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The Density Matrix Renormalization Group (DMRG) method has become a prominent tool for simulating strongly correlated electronic systems characterized by dominant static correlation effects. However, capturing the full scope of electronic…

Chemical Physics · Physics 2024-11-13 Nicholas Bauman , Libor Veis , Karol Kowalski , Jiri Brabec

The accurate description of large molecular systems in complex environments remains an ongoing challenge for the field of computational chemistry. This problem is even more pronounced for photo-induced processes, as multiple excited…

In this work, we determine the vapor-liquid (VL) coexistence and interfacial properties of the hydroquinone (HQ) pure system from $NVT$ molecular dynamics simulations. We employ the direct coexistence technique to put in contact both phases…

Incremental Potential Contact (IPC) is a widely used, robust, and accurate method for simulating complex frictional contact behaviors. However, achieving high efficiency remains a major challenge, particularly as material stiffness…

Graphics · Computer Science 2025-05-05 Kemeng Huang , Xinyu Lu , Huancheng Lin , Taku Komura , Minchen Li

Accurate modelling of electrostatic interactions and charge transfer is fundamental to computational chemistry, yet most machine learning interatomic potentials (MLIPs) rely on local atomic descriptors that cannot capture long-range…

A fluid-structure interaction model in a port-Hamiltonian representation is derived for a classical guitar. We combine the laws of continuum mechanics for solids and fluids within a unified port-Hamiltonian (pH) modeling approach by…

We present the formulation, algorithm and numerical tests of the magnetohydrodynamic-particle-in-cell (MHD-PIC) method with particles treated under the guiding center approximation, which we term the MHD-gPIC method, and it is implemented…

High Energy Astrophysical Phenomena · Physics 2025-10-20 Zitao Hu , Xue-Ning Bai , Xiaochen Sun

Injection from metallic electrodes serves as a main channel of charge generation in organic semiconducting devices and the quantum effect is normally regarded to be essential. We develop a dynamic approach based upon the surface hopping…

Applied Physics · Physics 2021-01-20 Jiaqing Huang , Yijie Mo , Yao Yao

The vibrational motion of molecules in dissipative environments, such as solvation and protein molecules, is composed of contributions from both intermolecular and intramolecular modes. The existence of these collective modes introduces…

Soft Condensed Matter · Physics 2020-04-16 Seiji Ueno , Yoshitaka Tanimura

We introduce an entirely new class of high-order methods for computational fluid dynamics (CFD) based on the Gaussian Process (GP) family of stochastic functions. Our approach is to use kernel-based GP prediction methods to…

Computational Physics · Physics 2017-05-16 Adam Reyes , Dongwook Lee , Carlo Graziani , Petros Tzeferacos

Particle accelerator modeling is an important field of research and development, essential to investigating, designing and operating some of the most complex scientific devices ever built. Kinetic simulations of relativistic, charged…

Accelerator Physics · Physics 2024-05-02 Ryan T. Sandberg , Remi Lehe , Chad E. Mitchell , Marco Garten , Andrew Myers , Ji Qiang , Jean-Luc Vay , Axel Huebl

The dynamic load-balancing framework in Charm++/AMPI, developed at the University of Illinois, is based on using processor virtualization to allow thread migration across processors. This framework has been successfully applied to many…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-17 Alvaro Luiz Fazenda , Celso L. Mendes , Laxmikant V. Kale , Jairo Panetta , Eduardo Rocha Rodrigues

Port-Hamiltonian (pH) systems are a very important modeling tool in almost all areas of systems and control, in particular in network based model of multi-physics multi-scale systems. They lead to remarkably robust models that can be easily…

Optimization and Control · Mathematics 2019-03-19 Karim Cherifi , Volker Mehrmann , Kamel Hariche

Graphene functionalized with catalytic transition metals offers high-performance gas sensing by coupling graphene's exceptional electronic transport properties with the metal's catalytic activity, yet the atomistic relationships connecting…

Materials Science · Physics 2025-05-29 Akram Ibrahim , Ahmed M. Hafez , Mahmooda Sultana , Can Ataca

Efficient simulation of complex plasma dynamics is crucial for advancing fusion energy research. Particle-in-Cell (PIC) Monte Carlo (MC) simulations provide insights into plasma behavior, including turbulence and confinement, which are…

Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on…

Quantitative Methods · Quantitative Biology 2017-08-15 Alexis Delabrière , Ulli Hohenester , Benoit Colsch , Christophe Junot , François Fenaille , Etienne Thévenot

I describe a modification to the original Fast Multipole Method (FMM) of Greengard & Rokhlin that approximates the gravitation field of an FMM cell as a small uniform grid (a "gridlet") of effective masses. The effective masses on a gridlet…

Computational Physics · Physics 2019-07-31 Nickolay Y. Gnedin

The Athena MHD code has been extended to integrates the motion of particles coupled with the gas via aerodynamic drag, in order to study the dynamics of gas and solids in protoplanetary disks and the formation of planetesimals. Our…

Earth and Planetary Astrophysics · Physics 2015-05-19 Xue-Ning Bai , James M. Stone

We develop an unconditionally stable numerical method for solving the coupling between two fluids (frictional forces/heatings, ionization, and recombination), and investigate the dynamical condensation process of thermally unstable gas that…

Astrophysics · Physics 2010-12-20 Tsuyoshi Inoue , Shu-ichiro Inutsuka

In recent years, the Hamiltonian Monte Carlo (HMC) algorithm has been found to work more efficiently compared to other popular Markov Chain Monte Carlo (MCMC) methods (such as random walk Metropolis-Hastings) in generating samples from a…

Computation · Statistics 2014-02-18 Andrew L. Beam , Sujit K. Ghosh , Jon Doyle