix elements from (matrices of) correlation functions in quantum field theory, and identified exact coincidences between…

High Energy Physics - Lattice · Physics 2025-03-24 Ryan Abbott , Daniel C. Hackett , George T. Fleming , Dimitra A. Pefkou , Michael L. Wagman

Ordinary orthogonal polynomials are uniquely characterized by the three term recurrence relations up to an overall multiplicative constant. We show that the newly discovered M-indexed orthogonal polynomials satisfy 3+2M term recurrence…

Mathematical Physics · Physics 2015-06-15 Satoru Odake

It is well known that between all processes with independent increments, essentially only the Brownian motion and the Poisson process possess the chaotic representation property (CRP). Thus, a natural question appears: What is an…

Probability · Mathematics 2016-09-07 E. Lytvynov

Krylov space methods provide an efficient framework for analyzing the dynamical aspects of quantum systems, with tridiagonal matrices playing a key role. Despite their importance, the behavior of such matrices from chaotic to integrable…

Quantum Physics · Physics 2025-02-13 Budhaditya Bhattacharjee , Pratik Nandy

Mixed-effects models are widely used to model data with hierarchical grouping structures and high-cardinality categorical predictor variables. However, for high-dimensional crossed random effects, current standard computations relying on…

Methodology · Statistics 2026-05-15 Pascal Kündig , Fabio Sigrist