Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Software Engineering

Eduard Gette will present his master thesis proposal on the topic:

Predicting Spin-Interaction Parameters of the Hamiltonian from Simulated INS Data of Single Crystals

Inelastic neutron scattering (INS) experiments are a special kind of spectroscopy in which a monochromatic incident beam of neutrons is ”fired”
at a sample of the material of interest. Upon collision with the target material an incident neutron gets diffracted and some of its energy is absorbed by the sample. Since both of the quantities as measured by the detectors behind the sample, the "wave transfer" vector and "energy transfer", are determined by the structural properties of the sample, the resulting data can be used to estimate parameters for modelling the underlying physical process. Estimating these parameters however is a non-trivial task often requiring field experts, due to the ill-posed nature of the reverse transformation problem.
The aim of this thesis will be to investigate the effectiveness of machine learning algorithms for solving one such inverse transformation problem - estimating spin-interaction parameters of the hamiltonian using INS data of single crystal materials. All experiments will be carried out on simulated INS data of a BaNi2V2O8 single crystal sample.

Die Zugangsdaten zum Zoom Onlinemeeting teilt Hoang Lam Nguyen gern auf Anfrage mit.