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Thomas Pöschl

Courses and Dates

Offered Bachelor’s or Master’s Theses Topics

Antiparticle Spectra in Upsilon Decays

Detection of antiparticle cosmic rays can be a key way to search for exotic sources of antimatter in our universe such as dark matter annihilation. Cosmic-ray antideuterons (an antiproton and antineutron bound together) are particularly good to look for since they are infrequently produced by non-exotic sources. However, the mechanism of their production from antiprotons and antineutrons---called coalescence---is poorly understood. We can study this process in the laboratory using decays of upsilon mesons (bound states of bottom and antibottom quarks) produced at the Belle experiment in Tsukuba, Japan (and in the near future at the Belle II experiment). To do this, we need to measure the momentum spectra of antideuterons and antiprotons produced by decaying upsilons. The task of this thesis work is to analyze existing data from the Belle experiment (and plan for future data from the Belle II experiment) to search for antiprotons and antideuterons in upsilon decays.

Tasks

Learn how an analysis is conducted at a high-energy physics experiment

Compose the analysis using C++ / Python

Check the accuracy of the analysis using simulated data

Prerequisites 

Experience in C++ or Python programming is helpful, but not required.

Contact

Thomas Pöschl, Room PH1 3257, Thomas.poeschl@ph.tum.de

Daniel Greenwald, Room PH1 3275, daniel.greenwald@tum.de

Prof. Stephan Paul, Room PH1 3263, stephan.paul@tum.de

suitable as
  • Master’s Thesis Nuclear, Particle, and Astrophysics
Supervisor: Stephan Paul
Particle Identification for a Radiation Monitor based on Neural Networks

The RadMap Telescope is a new radiation detector to measure and characterize the radiation environment onboard the International Space Station. It is most sensitive to low-energy protons and ions and can distinguish particles by their interactions with the material of the detector. In this thesis, a neural network shall be developed that can identify the particle species by the measured interaction in the detector. You will have to design a network structure, train the network with simulation data, and assess its performance. The final network shall be implemented on the on-board computer of the RadMap Telescope. 

Tasks

  • Acquire necessary theoretical understanding of neural networks and the different architectures.
  • Implement a neural network in Python using Keras with Tensorflow.
  • Train and validate the algorithm with detector data generated with the high-energy physics simulation tool Geant4.
  • Calculate the reconstruction efficiency and confusion rate for ions ranging from Hydrogen to Iron.
  • Implement the trained network on the on-board computer of the RadMap Telescope using the C++ programming language.

Prerequisites 

Experience in Python and C++ programming is helpful, but not required.

Contact

Thomas Pöschl, Room PH1 3554, Thomas.poeschl@ph.tum.de

Prof. Stephan Paul, Room PH1 3263, stephan.paul@tum.de

suitable as
  • Master’s Thesis Nuclear, Particle, and Astrophysics
  • Master’s Thesis Applied and Engineering Physics
Supervisor: Stephan Paul
Simulations of the Lunar Radiation Environment

In recent years, the plan of sending human back to the Moon came back to the fore. Some ambitious plans even consider building a permanently inhabited base on the moon. However, the radiation environment on the Moon can be a problematic health issue for the astronauts. Only little data is available from the Moon’s surface and the effect of particles that are produced in the upper layers of the lunar surface by the bombardment of cosmic rays is not yet fully understood. In this thesis, a full simulation of the lunar radiation environment shall be conducted. A detailed simulation of the galactic cosmic-ray background interacting with the Moon’s regolith shall be conducted using the high-energy physics simulation tool Geant4. The outcome of this study shall be used to set requirements for radiation detectors that shall measure all contributing radiation components. These results shall be used to optimize the design of the radiation detector currently under development for the LUVMI-X moon rover. 

Tasks

  • Acquire the necessary theoretical understanding of the radiation environment in space and the interactions of cosmic rays with matter.
  • Set up a simulation written in C++, based on the Geant4 simulation framework.
  • Analyze and interpret the simulated radiation environment.
  • Optimize the design of a particle detector that can efficiently measure the lunar radiation environment.  

Prerequisites 

Experience in C++ programming is helpful, but not required.

Contact

Thomas Pöschl, Room PH1 3257, Thomas.poeschl@ph.tum.de

Martin Losekamm, Room PH1 3257, m.losekamm@tum.de

Prof. Stephan Paul, Room PH1 3263, stephan.paul@tum.de

suitable as
  • Master’s Thesis Nuclear, Particle, and Astrophysics
  • Master’s Thesis Applied and Engineering Physics
Supervisor: Stephan Paul
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