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OpenFMO framework, an open-source software (OSS) platform for Fragment Molecular Orbital (FMO) method, is extended to multi-physics simulations (MPS). After reviewing the several FMO implementations on distributed computer environments, the…

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Numerical physics has gained a lot of importance in the last decade, its efficiency being motivated and sustained by the growth of computational power. This paper presents a concept that is to be developed in the next few years: OpenPh.…

Digital Libraries · Computer Science 2011-06-28 George Milescu , Gabriel Noaje , Florin Pop

Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring significant advantages in terms of power efficiency, parallelism, and computational speed compared with conventional deep neural networks (DNNs),…

Artificial Intelligence · Computer Science 2022-09-29 Yingjie Li , Ruiyang Chen , Weilu Gao , Cunxi Yu

The problem of orbital stabilization of underactuated mechanical systems with one passive degree-of-freedom (DOF) is revisited. Virtual holonomic constraints are enforced using a continuous controller; this results in a dense set of closed…

Systems and Control · Electrical Eng. & Systems 2020-12-21 Nilay Kant , Ranjan Mukherjee

Density functional theory (DFT) is a cornerstone of computational chemistry and materials science, but its computational cost limits its use in large-scale and high-throughput applications. While machine learning has accelerated energy…

Chemical Physics · Physics 2026-03-18 Yingdi Jin , Xinming Qin , Ruichen Liu , Jie Liu , Zhenyu Li , Jinlong Yang

Deriving LoD2 models from orthophoto and digital surface models (DSM) reconstructed from satellite images is a challenging task. Existing solutions are mostly system approaches that require complicated step-wise processes, including not…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Shengxi Gui , Rongjun Qin , Yang Tang

This study presents a set of algorithms that deal with trajectory planning of rational single-loop mechanisms with one degree of freedom (DoF). Benefiting from a dual quaternion representation of a rational motion, a formula for direct…

Robotics · Computer Science 2025-06-03 Daniel Huczala , Andreas Mair , Tomas Postulka

Studying 2 degree-of-freedom (DOF) Hamiltonian dynamical systems often involves the computation of stable & unstable manifolds of periodic orbits, due to the homoclinic & heteroclinic connections they can generate. Such study is generally…

Dynamical Systems · Mathematics 2025-09-05 Bhanu Kumar

The analytic energy gradients in the atomic orbital representation have recently been published (J. Chem. Phys. 146, 014102, 2017) within the framework of the natural orbital functional theory (NOFT). We provide here an alternative…

Chemical Physics · Physics 2018-02-19 Ion Mitxelena , Mario Piris

Orbital-free density functional theory (OF-DFT) runs at low computational cost that scales linearly with the number of simulated atoms, making it suitable for large-scale material simulations. It is generally considered that OF-DFT strictly…

Materials Science · Physics 2022-04-05 Qiang Xu , Cheng Ma , Wenhui Mi , Yanchao Wang , Yanming Ma

We introduce an energy functional for ground-state electronic structure calculations. Its variables are the natural spin-orbitals of singlet many-body wave functions and their joint occupation probabilities deriving from controlled…

Chemical Physics · Physics 2016-12-04 Ralph Gebauer , Morrel H. Cohen , Roberto Car

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and…

Polarons are widespread in functional materials and are key to device performance in several technological applications. However, their effective impact on material behavior remains elusive, as condensed matter studies struggle to capture…

Neural Operators (NOs) are a leading method for surrogate modeling of partial differential equations. Unlike traditional neural networks, which approximate individual functions, NOs learn the mappings between function spaces. While NOs have…

Astrophysics of Galaxies · Physics 2025-08-01 Keith Poletti , Stella S. R. Offner , Rachel A. Ward

Orbital-free density functional theory (OF-DFT) provides an alternative approach for calculating the molecular electronic energy, relying solely on the electron density. In OF-DFT, both the ground-state density is optimized variationally to…

Chemical Physics · Physics 2023-11-23 Alexandre de Camargo , Ricky T. Q. Chen , Rodrigo A. Vargas-Hernández

Diffractive optical neural networks (DONNs) have been emerging as a high-throughput and energy-efficient hardware platform to perform all-optical machine learning (ML) in machine vision systems. However, the current demonstrated…

Machine Learning · Computer Science 2023-02-23 Ruiyang Chen , Yingheng Tang , Jianzhu Ma , Weilu Gao

We introduce a novel energy functional for ground-state electronic-structure calculations. Its fundamental variables are the natural spin-orbitals of the implied singlet many-body wave function and their joint occupation probabilities. The…

Chemical Physics · Physics 2015-06-23 Ralph Gebauer , Morrel H. Cohen , Roberto Car

Nonlinear optical properties (NLOPs) play a major role in photonics, electro-optics and optoelectronics, and other fields of modern optics. The design of new NLO molecules and materials has benefited from the development of computational…

Chemical Physics · Physics 2019-09-04 Sebastian P. Sitkiewicz , Mauricio Rodriguez-Mayorga , Josep M. Luis , Eduard Matito

The nuclear-electronic orbital (NEO) method is a well-established approach for treating nuclei quantum mechanically in molecular systems beyond the usual Born-Oppenheimer approximation. In this work, we present a strategy to implement the…

Computational Physics · Physics 2022-06-29 Jianhang Xu , Ruiyi Zhou , Zhen Tao , Christopher Malbon , Volker Blum , Sharon Hammes-Schiffer , Yosuke Kanai