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Gaussian process regression has recently emerged as a powerful, system-agnostic tool for building global potential energy surfaces (PES) of polyatomic molecules. While the accuracy of GP models of PES increases with the number of potential…

Chemical Physics · Physics 2019-07-23 Jun Dai , Roman V. Krems

A shape sensitive, variational approach for the matching of surfaces considered as thin elastic shells is investigated. The elasticity functional to be minimized takes into account two different types of nonlinear energies: a membrane…

Optimization and Control · Mathematics 2021-06-09 José A. Iglesias , Martin Rumpf , Otmar Scherzer

We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where…

Numerical Analysis · Mathematics 2014-11-21 Liliana Borcea , Vladimir Druskin , Alexander V. Mamonov , Mikhail Zaslavsky

Physically accurate and mathematically tractable models are presented to characterize scattering and reflection properties of reconfigurable intelligent surfaces (RISs). We take continuous and discrete strategies to model a single patch and…

Systems and Control · Electrical Eng. & Systems 2022-08-31 Tiebin Mi , Jianan Zhang , Rujing Xiong , Zhengyu Wang , Robert Caiming Qiu

In this work, we propose and analyze optimization strategies for the VQE algorithm that combine various methods, including molecular point group symmetries (symmetry adaptation), compact excitation circuits (qubit-excitation-based),…

Quantum Physics · Physics 2025-04-30 Konstantin M. Makushin , Aleksey K. Fedorov

We propose a new adaptive algorithm for the approximation of the Landau-Lifshitz-Gilbert equation via a higher-order tangent plane scheme. We show that the adaptive approximation satisfies an energy inequality and demonstrate numerically,…

Numerical Analysis · Mathematics 2026-02-06 Jan Bohn , Willy Dörfler , Michael Feischl , Stefan Karch

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

Monitoring ozone concentrations in the Earth's atmosphere using spectroscopic methods is a major activity which undertaken both from the ground and from space. However there are long-running issues of consistency between measurements made…

Atmospheric and Oceanic Physics · Physics 2018-04-22 Oleg L. Polyansky , Nikolai F. Zobov , Irina I. Mizus , Aleksandra A. Kyuberis , Lorenzo Lodi , Jonathan Tennyson

Fluid-Structure Interaction (FSI) is a crucial problem in ocean engineering. The smoothed particle hydrodynamics (SPH) method has been employed recently for FSI problems in light of its Lagrangian nature and its advantage in handling…

Fluid Dynamics · Physics 2023-07-19 Tianrun Gao , Huihe Qiu , Lin Fu

We present an adaptive refinement algorithm for T-splines on unstructured 2D meshes. While for structured 2D meshes, one can refine elements alternatingly in horizontal and vertical direction, such an approach cannot be generalized directly…

Numerical Analysis · Mathematics 2022-05-03 Roland Maier , Philipp Morgenstern , Thomas Takacs

The interaction between two particles with shape or interaction anisotropy can be modeled using a pairwise potential energy function that depends on their relative position and orientation; however, this function is often challenging to…

Soft Condensed Matter · Physics 2025-03-03 Mohammadreza Fakhraei , Chris A. Kieslich , Michael P. Howard

Machine Learning techniques can be used to represent high-dimensional potential energy surfaces for reactive chemical systems. Two such methods are based on a reproducing kernel Hilbert space representation or on deep neural networks. They…

Chemical Physics · Physics 2019-09-19 Oliver T. Unke , Markus Meuwly

This article presents a new and efficient alternative to well established algorithms for molecular geometry optimization. The new approach exploits the approximate decoupling of molecular energetics in a curvilinear internal coordinate…

Materials Science · Physics 2007-05-23 Károly Németh , Matt Challacombe

Reconstruction of geometry based on different input modes, such as images or point clouds, has been instrumental in the development of computer aided design and computer graphics. Optimal implementations of these applications have…

Computer Vision and Pattern Recognition · Computer Science 2019-01-15 Jun Gao , Chengcheng Tang , Vignesh Ganapathi-Subramanian , Jiahui Huang , Hao Su , Leonidas J. Guibas

We generalize the transfinite triangular interpolant of (Nielson, 1987) in order to generate visually smooth (not necessarily polynomial) local interpolating quasi-optimal triangular spline surfaces. Given as input a triangular mesh stored…

Numerical Analysis · Mathematics 2016-04-08 Ágoston Róth

The question of adaptive mesh generation for approximation by splines has been studied for a number of years by various authors. The results have numerous applications in computational and discrete geometry, computer aided geometric design,…

Numerical Analysis · Mathematics 2011-01-14 Yuliya Babenko

The paper presents a new method for shape and topology optimization based on an efficient and scalable boundary integral formulation for elasticity. To optimize topology, our approach uses iterative extraction of isosurfaces of a…

Optimization and Control · Mathematics 2016-12-14 Igor Ostanin , Ivan Tsybulin , Mikhail Litsarev , Ivan Oseledets , Denis Zorin

Critical points of energy functionals, which are of broad interest, for instance, in physics and chemistry, in solid and quantum mechanics, in material science, or in general diffusion-reaction models arise as solutions to the associated…

Numerical Analysis · Mathematics 2025-10-20 Pascal Heid , Thomas P. Wihler

A new gradient-based adaptive sampling method is proposed for design of experiments applications which balances space filling, local refinement, and error minimization objectives while reducing reliance on delicate tuning parameters. High…

Methodology · Statistics 2024-05-09 Lucas Caparini , Gwynn J. Elfring , Mauricio Ponga

We describe the development of machine-learned potentials of atmospheric gases with flexible monomers for molecular simulations. A recently suggested permutationally invariant polynomial neural network (PIP-NN) approach is utilized to…

Chemical Physics · Physics 2025-04-21 Artem Finenko