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Binding free energies are a key element in understanding and predicting the strength of protein--drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs including transition metal…

The pair-coupled-cluster doubles (pCCD) method has emerged as a viable approach for quantum-chemical studies of strongly correlated systems. Despite its lower formal scaling (O(N$^4$)) compared to other versions of coupled cluster (CC)…

Chemical Physics · Physics 2026-04-17 Rahul Chakraborty , Paweł Tecmer

The evaluation of the electrostatic potential is fundamental to the study of condensed phase systems. We discuss the calculation of the relevant lattice summations by Ewald-type techniques. A model charge density is introduced, that cancels…

Materials Science · Physics 2026-04-14 Chiara Ribaldone , Jacques Kontak Desmarais

Quantum Extreme Learning Machine (QELM) is an emerging hybrid quantum machine learning framework that leverages quantum system dynamics to enhance classical models. However, QELM can suffer from the exponential concentration problem, where…

Quantum Physics · Physics 2026-04-24 Payal D. Solanki , Anh Pham

Electrostatic forces play many important roles in molecular biology, but are hard to model due to the complicated interactions between biomolecules and the surrounding solvent, a fluid composed of water and dissolved ions. Continuum model…

Numerical Analysis · Mathematics 2015-12-29 Jaydeep P. Bardhan , Matthew G. Knepley

In computational molecular science, calculation of electrostatic interactions involving charged atoms - the strongest interactions in condensed phases, is a major bottleneck. We propose a quantum-classical algorithm for fast, yet, accurate…

Quantum Physics · Physics 2026-02-18 Mansur Ziiatdinov , Igor Novikov , Farid Ablayev , Valeri Barsegov

The structure and function of biological molecules are strongly influenced by the water and dissolved ions that surround them. This aqueous solution (solvent) exerts significant electrostatic forces in response to the biomolecule's…

Numerical Analysis · Mathematics 2015-12-29 Matthew G. Knepley , Jaydeep P. Bardhan

We present a polarizable embedding quantum mechanics/molecular mechanics (QM/MM) framework for ground- and excited-state Complete Active Space Self-Consistent Field (CASSCF) calculations on molecules within complex environments, such as…

Chemical Physics · Physics 2024-11-20 Tommaso Nottoli , Mattia Bondanza , Filippo Lipparini , Benedetta Mennucci

We present a new approach to efficiently simulate electrolytes confined between infinite charged walls using a 3d Ewald summation method. The optimal performance is achieved by separating the electrostatic potential produced by the charged…

Soft Condensed Matter · Physics 2018-01-18 Alexandre P. dos Santos , Matheus Girotto , Yan Levin

We present a new method, in the following called MMM2D, to accurately calculate the electrostatic energy and forces on charges being distributed in a two dimensional periodic array of finite thickness. It is not based on an Ewald summation…

Soft Condensed Matter · Physics 2009-11-07 Axel Arnold , Christian Holm

Standard Ewald sums, which calculate e.g. the electrostatic energy or the force in periodically closed systems of charged particles, can be efficiently speeded up by the use of the Fast Fourier Transformation (FFT). In this article we…

Soft Condensed Matter · Physics 2009-10-31 Markus Deserno , Christian Holm

Rechargeable battery electrodes have highly complex microstructures, consisting of nonuniform electrode particles, tortuous electrolyte channels, and irregular particle-electrolyte interfaces. Moreover, the electrochemical processes involve…

Materials Science · Physics 2026-03-26 Hui-Chia Yu , Bernardo Orvananos , Scott Cronin , Martin Bazant , Scott Barnett , K. Thornton

Quasi two-dimensional Coulomb systems have drawn widespread interest. The reduced symmetry of these systems leads to complex collective behaviors, yet simultaneously poses significant challenges for particle-based simulations. In this…

Numerical Analysis · Mathematics 2025-07-15 Zecheng Gan , Xuanzhao Gao , Jiuyang Liang , Zhenli Xu

A novel embedded atom method (EAM) potential for the Xi-phases of Al-Pd-Mn has been determined with the force-matching method. Different combinations of analytic functions were tested for the pair and transfer part. The best results are…

Materials Science · Physics 2012-02-09 Daniel Schopf , Peter Brommer , Benjamin Frigan , Hans-Rainer Trebin

Computer simulations of model systems are widely used to explore striking phenomena in promising applications spanning from physics, chemistry, biology, to materials science and engineering. The long range electrostatic interactions between…

Computational Physics · Physics 2020-07-21 Sheng-Chun Yang , Bin Li , You-Liang Zhu , Aatto Laaksonen , Yong-Lei Wang

We present a variant of the recently developed quantum corrected model (QCM) for plasmonic nanoparticles [Nature Commun. 3, 825 (2012)] using non-local boundary conditions. The QCM accounts for electron tunneling in narrow gap regions of…

Mesoscale and Nanoscale Physics · Physics 2015-06-11 Ulrich Hohenester

Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely used in enzyme simulation. Over ten convergence studies of QM/MM methods have revealed over the past several years that key energetic and structural properties…

Chemical Physics · Physics 2017-01-11 Maria Karelina , Heather J. Kulik

The tight binding model is a minimal electronic structure model for molecular modelling and simulation. We show that the total energy in this model can be decomposed into site energies, that is, into contributions from each atomic site…

Numerical Analysis · Mathematics 2015-06-19 Huajie Chen , Christoph Ortner

Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling and drug discovery, from…

We address the estimation problem for general finite mixture models, with a particular focus on the elliptical mixture models (EMMs). Compared to the widely adopted Kullback-Leibler divergence, we show that the Wasserstein distance provides…

Machine Learning · Computer Science 2020-10-09 Shengxi Li , Zeyang Yu , Min Xiang , Danilo Mandic