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The efficient and accurate QR decomposition for matrices with hierarchical low-rank structures, such as HODLR and hierarchical matrices, has been challenging. Existing structure-exploiting algorithms are prone to numerical instability as…

Numerical Analysis · Mathematics 2018-09-28 Daniel Kressner , Ana Susnjara

We consider the problem of finding the optimal coefficient vector that maximizes the computation rate at a relay in the compute-and-forward scheme. Based on the idea of sphere decoding, we propose a highly efficient algorithm that finds the…

Information Theory · Computer Science 2016-06-28 Jinming Wen , Baojian Zhou , Wai Ho Mow , Xiao-Wen Chang

The dominant cost in solving least-square problems using Newton's method is often that of factorizing the Hessian matrix over multiple values of the regularization parameter ($\lambda$). We propose an efficient way to interpolate the…

Machine Learning · Computer Science 2015-06-11 Da Kuang , Alex Gittens , Raffay Hamid

In recent years, randomized algorithms have established themselves as fundamental tools in computational linear algebra, with applications in scientific computing, machine learning, and quantum information science. Many randomized matrix…

Numerical Analysis · Mathematics 2025-12-19 Ethan N. Epperly

In this paper, we present a finite element method (FEM) framework enhanced by an operator-adapted wavelet decomposition algorithm designed for the efficient analysis of multiscale electromagnetic problems. Usual adaptive FEM approaches,…

Computational Physics · Physics 2026-02-18 F. Şık , F. L. Teixeira , B. Shanker

Solving a Poisson equation is generally reduced to solving a linear system with a coefficient matrix $A$ of entries $a_{ij}$, $i,j=1,2,...,n$, from the discretized Poisson equation. Although the variational quantum algorithms are promising…

Quantum Physics · Physics 2023-09-25 Hui-Min Li , Zhi-Xi Wang , Shao-Ming Fei

Logarithms of determinants of large positive definite matrices appear ubiquitously in machine learning applications including Gaussian graphical and Gaussian process models, partition functions of discrete graphical models, minimum-volume…

Data Structures and Algorithms · Computer Science 2015-03-24 Insu Han , Dmitry Malioutov , Jinwoo Shin

This paper studies the estimation of large precision matrices and Cholesky factors obtained by observing a Gaussian process at many locations. Under general assumptions on the precision and the observations, we show that the sample…

Statistics Theory · Mathematics 2025-03-25 Jiaheng Chen , Daniel Sanz-Alonso

We present an algorithm for computing a spectral decomposition of an interval matrix as an enclosure of spectral decompositions of particular realizations of interval matrices. The algorithm relies on tight outer estimations of eigenvalues…

Numerical Analysis · Mathematics 2025-10-07 David Hartman , Milan Hladík , David Říha

A Cholesky decomposition (CD)-based implementation of relativistic two-component coupled-cluster (CC) and equation-of-motion CC (EOM-CC) methods using an exact two-component Hamiltonian augmented with atomic-mean-field spin-orbit integrals…

Chemical Physics · Physics 2023-09-19 Chaoqun Zhang , Filippo Lipparini , Stella Stopkowicz , Jürgen Gauss , Lan Cheng

We present a novel and efficient implementation of coupled-cluster with singles and doubles (CCSD) analytic gradients that combines the Cholesky decomposition (CD) of electron-repulsion integrals with the exploitation of Abelian point-group…

Chemical Physics · Physics 2025-12-29 Luca Melega , Tommaso Nottoli , Jürgen Gauss , Filippo Lipparini

Single particle cryo-electron microscopy has become a critical tool in structural biology over the last decade, able to achieve atomic scale resolution in three dimensional models from hundreds of thousands of (noisy) two-dimensional…

Numerical Analysis · Mathematics 2023-07-19 Aaditya V. Rangan , Leslie Greengard

In this paper, we consider the estimation and inference of precision matrices of a rich class of locally stationary and nonlinear time series assuming that only one realization of the time series is observed. Using a Cholesky decomposition…

Statistics Theory · Mathematics 2019-08-15 Xiucai Ding , Zhou Zhou

This paper presents new quadrature rules for functions in a reproducing kernel Hilbert space using nodes drawn by a sampling algorithm known as randomly pivoted Cholesky. The resulting computational procedure compares favorably to previous…

Numerical Analysis · Mathematics 2023-12-08 Ethan N. Epperly , Elvira Moreno

The paper explores the numerical stability and the computational efficiency of a direct method for unfolding the resolution function from the measurements of the neutron induced reactions. A detailed resolution function formalism is laid…

The efficient compression of kernel matrices, for instance the off-diagonal blocks of discretized integral equations, is a crucial step in many algorithms. In this paper, we study the application of Skeletonized Interpolation to construct…

Numerical Analysis · Mathematics 2018-07-16 Zixi Xu , Léopold Cambier , François-Henry Rouet , Pierre L'Eplatennier , Yun Huang , Cleve Ashcraft , Eric Darve

Most modern calculations of many-electron atoms use basis sets of atomic orbitals. An accurate account for the electronic correlations in heavy atoms is very difficult computational problem and optimization of the basis sets can reduce…

Atomic Physics · Physics 2024-01-17 M. G. Kozlov , Yu. A. Demidov , M. Y. Kaygorodov , E. V. Triapitsyna

We present an implementation for the use of Cholesky decomposition (CD) of two-electron integrals within the spin-free Dirac-Coulomb (SFDC) scheme that enables to perform high-accuracy coupled-cluster (CC) calculations at costs almost…

Chemical Physics · Physics 2024-07-02 Tereza Uhlířová , Davide Cianchino , Tommaso Nottoli , Filippo Lipparini , Jürgen Gauss

Astrochemical simulations are a powerful tool for revealing chemical evolution in the interstellar medium. Astrochemical calculations require efficient processing of large matrices for the chemical networks. The large chemical reaction…

Instrumentation and Methods for Astrophysics · Physics 2023-12-11 Kazutaka Motoyama , Ruben Krasnopolsky , Hsien Shang , Kento Aida , Eisaku Sakane

We describe an algorithm to efficiently compute the second-Born self-energy of many-body perurbation theory. The core idea consists in dissecting the set of all four-index Coulomb integrals into properly chosen subsets, thus avoiding to…

Other Condensed Matter · Physics 2019-09-04 E. Perfetto , G. Stefanucci