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Developing fast surrogates for Partial Differential Equations (PDEs) will accelerate design and optimization in almost all scientific and engineering applications. Neural networks have been receiving ever-increasing attention and…

Machine Learning · Computer Science 2024-11-21 AmirPouya Hemmasian , Amir Barati Farimani

Numerical hydrodynamics simulations of gases dominated by ideal, nondegenerate matter pressure and thermal radiation pressure in equilibrium entail finding the temperature as part of the evolution. Since the temperature is not typically a…

High Energy Astrophysical Phenomena · Physics 2025-11-14 Thomas W. Baumgarte , Stuart L. Shapiro

We study the effect of advection and small diffusion on passive tracers. The advecting velocity field is assumed to have mean zero and to possess time-periodic stream lines. Using a canonical transform to action-angle variables followed by…

Fluid Dynamics · Physics 2009-11-13 Tobias Schaefer , Andrew C. Poje , Jesenko Vukadinovic

Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor lambda. Currently the most important application of these methods is to temporal…

Artificial Intelligence · Computer Science 2008-02-03 P. Cichosz

In this paper we propose a novel way to integrate time-evolving partial differential equations that contain nonlinear advection and stiff linear operators, combining exponential integration techniques and semi-Lagrangian methods. The…

Computational Physics · Physics 2019-11-05 Pedro da Silva Peixoto , Martin Schreiber

In this study, two initial boundary value problems for one dimensional advection-dispersion equation are solved by differential quadrature method based on sine cardinal functions. Pure advection problem modeling transport of conservative…

Numerical Analysis · Mathematics 2016-02-09 Alper Korkmaz

In grid-based codes that provide the combined solution of the Einstein equations and of relativistic hydrodynamics, the history of the fluid is not simple to track, especially when compared with particle-based codes. The use of tracers,…

General Relativity and Quantum Cosmology · Physics 2018-03-28 Luke Bovard , Luciano Rezzolla

We analyze the diffusion of charged and neutral tracers suspended in an electrolyte embedded in a channel of varying cross-section. Making use of systematic approximations, the diffusion equation governing the motion of tracers is mapped…

Soft Condensed Matter · Physics 2016-02-17 Paolo Malgaretti , Ignacio Pagonabarraga , Miguel J Rubi

Tropical differential equations are introduced and an algorithm is designed which tests solvability of a system of tropical linear differential equations within the complexity polynomial in the size of the system and in its coefficients.…

Symbolic Computation · Computer Science 2018-11-08 Dima Grigoriev

A novel numerical approach to solving the shallow-water equations on the sphere using high-order numerical discretizations in both space and time is proposed. A space-time tensor formalism is used to express the equations of motion…

Numerical Analysis · Mathematics 2021-11-12 Stéphane Gaudreault , Martin Charron , Valentin Dallerit , Mayya Tokman

In this paper, a stabilized second order in time accurate linear exponential time differencing (ETD) scheme for the no-slope-selection thin film growth model is presented. An artificial stabilizing term $A\tau^2\frac{\partial\Delta^2…

Numerical Analysis · Mathematics 2019-07-05 Wenbin Chen , Weijia Li , Zhiwen Luo , Cheng Wang , Xiaoming Wang

Nowadays, our mobility systems are evolving into the era of intelligent vehicles that aim to improve road safety. Due to their vulnerability, pedestrians are the users who will benefit the most from these developments. However, predicting…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Lina Achaji , Thierno Barry , Thibault Fouqueray , Julien Moreau , Francois Aioun , Francois Charpillet

Differential equations are pivotal in modeling and understanding the dynamics of various systems, offering insights into their future states through parameter estimation fitted to time series data. In fields such as economy, politics, and…

Machine Learning · Statistics 2024-04-24 Hyeontae Jo , Sung Woong Cho , Hyung Ju Hwang

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and…

Numerical Analysis · Mathematics 2018-04-03 Lukas Einkemmer , Mayya Tokman , John Loffeld

This paper introduces a boundary integral equation for time-harmonic electromagnetic scattering by composite dielectric objects. The formulation extends the classical M\"uller equation to composite structures through the global multi-trace…

Numerical Analysis · Mathematics 2026-01-21 Van Chien Le , Kristof Cools

This paper considers one-dimensional heat transfer in a media with temperature-dependent thermal conductivity. To model the transient behavior of the system, we solve numerically the one-dimensional unsteady heat conduction equation with…

Numerical Analysis · Mathematics 2018-11-16 Stefan M Filipov , István Faragó

Off-policy learning allows us to learn about possible policies of behavior from experience generated by a different behavior policy. Temporal difference (TD) learning algorithms can become unstable when combined with function approximation…

Machine Learning · Computer Science 2021-06-23 Ray Jiang , Tom Zahavy , Zhongwen Xu , Adam White , Matteo Hessel , Charles Blundell , Hado van Hasselt

Existing studies on salient object detection (SOD) focus on extracting distinct objects with edge information and aggregating multi-level features to improve SOD performance. To achieve satisfactory performance, the methods employ refined…

Computer Vision and Pattern Recognition · Computer Science 2022-06-28 Min Seok Lee , Wooseok Shin , Sung Won Han

This paper presents a detailed evaluation of the envelope-tracking adaptive integral method (ET-AIM), an FFT-accelerated algorithm for analyzing electromagnetic scattering. ET-AIM is used to solve progressively more complex benchmark…

Computational Physics · Physics 2014-09-01 Guneet Kaur , Ali E. Yilmaz

We present a parametric family of semi-implicit second order accurate numerical methods for non-conservative and conservative advection equation for which the numerical solutions can be obtained in a fixed number of forward and backward…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Svetlana Krišková , Michaela Rohová , Michal Žeravý
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