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We present an algorithm where only the Cholesky basis is determined in the decomposition procedure. This allows for improved screening and a partitioned matrix decomposition scheme, both of which significantly reduce memory usage and…

化学物理 · 物理学 2019-06-05 Sarai D. Folkestad , Eirik F. Kjønstad , Henrik Koch

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…

化学物理 · 物理学 2025-12-29 Luca Melega , Tommaso Nottoli , Jürgen Gauss , Filippo Lipparini

To treat the electronic structure of large molecules by electron propagator methods we developed a parallel computer program called P-RICD$\Sigma$. The program exploits the sparsity of the two-electron integral matrix by using Cholesky…

化学物理 · 物理学 2010-01-28 Victor P. Vysotskiy , Lorenz S. Cederbaum

In this paper we present a method for matrix inversion based on Cholesky decomposition with reduced number of operations by avoiding computation of intermediate results; further, we use fixed point simulations to compare the numerical…

数学软件 · 计算机科学 2013-10-21 Aravindh Krishnamoorthy , Deepak Menon

In this contribution, we present the implementation of a second-order CASSCF algorithm in conjunction with the Cholesky decomposition of the two-electron repulsion integrals. The algorithm, called Norm-Extended Optimization, guarantees…

化学物理 · 物理学 2021-04-09 Tommaso Nottoli , Jürgen Gauss , Filippo Lipparini

The Cholesky decomposition is a fundamental tool for solving linear systems with symmetric and positive definite matrices which are ubiquitous in linear algebra, optimization, and machine learning. Its numerical stability can be improved by…

机器学习 · 计算机科学 2025-07-29 Filip de Roos , Fabio Muratore

This paper introduces a new method for minimizing matrix-smooth non-convex objectives through the use of novel Compressed Gradient Descent (CGD) algorithms enhanced with a matrix-valued stepsize. The proposed algorithms are theoretically…

最优化与控制 · 数学 2024-04-23 Hanmin Li , Avetik Karagulyan , Peter Richtárik

In large-scale quantum-chemical calculations the electron-repulsion integral (ERI) tensor rapidly becomes the bottleneck in terms of memory and disk space. When an external finite magnetic field is employed, this problem becomes even more…

化学物理 · 物理学 2022-02-16 Simon Blaschke , Stella Stopkowicz

In the present article, we introduce the relativistic Cholesky-decomposed density (CDD) matrix second-order M{\o}ller-Plesset perturbation theory (MP2) energies. The working equations are formulated in terms of the usual intermediates of…

化学物理 · 物理学 2018-12-26 Benjamin Helmich-Paris , Michal Repisky , Lucas Visscher

We report a complete implementation of the coupled-cluster method with single, double, and triple excitations (CCSDT) where tensor decompositions are used to reduce its scaling and overall computational costs. For the decomposition of the…

化学物理 · 物理学 2020-02-20 Michał Lesiuk

In this paper, we propose a scalable algorithm for spectral embedding. The latter is a standard tool for graph clustering. However, its computational bottleneck is the eigendecomposition of the graph Laplacian matrix, which prevents its…

机器学习 · 计算机科学 2019-04-12 Mireille El Gheche , Giovanni Chierchia , Pascal Frossard

Implicit neural representations (INRs) provide a parameter-efficient and fully differentiable image model for CT reconstruction. However, optimizing INRs for CT reconstruction using standard auto-differentiation techniques can be…

图像与视频处理 · 电气工程与系统科学 2026-04-14 Mahrokh Najaf , Gregory Ongie

Large kernel systems are prone to be ill-conditioned. Pivoted Cholesky decomposition (PCD) render a stable and efficient solution to the systems without a perturbation of regularization. This paper proposes a new PCD algorithm by tuning…

数值分析 · 数学 2019-04-29 Dishi Liu , Hermann G. Matthies

This paper presents an efficient gradient projection-based method for structural topological optimization problems characterized by a nonlinear objective function which is minimized over a feasible region defined by bilateral bounds and a…

计算工程、金融与科学 · 计算机科学 2020-06-16 Zhi Zeng , Fulei Ma

Deep unfolding is a promising deep-learning technique, whose network architecture is based on expanding the recursive structure of existing iterative algorithms. Although convergence acceleration is a remarkable advantage of deep unfolding,…

机器学习 · 计算机科学 2020-10-27 Satoshi Takabe , Tadashi Wadayama

We consider the problem of minimizing the composition of a smooth (nonconvex) function and a smooth vector mapping, where the inner mapping is in the form of an expectation over some random variable or a finite sum. We propose a stochastic…

最优化与控制 · 数学 2019-06-26 Junyu Zhang , Lin Xiao

We present an efficient implementation of the low-cost linear-response coupled-cluster singles and doubles (LR-CCSD) method for computing static and frequency-dependent polarizabilities in systems with significant relativistic and…

化学物理 · 物理学 2026-04-15 Sudipta Chakraborty , Muskan Begom , Xubo Wang , Achintya Kumar Dutta

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…

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…

Electron cryomicroscopy (cryo-EM) is an imaging technique widely used in structural biology to determine the three-dimensional structure of biological molecules from noisy two-dimensional projections with unknown orientations. As the…

数值分析 · 数学 2025-06-26 Bogdan Toader , Marcus A. Brubaker , Roy R. Lederman
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