Physics beyond the Standard Model

The detectors and analysis methods we have developed to understand the strong interaction are also very well suited to either look for unusual signals directly, or to measure quantities that are needed in order to interpret data from other experiments looking for new physics. NA64 is a medium-scale experiment at CERN that uses a hadron-physics-like setup to search for signatures of Dark Matter particles. If existing at all, such signals are expected to be extremely rare, so large statistics and very good detector efficiency are a must. 

NA64

With NA64, we look for missing-energy events with electrons or muons being fired onto a hermetic detector setup. Such events could signal the production of so-called dark photons, massive vector particles linking the standard model world with a hitherto unknown so-called dark sector of particles. Our group provides and operates GEM tracking detectors which are used in the setup to measure the incoming particle track and its momentum and contributes to the reconstruction and data analysis.   

Contact person

Here you can find possible thesis topics.

Antiproton Cross Section Measurement

With AMBER, we will measure the differential cross section for the production of antiprotons, the antiparticles of protons, in proton-nucleus collisions. This is an important quantity in order to understand data measured e.g. by the Alpha Mass Spectrometer (AMS-II) on the International Space Station (ISS). AMS-II investigates the flux of antiparticles in space. There are hints of an excess of antiprotons, which could be explained by the annihilation of dark-matter particles. The limiting factor at the moment, however, is the large uncertainty on the production cross section of antiprotons from collisions of cosmic protons with He nuclei. AMBER will measure the antiproton production at different proton beam energies with high precision and thus contribute to the search for dark matter. 

Contact Person

Here you can find possible thesis topics.

Wird geladen