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The nature of the sources powering nebular He II emission in star-forming galaxies remains debated, and various types of objects have been considered, including Wolf-Rayet stars, X-ray binaries, and Population III stars.
Modern X-ray observations show the ubiquitous presence of hot gas filling star-forming galaxies. We use a collisional ionization plasma code to compute the specific He II ionizing flux produced by hot gas and show that if its temperature is not too high (less than or similar to 2.5 MK), then the observed levels of soft diffuse X-ray radiation could explain He II ionization in galaxies.
To gain a physical understanding of this result, we propose a model that combines the hydrodynamics of cluster winds and hot superbubbles with observed populations of young massive clusters in galaxies. We find that in low-metallicity galaxies, the temperature of hot gas is lower and the production rate of He II ionizing photons is higher compared to high-metallicity galaxies. The reason is that the slower stellar winds of massive stars in lower-metallicity galaxies input less mechanical energy in the ambient medium.
Furthermore, we show that ensembles of star clusters up to similar to 10-20 Myr old in galaxies can produce enough soft X-rays to induce nebular He II emission. We discuss observations of the template low-metallicity galaxy I Zw 18 and suggest that the He II nebula in this galaxy is powered by a hot superbubble.
Finally, appreciating the complex nature of stellar feedback, we suggest that soft X-rays from hot superbubbles are among the dominant sources of He II ionizing flux in low-metallicity star-forming galaxies.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction.
The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data.
Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS).
This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.