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We propose a unique scheme to construct fully optimized atomic basis sets for density-functional calculations. The shapes of the radial functions are optimized by minimizing the {\it spillage} of the wave functions between the atomic…

Materials Science · Physics 2015-05-19 Mohan Chen , G-C Guo , Lixin He

Strong multiple scattering of the probe in scanning transmission electron microscopy (STEM) means image simulations are usually required for quantitative interpretation and analysis of elemental maps produced by electron energy-loss…

Materials Science · Physics 2019-12-25 Hamish G. Brown , Jim Ciston , Colin Ophus

The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics. However, the parameterization of the effective Hamiltonian is…

A coarse-grained computational procedure based on the Finite Element Method is proposed to calculate the normal modes and mechanical response of proteins and their supramolecular assemblies. Motivated by the elastic network model, proteins…

Biomolecules · Quantitative Biology 2007-05-23 Mark Bathe

The simulation of charge transport in ultra-scaled electronic devices requires the knowledge of the atomic configuration and the associated potential. Such "atomistic" device simulation is most commonly handled using a tight-binding…

Mesoscale and Nanoscale Physics · Physics 2019-10-02 Maarten L. Van de Put , Massimo V. Fischetti , William G. Vandenberghe

We propose a framework for optimization of the chemical composition of multinary compounds with the aid of machine learning. The scheme is based on first-principles calculation using the Korringa-Kohn-Rostoker method and the coherent…

Materials Science · Physics 2019-06-05 Taro Fukazawa , Yosuke Harashima , Zhufeng Hou , Takashi Miyake

Achieving ultimate bounds in estimation processes is the main objective of quantum metrology. In this context, several problems require measurement of multiple parameters by employing only a limited amount of resources. To this end,…

Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how…

Materials Science · Physics 2026-04-13 Jonas Grandel , Philipp Benner , Janine George

Modern applications of atomic physics, including the determination of frequency standards, and the analysis of astrophysical spectra, require prediction of atomic properties with exquisite accuracy. For complex atomic systems,…

Atomic Physics · Physics 2024-08-02 Pavlo Bilous , Charles Cheung , Marianna Safronova

We employ a technique that combines the configuration interaction method with the singles-doubles coupled-cluster method to perform calculation of the energy levels, transition amplitudes, lifetimes, g-factors, and magnetic dipole and…

Atomic Physics · Physics 2020-05-08 V. A. Dzuba , V. V. Flambaum , B. M. Roberts

We consider the problem of computing a binary linear transformation using unreliable components when all circuit components are unreliable. Two noise models of unreliable components are considered: probabilistic errors and permanent errors.…

Information Theory · Computer Science 2017-05-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

This manuscript explores a variational quantum formulation for nonlinear elasticity problems arising from hyperelastic material models, targeting near term noisy intermediate scale quantum (NISQ) devices. The approach leverages the…

Quantum Physics · Physics 2026-05-29 Uditnarayan Kouskiya , Caglar Oskay

Accurately predicting protein structures from amino acid sequences remains a fundamental challenge in computational biology, with profound implications for understanding biological functions and enabling structure-based drug discovery.…

We present a new formulation of the correlated electron-ion dynamics (CEID) scheme, which systematically improves Ehrenfest dynamics by including quantum fluctuations around the mean-field atomic trajectories. We show that the method can…

Materials Science · Physics 2007-12-13 L. Stella , M. Meister , A. J. Fisher , A. P. Horsfield

Alchemical binding free energy (BFE) calculations offer an efficient and thermodynamically rigorous approach to in silico binding affinity predictions. As a result of decades of methodological improvements and recent advances in computer…

Statistical Mechanics · Physics 2021-07-13 Pengfei Li , Zhijie Li , Yu Wang , Huaixia Dou , Brian K. Radak , Woody Sherman , Huafeng Xu

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has use cases in chemistry, biology, and medicine. In the past decade, the advent of machine learning…

Chemical Physics · Physics 2022-08-23 Sajjad Heydari , Stefano Raniolo , Lorenzo Livi , Vittorio Limongelli

Quasi-forbidden electronic transitions in atoms and quasi-degenerate vibronic transitions in molecules serve as powerful probes of hypothetical temporal variations of fundamental constants. Computation of the sensitivity of a transition to…

Chemical Physics · Physics 2025-11-17 Carsten Zülch , Konstantin Gaul , Robert Berger

h-BCN is an intriguing material system where the bandgap varies considerably depending on the atomic configuration, even at a fixed composition. Exploring stable atomic configurations in this system is crucial for discussing the energetic…

Molecule-optimized basis sets, based on approximate natural orbitals, are developed for accelerating the convergence of quantum calculations with strongly correlated (multi-referenced) electrons. We use a low-cost approximate solution of…

Chemical Physics · Physics 2014-02-12 Gergely Gidofalvi , David A. Mazziotti

In previous papers we showed that a division of the f-shell into two subsystems gives a better understanding of cohesive properties as well the general behavior of lanthanide systems. In this paper we present numerical computations using…

Strongly Correlated Electrons · Physics 2007-05-23 U. Lundin , I. Sandalov , O. Eriksson