Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...
Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational ...
Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based on machine learning ...
Physics-informed neural networks (PINNs) represent a burgeoning paradigm in computational science, whereby deep learning frameworks are augmented with explicit physical laws to solve both forward and ...
Marginal Stability and Stabilization in the Numerical Integration of Ordinary Differential Equations
This is a preview. Log in through your library . Abstract Strongly stable and consistent multistep methods with maximum order are subject to marginal (or weak) stability. In this paper we introduce ...
This is the first part of a two course graduate sequence in analytical methods to solve ordinary and partial differential equations of mathematical physics. Review of Advanced ODE’s including power ...
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