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Quantum algorithms for estimating the eigenvalues of matrices, including the phase estimation algorithm, serve as core subroutines in a wide range of quantum algorithms, including those in quantum chemistry and quantum machine learning. The…

Quantum Physics · Physics 2025-09-03 Abhijeet Alase , Salini Karuvade

The main contribution of this paper is twofold: On the one hand, a general framework for performing Hermite interpolation on Riemannian manifolds is presented. The method is applicable, if algorithms for the associated Riemannian…

Numerical Analysis · Mathematics 2021-12-20 Ralf Zimmermann

This paper exploits a basic connection between sequential quadratic programming and Riemannian gradient optimization to address the general question of selecting a metric in Riemannian optimization, in particular when the Riemannian…

Optimization and Control · Mathematics 2016-03-10 Bamdev Mishra , Rodolphe Sepulchre

A method is suggested to obtain solutions of the various quantum optical Hamiltonians in the framework of the asymptotic iteration method. We extend the notion of asymptotic iteration method to solve the 2 \times 2 matrix Hamiltonians. On a…

Quantum Physics · Physics 2008-03-06 Ramazan Koc , Okan Ozer , Hayriye Tutunculer

Dynamical Mean Field Theory (DMFT) is one of the powerful computational approaches to study electron correlation effects in solid-state materials and molecules. Its practical applicability is, however, limited by the quantity of numerical…

Strongly Correlated Electrons · Physics 2024-12-23 Jannis Ehrlich , Daniel Urban , Christian Elsässer

Such problems as computation of spectra of spin chains and vibrational spectra of molecules can be written as high-dimensional eigenvalue problems, i.e., when the eigenvector can be naturally represented as a multidimensional tensor. Tensor…

Numerical Analysis · Mathematics 2019-09-04 Maxim Rakhuba , Alexander Novikov , Ivan Oseledets

We propose a quantum algorithm based on ridge regression model, which get the optimal fitting parameters w and a regularization hyperparameter {\alpha} by analysing the training dataset. The algorithm consists of two subalgorithms. One is…

Quantum Physics · Physics 2021-04-28 Menghan Chen , Chaohua Yu , Gongde Guo , Song Lin

The low-rank quaternion matrix approximation has been successfully applied in many applications involving signal processing and color image processing. However, the cost of quaternion models for generating low-rank quaternion matrix…

Numerical Analysis · Mathematics 2024-03-01 Peng-Ling Wu , Kit Ian Kou , Hongmin Cai , Zhaoyuan Yu

We consider PDE eigenvalue problems as they occur in two-dimensional photonic crystal modeling. If the permittivity of the material is frequency-dependent, then the eigenvalue problem becomes nonlinear. In the lossless case, linearization…

Numerical Analysis · Mathematics 2019-12-03 Robert Altmann , Marine Froidevaux

In this paper, we extend the Chen and Moore determinants of quaternion Hermitian} matrices to dual quaternion Hermitian matrices. We show the Chen determinant of dual quaternion Hermitian {matrices is invariant under addition, switching,…

Rings and Algebras · Mathematics 2024-05-21 Chunfeng Cui , Liqun Qi , Guangjing Song , Qingwen Wang

We obtain accurate eigenvalues for two recently derived SUSY partner Hamiltonians. We improve the Rayleigh-Ritz variational method proposed by the authors and show how to apply the Riccati-Pad\'{e} method to those particular partner…

Mathematical Physics · Physics 2015-06-04 Francisco M. Fernández

We describe a new polynomial time quantum algorithm that uses the quantum fast fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases (commonly found in ab initio physics and…

Quantum Physics · Physics 2009-01-23 Daniel S. Abrams , Seth Lloyd

Here we revisit the quantum phase estimation (QPE) algorithm, and devise an iterative method to improve the precision of QPE with propagators over a variety of time spans. For a given propagator and a certain eigenstate as input, QPE with…

Quantum Physics · Physics 2024-04-09 Junxu Li

Polynomial filtering can provide a highly effective means of computing all eigenvalues of a real symmetric (or complex Hermitian) matrix that are located in a given interval, anywhere in the spectrum. This paper describes a technique for…

Numerical Analysis · Mathematics 2015-12-29 Ruipeng Li , Yuanzhe Xi , Eugene Vecharynski , Chao Yang , Yousef Saad

The VQE algorithm has turned out to be quite expensive to run given the way we currently access quantum processors (i.e. over the cloud). In order to alleviate this issue, we introduce Quantum Sampling Regression (QSR), an alternative…

Quantum Physics · Physics 2020-12-07 Pedro Rivero , Ian C. Cloët , Zack Sullivan

The Rayleigh quotient, which provides the classical variational characterization of the spectral radius of Hermitian matrices, can be extended to nonsymmetric nonnegative irreducible matrices, ${\bf A}$, by the inclusion of a diagonal…

Spectral Theory · Mathematics 2020-01-01 Lee Altenberg

Preconditioned eigenvalue solvers (eigensolvers) are gaining popularity, but their convergence theory remains sparse and complex. We consider the simplest preconditioned eigensolver--the gradient iterative method with a fixed step size--for…

Numerical Analysis · Mathematics 2010-06-02 Andrew V. Knyazev , Klaus Neymeyr

We propose a verified computation method for partial eigenvalues of a Hermitian generalized eigenproblem. The block Sakurai-Sugiura Hankel method, a contour integral-type eigensolver, can reduce a given eigenproblem into a generalized…

Numerical Analysis · Mathematics 2022-05-30 Akira Imakura , Keiichi Morikuni , Akitoshi Takayasu

While perturbation theories constitute a significant foundation of modern quantum system analysis, extending them from the Hermitian to the non-Hermitian regime remains a non-trivial task. In this work, we generalize the…

Quantum Physics · Physics 2025-11-18 Wei-Ming Chen , Yen-Ting Lin , Chia-Yi Ju

The variational quantum eigensolver (VQE) is a hybrid quantum-classical variational algorithm that produces an upper-bound estimate of the ground-state energy of a Hamiltonian. As quantum computers become more powerful and go beyond the…