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The use of deep learning methods for solving PDEs is a field in full expansion. In particular, Physical Informed Neural Networks, that implement a sampling of the physical domain and use a loss function that penalizes the violation of the…

Machine Learning · Computer Science 2021-12-08 Valentin Mercier , Serge Gratton , Pierre Boudier

The finite-difference time-domain (FDTD) algorithm is a popular numerical method for solving electromagnetic problems. FDTD simulations can suffer from instability due to the explicit nature of the method. Stability enforcement can be…

Computational Engineering, Finance, and Science · Computer Science 2018-12-26 Fadime Bekmambetova , Xinyue Zhang , Piero Triverio

Large language models (LLMs) have shown remarkable in-context learning (ICL) capabilities, yet their potential for sequential decision-making remains underexplored. In this paper, we study the ICL capabilities of LLMs in sequential…

Machine Learning · Computer Science 2026-05-12 Minmin Zhang , Sina Aghaei , Soroush Saghafian

Rigorous computer simulations of propagating electromagnetic fields have become an important tool for optical metrology and design of nanostructured optical components. A vectorial finite element method (FEM) is a good choice for an…

Optics · Physics 2009-05-28 L. Zschiedrich , S. Burger , A. Schädle , F. Schmidt

We discuss parallel (additive) and sequential (multiplicative) variants of overlapping Schwarz methods for the Helmholtz equation in $\mathbb{R}^d$, with large real wavenumber and smooth variable wave speed. The radiation condition is…

Numerical Analysis · Mathematics 2025-10-21 Jeffrey Galkowski , Shihua Gong , Ivan G. Graham , David Lafontaine , Euan A. Spence

The electron states in axially symmetric quantum wires are computed by means of the effective-mass Schroedinger equation, which is written in cylindrical coordinates phi, rho, and z. We show that a direct discretization of the Schroedinger…

Mesoscale and Nanoscale Physics · Physics 2015-12-21 V. V. Arsoski , M. Z. Tadic , N. A. Cukaric , F. M. Peeters

We propose a novel multilinear dynamical system (MLDS) in a transform domain, named $\mathcal{L}$-MLDS, to model tensor time series. With transformations applied to a tensor data, the latent multidimensional correlations among the frontal…

Machine Learning · Computer Science 2018-11-20 Weijun Lu , Xiao-Yang Liu , Qingwei Wu , Yue Sun , Anwar Walid

Outstanding advances in solid-state laser technology, employing the optical parametric chirped-pulse-amplification (OPCPA) technique, have led physicists to focus laser pulses to highly-relativistic intensities which led to novel schemes…

Plasma Physics · Physics 2026-01-28 Szilárd Majorosi , Nasr Hafz , Zsolt Lécz

This paper addresses the problem of planning under uncertainty in large Markov Decision Processes (MDPs). Factored MDPs represent a complex state space using state variables and the transition model using a dynamic Bayesian network. This…

Artificial Intelligence · Computer Science 2011-06-10 C. Guestrin , D. Koller , R. Parr , S. Venkataraman

We propose discrete-time polarization mode dispersion (PMD) models that are compatible with the emerging coherent receiver techniques, and statistical sampling schemes for the model parameters. These models use multiple-input…

Optics · Physics 2012-12-06 A. Gokcen Mahmutoglu , Alper T. Erdogan , Alper Demir

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible…

The real-space density-functional perturbation theory (DFPT) for the computations of the response properties with respect to the atomic displacement and homogeneous electric field perturbation has been recently developed and implemented…

Computational Physics · Physics 2020-10-28 Honghui Shang , Wanzhen Liang , Yunquan Zhang , Jinlong Yang

In this paper we describe a computational model for the simulation of fluid-structure interaction problems based on a fictitious domain approach. We summarize the results presented over the last years when our research evolved from the…

Numerical Analysis · Mathematics 2021-04-29 Daniele Boffi , Lucia Gastaldi

We present a fast and memory-efficient algorithm for transient, space-time-domain, and elastodynamic boundary-integral analysis. Associated data-sparse approximations and operations are named fast domain partitioning hierarchical matrices…

Computational Physics · Physics 2026-03-20 Dye SK Sato , Ryosuke Ando

In this work we present a variant of the fast multipole method (FMM) for efficiently evaluating standard layer potentials on geometries with complex coordinates in two and three dimensions. The complex scaled boundary integral method for…

Numerical Analysis · Mathematics 2025-10-20 Tristan Goodwill , Leslie Greengard , Jeremy Hoskins , Manas Rachh , Yuguan Wang

Ultra-light scalar fields and their non-interacting class, the so-called fuzzy dark matter (FDM), are candidates for dark matter, introduced to solve the small-scale problems of the standard cold dark matter. In this paper, we address…

Cosmology and Nongalactic Astrophysics · Physics 2024-01-24 Hamed Manouchehri Kousha , Sina Hooshangi , Aliakbar Abolhasani

We introduce an algorithm based on Generalized Dual Method (GDM) to efficiently study the dynamics of a particle in quasiperiodic environments without the need to use periodic approximations or to save the information of the vertices that…

Chaotic Dynamics · Physics 2022-04-28 Alan Rodrigo Mendoza Sosa , Atahualpa S. Kraemer

A novel explicit method to model Lorentz linear dispersive media with finite difference method are presented. The method shows an explicit method without any modification to the Leap-Frogging scheme. The polarizations of the Lorentz media…

Numerical Analysis · Mathematics 2020-07-22 Hiroshi Abe

We present a proof of concept for solving a 1+1D complex-valued, delay partial differential equation (PDE) that emerges in the study of waveguide quantum electrodynamics (QED) by adapting the finite-difference time-domain (FDTD) method. The…

Mathematical Software · Computer Science 2018-11-19 Yao-Lung L. Fang

Thermal Energy Storage (TES) using Phase Change Materials (PCMs) represents a critical technology for sustainable energy management and grid stability. This study presents a novel Physics-Driven Deep Learning (PDDL) framework for modeling…

Mathematical Physics · Physics 2025-12-02 Meraj Hassanzadeh , Ehsan Ghaderi , Fatemeh Fatahi , Mohamad Ali Bijarchi