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Advances in deep learning have enabled physics-informed neural networks to solve partial differential equations. Numerical differentiation using the finite-difference (FD) method is efficient in physics-constrained designs, even in…

Machine Learning · Computer Science 2024-12-02 Yiye Zou , Tianyu Li , Lin Lu , Jingyu Wang , Shufan Zou , Laiping Zhang , Xiaogang Deng

Ab initio molecular dynamics (AIMD) simulations using hybrid density functionals and plane waves are of great interest owing to the accuracy of this approach in treating condensed matter systems. On the other hand, such AIMD calculations…

Chemical Physics · Physics 2020-01-08 Sagarmoy Mandal , Nisanth N. Nair

Large-scale applications of energy density functional (EDF) methods depend on fast and reliable algorithms to solve the associated non-linear self-consistency problem. When dealing with large single-particle variational spaces, existing…

Nuclear Theory · Physics 2019-06-24 W. Ryssens , M. Bender , P. -H. Heenen

This paper presents AFD-STA Net, a neural framework integrating adaptive filtering and spatiotemporal dynamics learning for predicting high-dimensional chaotic systems governed by partial differential equations. The architecture combines:…

Machine Learning · Computer Science 2025-05-26 Chunlin Gong , Yin Wang , Jingru Li , Hanleran Zhang

In order to accelerate implementation of hyperelastic materials for finite element analysis, we developed an automatic numerical algorithm that only requires the strain energy function. This saves the effort on analytical derivation and…

Computational Engineering, Finance, and Science · Computer Science 2016-09-20 Yuxiang Wang , Gregory J. Gerling

One of the most popular methods employed in computational electromagnetics is the Finite Difference Time Domain (FDTD) method. We generalise it to a meshless setting using the Radial Basis Function generated Finite Difference (RBF-FD)…

Computational Physics · Physics 2026-02-26 Andrej Kolar-Požun , Gregor Kosec

The fourth-order PDE that models the density variation of smectic A liquid crystals presents unique challenges in its (numerical) analysis beyond more common fourth-order operators, such as the classical biharmonic. While the operator is…

Numerical Analysis · Mathematics 2023-08-24 Patrick E. Farrell , Abdalaziz Hamdan , Scott P. MacLachlan

V2X (Vehicle-to-everything) communication relies on short messages for short-range transmissions over a fading wireless channel, yet requires high reliability and low latency. Hard-decision decoding sacrifices the preservation of diversity…

Information Theory · Computer Science 2024-08-08 Praveen Sai Bere , Mohammed Zafar Ali Khan , Lajos Hanzo

To improve the computational efficiencies of the real-space orbital-free density functional theory, this work develops a new single-grid solver by directly providing the closed-form solution to the inner iteration and using an improved…

Computational Physics · Physics 2023-05-16 Ling-Ze Bu , Wei Wang

The finite-difference time-domain (FDTD) method, which is important in photonic hardware design flow, is widely adopted to solve time-domain Maxwell equations. However, FDTD is known for its prohibitive runtime cost, taking minutes to hours…

Computational Physics · Physics 2024-06-27 Pingchuan Ma , Haoyu Yang , Zhengqi Gao , Duane S. Boning , Jiaqi Gu

The efficient encoding of the fermionic Schr\"odinger equation as a spin system Hamiltonian is a long-term problem. I describe an encoding for the fermionic position space Schr\"odinger equation on a finite-volume periodic lattice with a…

Quantum Physics · Physics 2023-10-13 Kenneth S. McElvain

Fast power system state estimation (SE) solution is of paramount importance for achieving real-time decision making in power grid operations. Semidefinite programming (SDP) reformulation has been shown effective to obtain the global optimum…

Signal Processing · Electrical Eng. & Systems 2019-06-20 Yu Lan , Hao Zhu , Xiaohong Guan

A robust and fast solver for the fractional differential equation (FDEs) involving the Riesz fractional derivative is developed using an adaptive finite element method on non-uniform meshes. It is based on the utilization of hierarchical…

Numerical Analysis · Mathematics 2017-10-11 Xuan Zhao , Xiaozhe Hu , Wei Cai , George Em Karniadakis

The accuracy of atomistic simulations depends on the precision of force fields. Traditional numerical methods often struggle to optimize the empirical force field parameters for reproducing target properties. Recent approaches rely on…

In this paper we develop two conforming finite element methods for a fourth order bi-wave equation arising as a simplified Ginzburg-Landau-type model for d-wave superconductors in absence of applied magnetic field. Unlike the biharmonic…

Numerical Analysis · Mathematics 2009-02-09 Xiaobing Feng , Michael Neilan

Derivative-free optimization (DFO) is vital in solving complex optimization problems where only noisy function evaluations are available through an oracle. Within this domain, DFO via finite difference (FD) approximation has emerged as a…

Machine Learning · Computer Science 2025-02-19 Wang Du-Yi , Liang Guo , Liu Guangwu , Zhang Kun

The design of better exchange-correlation functionals for Density Functional Theory (DFT) is a central challenge of modern electronic structure theory. However, current developments are limited by the mathematical form of the functional,…

Chemical Physics · Physics 2024-08-19 Kyle Bystrom , Boris Kozinsky

A novel hybrid spectral difference/embedded finite volume method is introduced in order to apply a discontinuous high-order method for large scale engineering applications involving discontinuities in the flows with complex geometries. In…

Numerical Analysis · Mathematics 2015-05-20 Jung J. Choi

Over the past few years much progress has been made in Computational Fluid Dynamics (CFD) in its ability to accurately simulate the hydrodynamics associated with a deep-V monohull planing craft. This work has focused on not only predicting…

Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a…

Computational Physics · Physics 2018-08-16 Konduri Aditya , Diego A. Donzis