Title image of the page - Christopher Körber

Christopher Körber

High-Performance Computing Expert

My name is Christopher Körber and my job is to help domain scientist in High-Performance Computing matters at the Fraunhofer IEG. Previously, I was a postdoc at the Institute for Theoretical Physics II, lecturer, and member of the Research School Executive Board at the Ruhr-University Bochum. Before this position, I was a Feodor Lynenen Fellow at UC Berkeley and the Lawrance Berkeley National Lab. I obtained my doctorate in physics from Bonn University in association with the Forschungszentrum in Jülich.

I have specialized in simulating and analyzing quantum systems. A significant part of my work is related to connecting ideas for new physics, like Dark Matter, to existing experiments. Establishing such a connection is particularly difficult since, on the one hand, making predictions for things you don't know, well, is difficult. On the other hand, even for a fixed description of nature, one still has to solve a quantum problem (usually NP-hard). The latter problem is usually tackled by clever simplifications, introducing controlled approximations, and utilizing significant computational power. The first issue is addressed by an effective description using symmetries appearing in nature (Is a charge carried away? Is the process invariant under a mirror symmetry?...). Validating such effective descriptions and inferring it's properties is done by running (several) simulations and comparing predictions with experiments. On a more technical side, this procedure is called simulation-based inference of effective field theories. The beauty of this framework is that it is not only predictive for new physics ideas but also for interpreting known phenomena (which are difficult to describe for other reasons) like carbon nanosystems or quantum annealers. Practically, to face these problems, my work is centered around (high-performance) programming, data management, and utilizing (Bayesian) model selection frameworks.

Some more facts about me

  • I am a software enthusiast and Pythonista. I love trying new things, facing new challenges, and optimizing and automating daily routines.
  • I believe in open-source principles — both professionally and as guiding core principles. As such, I believe actively promoting diverse perspectives is the only way to ensure optimal decisions.
  • Also, I believe that $\LaTeX$, the arXiv, and VCS platforms like GitLab and GitHub are invaluable to the (modern) scientific process.
  • I use git for almost everything and am quite successful in convincing others to use it (not sure what one can infer from this...).
  • I believe the Bayesian principle is one of the most enlightening notions to understand how humans form beliefs.
  • I rather have a single well-made espresso a day than a never-ending supply of other sufficiently good coffee.