Description
Session Chair: Andrew Baczewski
X-ray induced structural transitions in solids are in focus of this talk. Depending on the dose absorbed, an irradiation with a femtosecond X-ray pulse can trigger an ultrafast electronic or structural transition in solid materials. In magnetic materials, an X-ray triggered ultrafast demagnetization can occur. In this talk, selected study cases for these transitions are presented. Dedicated...
The long term and sustainable success of the X-ray community essentially depends on its ability to meet growing challenges in handling and analysing data of increasing volume and complexity. Machine Learning (ML) provide a smart solution enabling a dramatic increase in the output of X ray scattering facilities regarding acceleration of data analysis, optimization of beam time usage and,...
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...
Artificial intelligence (AI) has great potential for accelerating electronic structure calculations to hitherto unattainable scales [1]. I will present our recent efforts on accomplishing speeding up Kohn-Sham density functional theory calculations at finite temperatures with deep neural networks in terms of our Materials Learning Algorithms framework [2,3] by illustrating results for metals...
