11–16 Sept 2022
Görlitz
Europe/Berlin timezone

Physics-Informed Neural Networks for Quantum Dynamics of Electrons

15 Sept 2022, 11:00
30m
Görlitz

Görlitz

Peterstraße 15, 02826 Görlitz

Speaker

Karan Shah (CASUS, Helmholtz-Zentrum Dresden-Rossendorf, Germany)

Description

Time-dependent density functional theory (TDDFT) is an important method for simulating dynamical processes in quantum many-body systems. We explore the feasibility of physics-informed neural networks as a surrogate for TDDFT. We examine the computational efficiency and convergence behaviour of these solvers to state-of-the-art numerical techniques on models and small molecular systems. The method developed here has the potential to accelerate the TDDFT workflow, 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, Helmholtz-Zentrum Dresden-Rossendorf, Germany)

Presentation materials

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