Robert Hammann: Probing the Invisible, Gebunden

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This book aims to shed light on this mystery by searching for hypothetical dark matter particle candidates in our Milky Way. The detector, which contains about 8 tons of liquid xenon as a target, is located in an underground laboratory in Italy to shield it from cosmic rays. Although dark matter has not yet been detected, the experiment has yielded some of the most sensitive results worldwide in recent years. Its large target mass, low energy threshold and extremely low background radiation make XENONnT sensitive to other rare processes, including interactions of neutrinos originating from the interior of the Sun. Robert Hammann's doctoral thesis makes outstanding contributions to both the physics analyses of this experiment and the development of new detector technologies for the future.

Robert's thesis documents his central contributions to two key analyses of XENONnT: the search for weakly interacting massive particles (WIMPs), a widely discussed dark matter candidate, and the measurement of solar neutrinos via coherent neutrino-nucleus scattering. The latter represents the first evidence for this interaction in a liquid-xenon detector, marking an important milestone in establishing such detectors as neutrino observatories. Both analyses use data from the first two scientific measurement campaigns, totaling an exposure of 3.1 ton-years. This book places particular emphasis on the rigorous statistical treatment required for such rare-event searches, providing a comprehensive and well-documented description of the statistical inference methods employed and their associated validation studies. As part of this work, Robert developed a statistical framework used both for the physics searches and for predicting the sensitivity of future measurement campaigns. Both physics searches were published in PRL 135 (2025) 221003 and PRL 133 (2024) 191002, respectively, and this book extends well beyond the content of these publications by documenting the extensive tests conducted to verify the robustness of the analyses.