Speaker: Annika Bande, Leibniz Hannover University, Helmholtz-Zentrum Berlin

The theory of electron dynamics solves the time-dependent Schrödinger equation and allows to predict the electronic motion in molecular structures [1,2]. It enables understanding of the fundamentals of chemical reactivity and of intricate ultrafast and light-driven and scattering processes, which shall be motivated by a didactically sound visualization of excitation processes [3] in addition to the basic explanation of the theory.

However, the most accurate wave function-based techniques reach their computational limits at an order of some ten electrons! At the same time, electron dynamics is challenged by complex and large-scale material-scientific problems relevant to modern society.

This presentation identifies strategies to address some of the major methodological and computational obstacles. For realistic calculations of (large) target structures in their true environment, description of energy and charge transfer processes among electrons and nuclei in the neighborhood are established [4]. Moreover, different ways of modeling nano-sized structures are considered [5,6]. Finally, modern computing strategies, machine learning from the field of data science [7], and quantum simulations from the field of quantum information technology [8], are explored for their use in electron dynamics computations.

[1] A. Bande, Chemical Modelling 17, 91 (2023), 10.1039/9781839169342-00091
[2] A. Bande, Trendbericht Theoretische Chemie, Nachrichten der Chemie 72, 48 (2024),  0.1002/nadc.20244145393
[3] F. Langkabel, P. A. Albrecht, A. Bande, P. Krause, Chem. Phys. 557, 111502 (2022), 10.1016/j.chemphys.2022.111502
[4] F. M. Pont, A. Bande, E. Fasshauer, A. Molle, D. Peláez, N. Sisourat, Phys. Rev. A 110, 042804 (2024), 10.1103/PhysRevA.110.042804.
[5] S. Marando, A. Bande, J. Chem. Phys. 163, 024124 (2025), 10.1063/5.0268255.
[6] P. Krause, J. C. Tremblay, and A. Bande, J. Phys. Chem. C 125, 4793 (2021), 10.1021/acs.jpca.1c02501
[7] K. Singh, K. H. Lee, D. Peláez, A. Bande, J. Comput. Chem. 1, (2024) 10.1002/jcc.27443.
[8] F. Langkabel, A. Bande, J. Chem. Theo. Comput. 18, 7082 (2022), 10.1021/acs.jctc.2c00878