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We propose a low-computational strategy for the efficient implementation of the "atom selection step" in sparse representation algorithms. The proposed procedure is based on simple tests enabling to identify subsets of atoms which cannot be…

Signal Processing · Electrical Eng. & Systems 2018-12-06 Clément Dorffer , Angélique Drémeau , Cedric Herzet

We show how the path-integral formulation of quantum statistical mechanics can be used to construct practical {\em ab initio} techniques for computing the chemical potential of molecules adsorbed on surfaces, with full inclusion of quantum…

Materials Science · Physics 2015-05-18 D. Alfe` , M. J. Gillan

The random phase approximation (RPA) has emerged as a prominent first-principles method in material science, particularly to study the adsorption and chemisorption of small molecules on surfaces. However, its widespread application is…

Materials Science · Physics 2025-09-01 Edoardo Spadetto , Pier Herman Theodoor Philipsen , Arno Förster , Lucas Visscher

We introduce new techniques for calculations in Gauge theories with extended supersymmetry. We are working in Projective Superspace where the $SU(2)$ R-symmetry is realized geometrically by including an auxilliary $\mathbb{CP}^1$ component…

High Energy Physics - Theory · Physics 2023-07-07 Ariunzul Davgadorj , Ulf Lindström , Rikard von Unge

Motivated by a large ground-level ozone dataset, we propose a new computationally efficient additive approximate Gaussian process. The proposed method incorporates a computational-complexity-reduction method and a separable covariance…

Methodology · Statistics 2019-06-10 Pulong Ma , Bledar A. Konomi , Emily L. Kang

A new scheme for constructing approximate effective electron potentials within density-functional theory is proposed. The scheme consists of calculating the effective potential for a series of reference systems, and then using these…

Condensed Matter · Physics 2016-08-14 K. Stokbro , N. Chetty , K. W. Jacobsen , J. K. Nørskov

We present a new use of Answer Set Programming (ASP) to discover the molecular structure of chemical samples based on the relative abundance of elements and structural fragments, as measured in mass spectrometry. To constrain the…

Logic in Computer Science · Computer Science 2026-02-25 Nils Küchenmeister , Alex Ivliev , Markus Krötzsch

In this article we present an algorithm to efficiently evaluate the exchange matrix in periodic systems when Gaussian basis set with pseudopotentials are used. The usual algorithm for evaluating exchange matrix scales cubically with the…

Strongly Correlated Electrons · Physics 2022-11-11 Sandeep Sharma , Alec F. White , Gregory Beylkin

A grid-based real-space implementation of the Projector Augmented Wave (PAW) method of P. E. Blochl [Phys. Rev. B 50, 17953 (1994)] for Density Functional Theory (DFT) calculations is presented. The use of uniform 3D real-space grids for…

Materials Science · Physics 2009-11-10 J. J. Mortensen , L. B. Hansen , K. W. Jacobsen

We propose efficient classical algorithms which (strongly) simulate the action of bosonic linear optics circuits applied to superpositions of Gaussian states. Our approach relies on an augmented covariance matrix formalism to keep track of…

Quantum Physics · Physics 2025-11-19 Beatriz Dias , Robert Koenig

Physics-inspired molecular representations are the cornerstone of similarity-based learning applied to solve chemical problems. Despite their conceptual and mathematical diversity, this class of descriptors shares a common underlying…

Chemical Physics · Physics 2024-02-21 Alberto Fabrizio , Ksenia R. Briling , Clemence Corminboeuf

We demonstrate how to determine numerically nearly exact orthonormal orbitals that are optimal for evaluation of the energy of arbitrary (correlated) states of atoms and molecules by minimization of the energy Lagrangian. Orbitals are…

This is a follow-up of our recently proposed work on pseudopotential calculation (Ref. [21]) of atoms and molecules within DFT framework, using cartesian coordinate grid. Detailed results are presented to demonstrate the usefulness,…

Chemical Physics · Physics 2015-05-18 Amlan K. Roy

A Gaussian Approximation Potential (GAP) was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics identifies (101) and…

We present a simple, yet general, end-to-end deep neural network representation of the potential energy surface for atomic and molecular systems. This methodology, which we call Deep Potential, is "first-principle" based, in the sense that…

Computational Physics · Physics 2020-07-20 Jiequn Han , Linfeng Zhang , Roberto Car , Weinan E

We develop a new scheme for determining molecular partial atomic charges (PACs) with external electrostatic potential (ESP) closely mimicking that of the molecule. The PACs are the "minimal corrections" to a reference-set of PACs necessary…

Chemical Physics · Physics 2017-05-02 Rebecca Efrat Hadad , Roi Baer

Gaussian Process (GP) models are a class of flexible non-parametric models that have rich representational power. By using a Gaussian process with additive structure, complex responses can be modelled whilst retaining interpretability.…

Machine Learning · Statistics 2022-06-22 Xiaoyu Lu , Alexis Boukouvalas , James Hensman

A basis set of generalized nonspherical Gaussian functions (GGTOs) is presented and discussed. As a first example we report on Born-Oppenheimer energies of the hydrogen molecule. Although accurate results have been obtained, we conclude…

Chemical Physics · Physics 2009-10-31 T. Detmer , P. Schmelcher , L. S. Cederbaum

We develop methods to calculate the electroweak gauge boson contribution to the effective Higgs potential in the context of composite Higgs models, using lattice gauge theory. The calculation is analogous to that of the electromagnetic mass…

High Energy Physics - Lattice · Physics 2016-09-14 T. A. DeGrand , M. Golterman , W. I. Jay , E. T. Neil , Y. Shamir , B. Svetitsky

We present a general framework for the efficient simulation of realistic fermionic systems with modern machine learning inspired representations of quantum many-body states, towards a universal tool for ab initio electronic structure. These…

Strongly Correlated Electrons · Physics 2023-05-16 Yannic Rath , George H. Booth
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