Freiburg 2024 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

A: Fachverband Atomphysik

A 9: Strong-field Ionization and Imaging (joint session MO/A)

A 9.3: Vortrag

Montag, 11. März 2024, 17:30–17:45, HS 3044

Wavefunction Reconstruction of Excitonic Edge States using Machine Learning — •Aritra Mishra and Alexander Eisfeld — Max Planck Institute for the Physics of Complex Systems, Dresden, Germany

A typical problem in quantum mechanics is to reconstruct the eigenstate wave functions from measured data. In the case of molecular aggregates, the information about the excitonic eigenstates is important to understand the optical and transport properties [1]. It has been shown for a linear and a 2D arrangement of the aggregate molecules that such a reconstruction is possible from the spatially resolved near field absorption spectra [2].

Here, we consider the aggregates arranged in two sublattices in a 2D arrangement, each sub lattice having a particular orientation of the molecules as described in [3]. Interestingly, such an arrangement can lead to the formation of topological excitonic edge states. We study the reconstruction of the excitonic wave function of such a system from the near field absorption spectra. The reconstruction is further investigated in the presence of disorder in the Hamiltonian and noise added to the spectra.
[1] X. Gao and A. Eisfeld, J. Phys. Chem. Lett. 9, 6003 (2018)
[2] F. Zheng, X. Gao and A. Eisfeld, Phys. Rev. Lett. 123, 163202 (2019)
[3] J. Yuen-Zhou, S. K. Saikin, N. Y. Yao and A. Aspuru-Guzik, Nature Materials 13, 1026 (2014)

Keywords: Molecular Aggregates; Excitons Edge States; Machine Learning