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We show that the joint spectral radius of a finite collection of nonnegative matrices can be bounded by the eigenvalue of a non-linear operator. This eigenvalue coincides with the ergodic constant of a risk-sensitive control problem, or of…

Optimization and Control · Mathematics 2018-05-10 Stephane Gaubert , Nikolas Stott

The angular synchronization problem is to obtain an accurate estimation (up to a constant additive phase) for a set of unknown angles $\theta_1,...,\theta_n$ from $m$ noisy measurements of their offsets $\theta_i-\theta_j \mod 2\pi$. Of…

Spectral Theory · Mathematics 2009-11-20 Amit Singer

When the eigenvalues of the coefficient matrix for a linear scalar ordinary differential equation are of large magnitude, its solutions exhibit complicated behaviour, such as high-frequency oscillations, rapid growth or rapid decay. The…

Numerical Analysis · Mathematics 2023-11-16 Murdock Aubry , James Bremer

The Numerical Renormalization Group method (NRG) has been developed by Wilson in the 1970's to investigate the Kondo problem. The NRG allows the non-perturbative calculation of static and dynamic properties for a variety of impurity models.…

Strongly Correlated Electrons · Physics 2009-10-31 R. Bulla

A new algorithm, denoted by RSRR, is presented for solving large-scale nonlinear eigenvalue problems (NEPs) with a focus on improving the robustness and reliability of the solution, which is a challenging task in computational science and…

Numerical Analysis · Mathematics 2016-07-27 Jinyou Xiao , Shuangshuang Meng , Chuanzeng Zhang , Changjun Zheng

Spectral enhancement -- which aims to undo spectral broadening -- leads to integral equations which are ill-posed and require special regularisation techniques for their solution. Even when an optimal regularisation technique is used,…

Numerical Analysis · Mathematics 2009-11-16 Markus Hegland

We investigate the generalized second-order Arnoldi (GSOAR) method, a generalization of the SOAR method proposed by Bai and Su [{\em SIAM J. Matrix Anal. Appl.}, 26 (2005): 640--659.], and the Refined GSOAR (RGSOAR) method for the quadratic…

Numerical Analysis · Mathematics 2015-03-17 Zhongxiao Jia , Yuquan Sun

Spectral methods which represent data points by eigenvectors of kernel matrices or graph Laplacian matrices have been a primary tool in unsupervised data analysis. In many application scenarios, parametrizing the spectral embedding by a…

Machine Learning · Statistics 2022-06-15 Ziyu Chen , Yingzhou Li , Xiuyuan Cheng

In this work we present the first initialization methods equipped with explicit performance guarantees adapted to the pose-graph simultaneous localization and mapping (SLAM) and rotation averaging (RA) problems. SLAM and rotation averaging…

Robotics · Computer Science 2022-01-12 Kevin J. Doherty , David M. Rosen , John J. Leonard

An approach is developed for constructing simple analytical formulae accurately approximating solutions to eigenvalue problems of quantum mechanics. This approach is based on self-similar approximation theory. In order to derive…

Condensed Matter · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova , S. Gluzman

We develop a numerical method for computing with orthogonal polynomials that are orthogonal on multiple, disjoint intervals for which analytical formulae are currently unknown. Our approach exploits the Fokas--Its--Kitaev Riemann--Hilbert…

Numerical Analysis · Mathematics 2024-01-18 Cade Ballew , Thomas Trogdon

We revisit the $k$-Hessian eigenvalue problem on a smooth, bounded, $(k-1)$-convex domain in $\mathbb R^n$. First, we obtain a spectral characterization of the $k$-Hessian eigenvalue as the infimum of the first eigenvalues of linear…

Analysis of PDEs · Mathematics 2021-09-28 Nam Q. Le

We study an inverse boundary value problem for the nonlinear wave equation in $2 + 1$ dimensions. The objective is to recover an unknown potential $q(x, t)$ from the associated Dirichlet-to-Neumann map using real-valued waves. We propose a…

Numerical Analysis · Mathematics 2025-11-18 Markus Harju , Suvi Anttila , Teemu Tyni

Spectral methods are widely used in geometry processing of 3D models. They rely on the projection of the mesh geometry on the basis defined by the eigenvectors of the graph Laplacian operator, becoming computationally prohibitive as the…

Signal Processing · Electrical Eng. & Systems 2018-10-08 Gerasimos Arvanitis , Aris S. Lalos , Konstantinos Moustakas

In the aim of reducing the computational cost of the resolution of parameter-dependent eigenvalue problems, a model order reduction (MOR) procedure is proposed. We focus on the case of non-self-adjoint generalized eigenvalue problems, such…

Numerical Analysis · Mathematics 2023-11-27 Yonah Conjungo Taumhas , Geneviève Dusson , Virginie Ehrlacher , Tony Lelièvre , François Madiot

Approximately 10 years ago, the method of renormalization-group symmetries entered the field of boundary value problems of classical mathematical physics, stemming from the concepts of functional self-similarity and of the Bogoliubov…

Mathematical Physics · Physics 2009-08-11 V. F. Kovalev , D. V. Shirkov

We establish a deep connection between the Prandtl equations linearised around a quadratic shear flow, confluent hypergeometric functions of the first kind, and the Schr\"odinger operator. Our first result concerns an ODE and a spectral…

Analysis of PDEs · Mathematics 2025-03-17 Francesco De Anna , Joshua Kortum

Definite integrals with parameters of holonomic functions satisfy holonomic systems of linear partial differential equations. When we restrict parameters to a one dimensional curve, the system becomes a linear ordinary differential equation…

Numerical Analysis · Mathematics 2026-04-10 Nobuki Takayama , Takaharu Yaguchi , Yi Zhang

We consider the problem of how to compute eigenvalues of a self-adjoint operator when a direct application of the Galerkin (finite-section) method is unreliable. The last two decades have seen the development of the so-called quadratic…

Spectral Theory · Mathematics 2015-06-16 James Hinchcliffe , Michael Strauss

Many eigenvalue problems arising in practice are often of the generalized form $A\x=\lambda B\x$. One particularly important case is symmetric, namely $A, B$ are Hermitian and $B$ is positive definite. The standard algorithm for solving…

Quantum Physics · Physics 2021-10-20 Changpeng Shao , Jin-Peng Liu