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Krylov complexity, as a novel measure of operator complexity under Heisenberg evolution, exhibits many interesting universal behaviors and also bounds many other complexity measures. In this work, we study Krylov complexity $\mathcal{K}(t)$…

High Energy Physics - Theory · Physics 2024-01-01 Haifeng Tang

Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations. In this paper we show that \alpha>0.30298, which improves the previous…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall

We demonstrate that time-evolved operators can construct a Krylov space to compute Operator complexity and introduce Krylov observability as a measure of effective phase space dimension in quantum systems. We test Krylov observability in…

Quantum Physics · Physics 2026-03-10 Saud Čindrak , Kathy Lüdge , Lina Jaurigue

In the numerical treatment of large-scale Sylvester and Lyapunov equations, projection methods require solving a reduced problem to check convergence. As the approximation space expands, this solution takes an increasing portion of the…

Numerical Analysis · Mathematics 2017-02-03 Davide Palitta , Valeria Simoncini

Sampling from Gaussian Markov random fields (GMRFs), that is multivariate Gaussian ran- dom vectors that are parameterised by the inverse of their covariance matrix, is a fundamental problem in computational statistics. In this paper, we…

We consider the problem of approximating the von Neumann entropy of a large, sparse, symmetric positive semidefinite matrix $A$, defined as $\operatorname{tr}(f(A))$ where $f(x)=-x\log x$. After establishing some useful properties of this…

Numerical Analysis · Mathematics 2023-06-23 Michele Benzi , Michele Rinelli , Igor Simunec

The computation of approximating e^tA B, where A is a large sparse matrix and B is a rectangular matrix, serves as a crucial element in numerous scientific and engineering calculations. A powerful way to consider this problem is to use…

Numerical Analysis · Mathematics 2023-08-29 H. Barkouki , A. H. Bentbib , K. Jbilou

We introduce the Tensorized-and-Restricted Krylov (TReK) method, a simple and efficient algorithm for estimating covariance tensors with large observational sizes. TReK extends the conjugate gradient method to incorporate range…

Computation · Statistics 2025-09-03 Ho Yun , Victor M. Panaretos

We propose a fast collocation method based on Krylov subspace iterative solver on general nonuniform grids for the fractional Laplacian problem, in which the fractional operator is presented in a singular integral formulation. The method is…

Numerical Analysis · Mathematics 2025-11-13 Meijie Kong , Hongfei Fu

We propose a novel Krylov subspace method for estimating the finite impulse response (FIR) of a one-dimensional linear time-invariant systems. The method approximates the system's FIR using a kernel-based formulation combined with…

Numerical Analysis · Mathematics 2026-05-12 Fabio Matti , Martin Skovgaard Andersen , Tianshi Chen , Daniel Kressner

We indicate a strategy in order to construct bilinear multiplication algorithms of type Chudnovsky in large extensions of any finite field. In particular, by using the symmetric version of the generalization of Randriambololona specialized…

Algebraic Geometry · Mathematics 2013-03-29 Stéphane Ballet , Alexis Bonnecaze , Mila Tukumuli

Nesterov's well-known scheme for accelerating gradient descent in convex optimization problems is adapted to accelerating stationary iterative solvers for linear systems. Compared with classical Krylov subspace acceleration methods, the…

Optimization and Control · Mathematics 2021-08-10 Tao Hong , Irad Yavneh

The quadratic numerical range $W^2(A)$ is a subset of the standard numerical range of a linear operator which still contains its spectrum. It arises naturally in operators which have a $2 \times 2$ block structure, and it consists of at…

Numerical Analysis · Mathematics 2019-12-24 Andreas Frommer , Birgit Jacob , Karsten Kahl , Christian Wyss , Ian Zwaan

We investigate the Krylov complexity of Schr\"odinger field theories, focusing on both bosonic and fermionic systems within the grand canonical ensemble that includes a chemical potential. Krylov complexity measures operator growth in…

High Energy Physics - Theory · Physics 2025-03-21 Peng-Zhang He , Hai-Qing Zhang

We propose a novel algorithm based on inexact GMRES methods for linear response calculations in density functional theory. Such calculations require iteratively solving a nested linear problem $\mathcal{E} \delta\rho = b$ to obtain the…

Numerical Analysis · Mathematics 2025-10-30 Michael F. Herbst , Bonan Sun

This article deals with the computation of the characteristic polynomial of dense matrices over small finite fields and over the integers. We first present two algorithms for the finite fields: one is based on Krylov iterates and Gaussian…

Symbolic Computation · Computer Science 2016-08-16 Jean-Guillaume Dumas , Clément Pernet , Zhendong Wan

Among randomized numerical linear algebra strategies, so-called sketching procedures are emerging as effective reduction means to accelerate the computation of Krylov subspace methods for, e.g., the solution of linear systems, eigenvalue…

Numerical Analysis · Mathematics 2024-08-02 Davide Palitta , Marcel Schweitzer , Valeria Simoncini

This paper deals with linear algebra operations on Graphics Processing Unit (GPU) with complex number arithmetic using double precision. An analysis of their uses within iterative Krylov methods is presented to solve acoustic problems.…

Numerical Analysis · Mathematics 2021-12-23 Abal-Kassim Cheik Ahamed , Frederic Magoules

The estimation of weather forecast uncertainty with ensemble systems requires a careful selection of perturbations to establish a reliable sampling of the error growth potential in the phase space of the model. Usually, the singular vectors…

Dynamical Systems · Mathematics 2022-09-15 Jens Winkler , Michael Denhard , Bernhard A. Schmitt

In this paper, we present novel deterministic algorithms for multiplying two $n \times n$ matrices approximately. Given two matrices $A,B$ we return a matrix $C'$ which is an \emph{approximation} to $C = AB$. We consider the notion of…

Data Structures and Algorithms · Computer Science 2014-08-21 Shiva Manne , Manjish Pal