AI solves one of the biggest problems in physics considered impossible: “First principles calculation”

A problem that has long been considered impossible to solve and that now, thanks to a breakthrough, can be calculated quickly ...
Nature

Physics-Informed Neural Networks and Differential Equations

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 ...

AI tensor network-based computational framework cracks a 100-year-old physics challenge

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational ...
JSTOR Daily

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 ...
Nature

(1) Determinants and Matrices (2) Theory of Equations (3) Integration (4) Vector Methods: Applied to Differential Geometry, Mechanics and Potential Theory (5) Integration of ...

TODD, J. (1) Determinants and Matrices (2) Theory of Equations (3) Integration (4) Vector Methods: Applied to Differential Geometry, Mechanics and Potential Theory (5) Integration of Ordinary ...