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DY: Fachverband Dynamik und Statistische Physik

DY 8: Artificial Intelligence in Condensed Matter Physics II (joint session TT/DY)

Montag, 18. März 2024, 15:00–16:00, H 3025

While artificial intelligence leaves an ever growing footprint in our everyday lives, it has as well inspired various new approaches in the physical sciences; for instance, one of the outstanding success stories is the prediction of protein folding with unprecedented accuracy. But what role can AI play in condensed matter physics? This symposium aims to provide an overview and discussion of recent applications of modern machine learning and its prospects for the advancement of research in this field. The increasingly data-intensive experiments with high-dimensional observations call for the development of new tools for analysis matching known strengths of machine learning algorithms. Reinforcement learning agents can be employed to precisely manipulate many-body systems, which, among other use cases, is a pivotal ingredient for quantum technologies. On the computational side, ideas from deep learning and generative modeling inspire new building blocks to boost numerical simulations. One may even ask the question whether a machine can autonomously discover physical concepts such as effective degrees of freedom or equations of motion, and reveal them in an interpretable manner to human researchers.

Prof. Dr. Simon Trebst, Universität Köln
Prof. Dr. Florian Marquardt, Max-Planck-Institut Erlangen
Dr. Markus Schmitt, FZ Jülich

	15:00	DY 8.1	Uncertainty-aware active learning for interatomic potentials generation and its applications for spin dynamics — •Valerio Briganti and Alessandro Lunghi
	15:15	DY 8.2	Transverse barrier and filament formation by electrical triggering of a metal-to-insulator or insulator-to-metal transition — •Lorenzo Fratino, Marcelo Rozenberg, Pavel Salev, Javier Del Valle, and Ivan K. Schuller
	15:30	DY 8.3	The contribution has been withdrawn (duplicate of O 93.4).
	15:45	DY 8.4	Neural quantum states for a two-leg Bose-Hubbard ladder under a magnetic field — •Kadir Çeven, Mehmet Özgür Oktel, and Ahmet Keleş