In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes ...

DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when ...

We study the classical linear partial differential equations: Poisson's equation and the heat equation. We learn about representation formulas for solutions, maximum principles, and energy estimates.

The course gives an introduction to analytical techniques for partial differential equations, in particular to separation of variables. In addition the course treats qualititative properties of ...

Abstract: Recently, the Physics-encoded Recurrent Convolutional Neural Network (PeRCNN) has garnered significant attention for solving partial differential equations (PDEs) using deep learning methods ...

Université de Paris, Laboratoire Jacques-Louis, Lions (LJLL), Paris F-75005, France Sorbonne Université, CNRS, LJLL, Paris F-75005, France ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster. A new ...

A python script that solves the one dimensional time-independent Schrodinger equation for bound states. The script uses a Numerov method to solve the differential equation and displays the desired ...

The method is an extension of Weinert’s pseudo-charge method [Weinert M, J Math Phys, 1981, 22:2433–2439] for solving the Poisson equation for the same class of charge density distributions. The ...