Explore 3 | Winter 2022

Explore (EXPeriential Learning Opportunity through Research and Exchange) is an academic course for international student research collaboration.
It is an innovative teaching initiative offered by the Goethe University (Germany), York University & University of Alberta (Canada) and Washington State University of St. Louis (USA).
Canadian students from York University must apply for participation - please check below!
See also below for details on the registration for Goethe-University students!

Prof. Laura Sagunski
Prof. Camilla Hansen
Prof. Jürgen Schaffner-Bielich
Prof. Nassim Bozorgnia
Prof. Saeed Rastgoo
Prof. Sean Tulin
Prof. Patrick Hall
Prof. James Mertens
Language English
Format Online via Zoom
Schedule Tuesday, 4 - 6 pm., online
Credit Points tba (Link to Olat)

Course organisation

Research topics

  • Quasars: These are cosmic lighthouses powered by supermassive black holes, visible from across the Universe. You will use high-energy photons from quasars to map out the history of the expanding Universe and confront your findings against the current paradigms of cosmology.
  • Stellar archaeology: Exotic stars containing carbon but little heavier elements are relics from the distant past, representing some of oldest known stars. You will analyze spectroscopic data from these stars to measure their composition and infer details about the ancient galactic environments in which they formed.
  • Dark matter hidden in neutron stars: Within the centers of neutron stars - extreme stars of pure nuclear matter - may be hiding cores of dark matter. When two such neutron stars collide, their dark matter cores can be revealed in the pattern of gravitational waves. You will perform simulations for how cores form for different types of dark matter, how they impact gravitational wave signals, and you will search for this effect in data from the Laser Interferometer Gravitational-Wave Observatory (LIGO).
  • Machine learning gravity: Mathematical techniques provide us with different ways to model gravitational wave signals from colliding black holes. However, these approaches often rely upon expensive numerical integrations. This can be alleviated using a type of neural network known as a physics-informed neural network (PINN). You will work towards producing waveforms using both a PINN and classical integrators, and investigate the differences between the two.


ID Day Time Room Language Person
Lecture Tuesday 4 - 6 pm. online English individual
Meeting with group mentor Thursday 4.15 - 6 pm. online English individual