In this mathematical work, various questions are studied that allow tomographic reconstructions of nanostructures on the atomic or molecular scale. In addition to uniqueness and stability results (`what kind of data is sufficient and what kind of noise can be compensated to uniquely reconstruct discrete structures?') a special focus is placed on investigating connections to fields such as number theory, algebra, discrete optimization, and geometrical clustering. Moreover, the computational complexity of the underlying tasks is studied, and algorithms are developed and applied to real-data originating from materials science and plasma physics experiments.
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In this mathematical work, various questions are studied that allow tomographic reconstructions of nanostructures on the atomic or molecular scale. In addition to uniqueness and stability results (`what kind of data is sufficient and what kind of noise can be compensated to uniquely reconstruct discrete structures?') a special focus is placed on investigating connections to fields such as number theory, algebra, discrete optimization, and geometrical clustering. Moreover, the computational compl...
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