Speaker
Karan Shah
(CASUS HZDR)
Description
We demonstrate the utility of Physics-Informed Neural Network based solvers for the solution of the Time-Dependent Schrödinger Equation. We study the performance and generalisability of PINN solvers on a simple quantum system. The method developed here can be potentially extended as a surrogate model for Time-Dependent Density Functional Theory, enabling the simulation of large-scale calculations of electron dynamics in matter exposed to strong electromagnetic fields, high temperatures, and pressures.
Primary author
Karan Shah
(CASUS HZDR)
Co-author
Dr
Attila Cangi
(Helmholtz-Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding)
