Dissertation: Cosmic clues from astrophysical particles
Time: Fri 2020-06-12 13.00 - 15.00
Location: FB42, AlbaNova University Centre, Roslagstullsbacken 21
Participating: Francesca Capel
Cosmic clues from astrophysical particles
Doctoral student: Francesca Capel, Department of Particle and Astroparticle Physics
Opponent: Dr Michael Unger, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
Supervisor: Professor Christer Fuglesang, Partikel- och astropartikelfysik
OBSERVE! This dissertation is also available on Zoom with meeting adress: https://kth-se.zoom.us/j/67435898835.
Ultra-high-energy cosmic rays (UHECRs) are charged particles that have been accelerated to extreme energies, such that they are effectively travelling at the speed of light. Interactions of these particles with the Earth’s atmosphere lead to the development of extensive showers of particles and radiation that can be measured with existing technology. Despite decades of research, the origins of UHECRs remain mysterious. However, they are thought to be accelerated within powerful astrophysical sources that lie beyond the borders of our Galaxy. This thesis explores different ideas towards the common goal of reaching a deeper understanding of UHECR phenomenology. Part I concerns the development of a novel space-based observatory that has the potential to detect unprecedented numbers of these enigmatic particles. The feasibility of such a project is demonstrated by the results from the Mini-EUSO instrument, a small ultraviolet telescope that is currently on-board the International Space Station. In Part II, the focus is on fully exploiting the available information with advanced analysis techniques to close the gap between theory and data. UHECRs are closely connected to the production of neutrinos and gamma rays, so frameworks for the joint analysis of these complementary cosmic messengers are also developed. The results presented herein demonstrate that to progress, it is crucial to invest in the development of both detection and analysis techniques. By taking a closer look at the existing data, new clues can be revealed to reach a more comprehensive understanding and better inform the design of future experiments.