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Experimental Physics 5b

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Welcome to the website of Astroparticle Physics Groups at TU Dortmund! The focus of our research interests is the field of multi-messenger and astroparticle physics. To study the thin rain of particles and waves arriving at Earth from the Cosmos, we develop and use modern detectors, advanced simulation and analysis methods, including machine learning. We aim at advancing computer science methods with the goal of identifying and characterising Cosmic accelerators and other high-energy phenomena.


Neutrino Astronomy


Neutrinos

Neutrino Astronomy aims at opening a new observational window, by detecting high energy neutrinos of astrophysical origin. The astroparticle physiscs group at TU Dortmund University is a member of the IceCube Collaboration and will also participate in the proposed upgrades of the detector.

Gamma Astronomy


Gamma

Using high-energy gamma radiation offers a unique view into the universe. Only the most extreme objects, like supernova remnants in our own Milkyway and supermassive black holes in the centers of other galaxies are sources of gamma radiation at TeV energies. Our main focus is on developing new, machine-learning based analysis methods, improving the simulations, real-time analysis and providing open and reproducible results.

Radio Astronomy


Radio Antennas

Radio astronomy provides information about astrophysical sources in the low-energy range of the electromagnetic spectrum. In Dortmund, we analyze data from the Very Long Baseline Array (VLBA) and the Low-Frequency Array (LOFAR) to learn more about the morphologies and acceleration mechanisms of cosmic accelerators such as active galactic nuclei.

Particle Interaction & Propagation


Propagation

A precise understanding of the interaction processes and a performant simulation of the particle propagation are necessary to do significant measurements. In Dortmund, the Monte-Carlo simulation tools CORSIKA and PROPOSAL simulating extended air showers from cosmic rays and neutrino induced charged leptons are further developed.

Method Development


Invers

For precise physics measurements the development of novel analysis techniques and concepts is as important as the development of new detection mechanisms. Method development at E5b largely focuses on machine learning and pattern recognition and extends beyond the application of novel tools. The areas of research include signal-background-separation with machine learning techniques, the development of DNN-based reconstruction algorithms and solving inverse problems.



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Contact

Experimental Physics Vb

Otto-Hahn-Str. 4a
44227 Dortmund
(Anfahrtsbeschreibung)

Tel.: (+49) 231 755-3539
Fax: (+49) 231 755-4547