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Panel-based, kernel-split quadrature is currently one of the most efficient methods available for accurate evaluation of singular and nearly singular layer potentials in two dimensions. However, it can fail completely for the layer…

Numerical Analysis · Mathematics 2022-01-20 Fredrik Fryklund , Ludvig af Klinteberg , Anna-Karin Tornberg

We present the first quantum-centric simulations of noncovalent interactions using a supramolecular approach. We simulate the potential energy surfaces (PES) of the water and methane dimers, featuring hydrophilic and hydrophobic…

The concept of potential energy landscapes is applied in many areas of science. We experimentally realize a random potential energy landscape (rPEL) to which colloids are exposed. This is achieved exploiting the interaction of matter with…

Optics · Physics 2016-07-11 J. Bewerunge , S. U. Egelhaaf

We show that a Gaussian Process model can be combined with a small number (of order 100) of scattering calculations to provide a multi-dimensional dependence of scattering observables on the experimentally controllable parameters such as…

Chemical Physics · Physics 2015-08-19 Jie Cui , Roman V. Krems

Kernel embeddings have emerged as a powerful tool for representing probability measures in a variety of statistical inference problems. By mapping probability measures into a reproducing kernel Hilbert space (RKHS), kernel embeddings enable…

Machine Learning · Statistics 2024-10-31 Dino Sejdinovic

Transition state theory was introduced in the 1930s to account for chemical reactions. Central to this theory is the idea of a potential energy surface (PES). It was assumed that such a surface could be constructed using eigensolutions of…

Quantum Physics · Physics 2015-06-05 Brian T. Sutcliffe , R. Guy Woolley

A trivial flaw in the utilization of artificial neural networks in interpolating chemical potential energy surfaces (PES) whose descriptors are Cartesian coordinates is their dependence on simple translations and rotations of the molecule…

Chemical Physics · Physics 2020-09-15 Sean R. McConnell , Johannes Kästner

We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a…

High Energy Physics - Phenomenology · Physics 2024-07-12 Tobias Golling , Lukas Heinrich , Michael Kagan , Samuel Klein , Matthew Leigh , Margarita Osadchy , John Andrew Raine

We report a permutationally invariant polynomial (PIP) potential energy surface for the water 4-body interaction. This 12-atom PES is a fit to 2119, symmetry-unique, CCSD(T)-F12a/haTZ (aug-cc-pVTZ basis for 'O' atom and cc-pVTZ basis for…

Chemical Physics · Physics 2021-10-27 Apurba Nandi , Chen Qu , Paul L. Houston , Riccardo Conte , Joel M. Bowman

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD) [J. Chem.…

Chemical Physics · Physics 2017-11-22 Xinzijian Liu , Jian Liu

In this paper, an adaptive non-parametric method is proposed to estimate the scalar-valued nonlinear function that appears in uncertain systems governed by ordinary differential equations (ODEs). By employing an infinite-dimensional…

Optimization and Control · Mathematics 2021-03-15 Jia Guo , Sai Tej Paruchuri , Andrew J. Kurdila

Machine Learning (ML) approximations to Density Functional Theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present they are not applicable…

Chemical Physics · Physics 2020-03-05 Xiaowei Xie , Kristin A. Persson , David W. Small

Kernel methods approximate nonlinear maps in a data-driven manner by projecting the target map onto a finite-dimensional Hilbert space called the solution space. Traditionally, this space is a subspace of a fixed ambient reproducing kernel…

Numerical Analysis · Mathematics 2026-01-30 Tamás Dózsa , Andrea Angino , Zoltán Szabó , József Bokor , Matthias Voigt

The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential rests on the proper treatment of locality…

Computational Physics · Physics 2019-12-05 Leonardo Zepeda-Núñez , Yixiao Chen , Jiefu Zhang , Weile Jia , Linfeng Zhang , Lin Lin

The electron density of a molecule or material has recently received major attention as a target quantity of machine-learning models. A natural choice to construct a model that yields transferable and linear-scaling predictions is to…

Chemical Physics · Physics 2022-06-29 Andrea Grisafi , Alan M. Lewis , Mariana Rossi , Michele Ceriotti

We created a computational workflow to analyze the potential energy surface (PES) of materials using machine-learned interatomic potentials in conjunction with the minima hopping algorithm. We demonstrate this method by producing a…

Materials Science · Physics 2025-02-14 Hossein Tahmasbi , Kushal Ramakrishna , Mani Lokamani , Attila Cangi

Quantum spin liquids can be faithfully represented and efficiently characterized within the framework of Projected Entangled Pair States (PEPS). Guided by extensive exact diagonalization and density matrix renormalization group…

Strongly Correlated Electrons · Physics 2020-07-01 Ji-Yao Chen , Sylvain Capponi , Alexander Wietek , Matthieu Mambrini , Norbert Schuch , Didier Poilblanc

In previous works it was shown that protein 3D-conformations could be encoded into discrete sequences called dominance partition sequences (DPS), that generated a linear partition of molecular conformational space into regions of molecular…

Computational Physics · Physics 2009-12-09 Jacques Gabarro-Arpa

A very accurate, (HF)$_2$ potential energy surface (PES) due to Huang et al. (J. Chem. Phys., 150, 154302 (2019)) is used to calculate the energy levels of the HF dimer by solving the nuclear-motion Schr\"{o}dinger equation using…

The mode specific dissociative chemisorption dynamics of ammonia on the Ru(0001) surface is investigated using a quasi-classical trajectory (QCT) method on a new global potential energy surface (PES) with twelve dimensions. The PES is…

Chemical Physics · Physics 2018-05-03 Xixi Hu , Minghui Yang , Daiqian Xie , Hua Guo