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Numerical integration over the implicitly defined domains is challenging due to topological variances of implicit functions. In this paper, we use interval arithmetic to identify the boundary of the integration domain exactly, thus getting…

Numerical Analysis · Mathematics 2024-12-20 Tianhui Yang , Ammar Qarariyah , Hongmei Kang , Jiansong Deng

We present a combinatorial approach to rigorously show the existence of fixed points, periodic orbits, and symbolic dynamics in discrete-time dynamical systems, as well as to find numerical approximations of such objects. Our approach…

Dynamical Systems · Mathematics 2017-06-28 Marian Gidea , Yitzchak Shmalo

We present a method of cones for rigorous estimations of eigenvectors, eigenspaces and eigenvalues of a matrix. The key notion is the cone-domination and is inspired by ideas from hyperbolic dynamical systems. We present theorems which…

Dynamical Systems · Mathematics 2015-05-20 Łukasz Struski , Jacek Tabor , Piotr Zgliczyński

Estimating the eigenvalues of non-normal matrices is a foundational problem with far-reaching implications, from modeling non-Hermitian quantum systems to analyzing complex fluid dynamics. Yet, this task remains beyond the reach of standard…

Quantum Physics · Physics 2025-10-23 Yukun Zhang , Yusen Wu , Xiao Yuan

We apply set-valued numerical methods to compute an accurate enclosure of the rotation number. The described algorithm is supplemented with a method of proving the existence of periodic points, which is used to check the rationality of the…

Dynamical Systems · Mathematics 2015-09-25 Anna Belova

Agents in cyber-physical systems are increasingly entrusted with safety-critical tasks. Ensuring safety of these agents often requires localizing the pose for subsequent actions. Pose estimates can, e.g., be obtained from various…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Tobias Ladner , Yasser Shoukry , Matthias Althoff

Non-Hermitian operators naturally arise in the description of open quantum systems, which exhibit features such as resonances and decay processes, where the associated eigenvalues are complex. Standard quantum algorithms, including the…

Quantum Physics · Physics 2026-04-01 Durgesh Pandey , Ankit Kumar Das , P. Arumugam

Wireless indoor localization using predictive models with received signal strength information (RSSI) requires proper calibration for reliable position estimates. One remedy is to employ synthetic labels produced by a (generally different)…

Machine Learning · Computer Science 2026-05-22 Seonghoon Yoo , Houssem Sifaou , Sangwoo Park , Joonhyuk Kang , Osvaldo Simeone

We present a new approach to compute eigenvalues and eigenvectors of locally definite multiparameter eigenvalue problems by its signed multiindex. The method has the interpretation of a semismooth Newton method applied to certain functions…

Numerical Analysis · Mathematics 2025-01-20 Henrik Eisenmann

Location retrieval based on visual information is to retrieve the location of an agent (e.g. human, robot) or the area they see by comparing the observations with a certain form of representation of the environment. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2022-08-02 Lijun Wei , Valerie Gouet-Brunet , Anthony Cohn

Fingerprint verification is an important bio-metric technique for personal identification. Most of the automatic verification systems are based on matching of fingerprint minutiae. Extraction of minutiae is an essential process which…

Computer Vision and Pattern Recognition · Computer Science 2017-10-17 Eman Alibeigi , Shadrokh Samavi , Shahram Shirani , Zahra Rahmani

This article deals with the efficient and certified numerical approximation of the smallest eigenvalue and the associated eigenspace of a large-scale parametric Hermitian matrix. For this aim, we rely on projection-based model order…

Numerical Analysis · Mathematics 2026-01-14 Mattia Manucci , Benjamin Stamm , Zhuoyao Zeng

We present a mathematically justifiable, computationally simple, sample eigenvalue based procedure for estimating the number of high-dimensional signals in white noise using relatively few samples. The main motivation for considering a…

Statistics Theory · Mathematics 2007-05-23 N. Raj Rao , Alan Edelman

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite…

Mathematical Physics · Physics 2022-02-03 Joshua Feinberg , Roman Riser

We present a set of efficient techniques in first-principles electronic-structure calculations utilizing the real-space finite-difference method. These techniques greatly reduce the overhead for performing integrals that involve…

Materials Science · Physics 2009-11-10 Tomoya Ono , Kikuji Hirose

Modern state estimation is often formulated as an optimization problem and solved using efficient local search methods. These methods at best guarantee convergence to local minima, but, in some cases, global optimality can also be…

Robotics · Computer Science 2022-11-28 Connor Holmes , Timothy D. Barfoot

Let ({\lambda}, v) be a known real eigenpair of a square real matrix A. In this paper it is shown how to locate the other eigenvalues of A in terms of the components of v. The obtained region is a union of Gershgorin discs of the second…

Combinatorics · Mathematics 2020-06-24 Rachid Marsli , Frank J. Hall

A new proof is given for why the non-Hermitian, PT-Invariant cubic oscillator with imaginary coupling has real eigenvalues. The proof consists of two steps. In the first step, it is shown that for many PT-Invariant Hamiltonians, one can…

Mathematical Physics · Physics 2009-10-28 Scott Chapman

The eigenvector-eigenvalue identity relates the eigenvectors of a Hermitian matrix to its eigenvalues and the eigenvalues of its principal submatrices in which the jth row and column have been removed. We show that one-dimensional arrays of…

Quantum Physics · Physics 2020-03-11 Henning U. Voss , Douglas J. Ballon

Dimensional reduction of high dimensional data can be achieved by keeping only the relevant eigenmodes after principal component analysis. However, differentiating relevant eigenmodes from the random noise eigenmodes is problematic. A new…

Data Analysis, Statistics and Probability · Physics 2008-12-31 Yu Ding , Yiu-Cho Chung , Kun Huang , Orlando P. Simonetti