Galactic Gas Distribution and Cosmic-Ray Transport

While space between the stars is transparent to the naked eye, it is hardly empty. It is filled with a very dilute gas, radiation, magnetic fields, and high-energy particles, so-called cosmic- rays. All these constituents interact with each other forming a highly dynamical environment. In this project we will try to improve our understanding of this environment, where we focus on the cosmic rays and the gas. The gas in the interstellar medium can be studied by dedicated observation of different spectral lines. Since we observe this gas from within the Milky way it is, however, very hard to determine its three-dimensional spatial distribution. The only directional information from the observations is the angular distribution of the emission and a shift of the spectral lines that can be translated to a relative motion between gas and observer. In this project, we therefore aim to compute new three-dimensional distributions not only of the gas, but also of cosmic-rays, their sources and other relevant quantities. For this, we will apply so-called information field theory models, which can relate observations to a model of the three-dimensional distribution in a statistical fashion and produce a best fit model in the process. We will utilize current knowledge on the interaction between the gas and the cosmic rays to obtain a joined model for the three -dimensional distribution of all these constituents. For this we combine modern codes for information field theory and for cosmic- ray transport to produce a joined inference framework. This will be an important advancement both in information field theory and in our understanding of the interstellar medium.

While space between the stars is transparent to the naked eye, it is hardly empty. It is filled with a very dilute gas, radiation, magnetic fields, and high-energy particles, so-called cosmic-rays. The dynamical environment formed in the interaction of all these constituents is the interstellar medium. In this project we improved our understanding of this environment in our Milky way, where we, correspondingly, developed new analysis methods. Here, we focussed on the cosmic rays and the gas in our Galaxy. The gas in the interstellar medium can be studied by dedicated observation in different wavelength regimes. Such observations yield the angular distribution of the emission and additional shifts of the wavelength of spectral lines, resulting from a relative velocity between gas and observer. Since we observe this gas from within the Milky way it is, however, very hard to translate these observations into a three-dimensional spatial distribution. For this, we applied so-called information field theory models, which can relate observations to a model of the three-dimensional distribution in a statistical fashion. These models also had to be supplied with the mathematical description of the motion of the gas and its emission. A prominent result of our project is a new reconstruction of the three-dimensional gas distribution in our Galaxy. Through interaction with the gas, the cosmic rays in the Milky way produce highly energetic radiation, i.e. gamma rays. As a further step we were able to determine the distribution of cosmic rays in our Galaxy by adding a description of the production of gamma-rays into our statistical analysis. To further our understanding of this distribution, we also require models describing the transport of cosmic rays. In the context of this proposal, we investigated how our improved gas model for the Galaxy impacts the transport of cosmic rays. Additionally, we coupled our numerical modelling of cosmic-ray transport to the statistical analysis, to allow a reconstruction of the distribution of cosmic-ray sources. In this context, we could show that the methods are also applicable to other scientific field, like, e.g., medical imaging. In our project, we made important advancements in the understanding of the three-dimensional structure of our Galaxy, while at the same time providing important extensions to the statistical methods used in such analyses.