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A fast and reliable geometry optimization algorithm is presented that optimizes atomic positions and lattice vectors simultaneously. Using a series of benchmarks, it is shown that the method presented in this paper outperforms in most cases…

Computational Physics · Physics 2024-12-05 Moritz Gubler , Marco Krummenacher , Hannes Huber , Stefan Goedecker

We devise an approach for targeted molecular design, a problem of interest in computational drug discovery: given a target protein site, we wish to generate a chemical with both high binding affinity to the target and satisfactory…

Artificial Intelligence · Computer Science 2018-09-07 Tristan Aumentado-Armstrong

Large-scale eigenvalue problems pose a significant challenge to classical computers. While there are efficient quantum algorithms for unitary or Hermitian matrices, eigenvalue problems for non-normal matrices remain open in quantum…

Quantum Physics · Physics 2026-03-25 Honghong Lin , Yun Shang

We propose to relax geometries throughout chemical compound space (CCS) using alchemical perturbation density functional theory (APDFT). APDFT refers to perturbation theory involving changes in nuclear charges within approximate solutions…

Chemical Physics · Physics 2024-01-10 Giorgio Domenichini , O. Anatole von Lilienfeld

This article is an introduction to a new approach to first principles electronic structure calculation. The starting point is the Hartree-Fock-Roothaan equation, in which molecular integrals are approximated by polynomials by way of Taylor…

Computational Physics · Physics 2019-07-18 Akihito Kikuchi

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their…

Materials Science · Physics 2017-05-24 Xiao-Tian Li , Xiao-bao Yang , Yu-Jun Zhao

Three algorithms are developed for uncertainty quantification in modeling coupled Stokes and Darcy flows. The porous media may consist of multiple regions with different properties. The permeability is modeled as a non-stationary stochastic…

Numerical Analysis · Mathematics 2019-03-05 Ilona Ambartsumyan , Eldar Khattatov , ChangQing Wang , Ivan Yotov

We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem into independent subproblems and treats the interactions…

Quantum Physics · Physics 2026-03-11 Maxime Dupont , Bhuvanesh Sundar , Meenambika Gowrishankar

Harnessing the local topography of the loss landscape is a central challenge in advanced optimization tasks. By accounting for the effect of potential parameter changes, we can alter the model more efficiently. Contrary to standard…

Machine Learning · Computer Science 2024-11-27 Jed A. Duersch , Tommie A. Catanach , Alexander Safonov , Jeremy Wendt

We describe a framework in which is possible to develop and implement algorithms for the approximation of invariant measures of dynamical systems with a given bound on the error of the approximation. Our approach is based on a general…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli

We present a real-space formulation and higher-order finite-difference implementation of periodic Orbital-free Density Functional Theory (OF-DFT). Specifically, utilizing a local reformulation of the electrostatic and kernel terms, we…

Computational Physics · Physics 2015-12-23 Swarnava Ghosh , Phanish Suryanarayana

This paper puts forth a new formulation and algorithm for the elastic matching problem on unparametrized curves and surfaces. Our approach combines the frameworks of square root normal fields and varifold fidelity metrics into a novel…

Differential Geometry · Mathematics 2019-03-05 Martin Bauer , Nicolas Charon , Philipp Harms

A new method to represent and approximate rotation matrices is introduced. The method represents approximations of a rotation matrix $Q$ with linearithmic complexity, i.e. with $\frac{1}{2}n\lg(n)$ rotations over pairs of coordinates,…

Machine Learning · Computer Science 2014-04-30 Michael Mathieu , Yann LeCun

We study the problem of distributional matrix completion: Given a sparsely observed matrix of empirical distributions, we seek to impute the true distributions associated with both observed and unobserved matrix entries. This is a…

Machine Learning · Statistics 2025-06-09 Jacob Feitelberg , Kyuseong Choi , Anish Agarwal , Raaz Dwivedi

Performing density functional theory (DFT) calculations requires a careful choice of computational parameters to ensure convergence and obtain meaningful results. This represents a particularly important problem for high-throughput and…

For predictive modeling relying on Bayesian inversion, fully independent, or ``mean-field'', Gaussian distributions are often used as approximate probability density functions in variational inference since the number of variational…

Methodology · Statistics 2023-07-14 Wyatt Bridgman , Reese Jones , Mohammad Khalil

One of the open problems in nuclear structure is how to predict properties of finite nuclei from the knowledge of a bare nucleon-nucleon interaction of the meson-exchange type. We point out that a promising starting point consists in…

Nuclear Theory · Physics 2014-11-20 Nguyen Van Giai , Brett V. Carlson , Zhongyu Ma , Hermann Wolter

We benchmark angular-momentum projected{-after-variation} Hartree-Fock calculations as an approximation to full configuration-interaction results in a shell model basis. For such a simple approximation we find reasonably good agreement…

Nuclear Theory · Physics 2021-11-12 Stephanie M. Lauber , Hayden C. Frye , Calvin W. Johnson

We have recently discussed an algorithm to automatically generate auxiliary basis sets (ABSs) of the standard form for density fitting (DF) or resolution-of-the-identity (RI) calculations in a given atomic orbital basis set (OBS) of any…

Computational Physics · Physics 2023-10-30 Susi Lehtola

The complexity of the standard hierarchy of quantum chemistry methods is not invariant to the choice of representation. This work explores how the scaling of common quantum chemistry methods can be reduced using real-space, momentum-space,…

Chemical Physics · Physics 2018-02-14 Narbe Mardirossian , James D. McClain , Garnet Kin-Lic Chan