Poster
in
Workshop: Machine Learning and the Physical Sciences

Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation

Karan Shah ⋅ Patrick Stiller ⋅ Nico Hoffmann ⋅ Attila Cangi

[ Poster]

Abstract

We demonstrate the utility of physics-informed neural networks (PINNs) as solvers for the non-relativistic, time-dependent Schrödinger equation. We study the performance and generalisability of PINN solvers on the time evolution of a quantum harmonic oscillator across varying system parameters, domains, and energy states.

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