Imaging and motion detection at the nanometer scale: a data-driven approach Trelin, Andrii , 1998- (VerfasserIn) Postnov, Dmitry (AkademischeR BetreuerIn) Otto, Oliver , 1964- (AkademischeR BetreuerIn) Universität Rostock (Grad-verleihende Institution) Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät (Grad-verleihende Institution) Text theses Text Hochschulschrift 2024 12.12.2024 eng ger electronic resourceremoteComputermedienOnline-Ressourceapplication/pdf1 Online-Ressource (vi, 92 Seiten) Illustrationen, Diagramme This thesis applies data-driven methods to small signal detection in physics, focusing on optical sensing of neuron action potentials and nanoscale tomography of nitrogen-vacancy centers in diamonds. It introduces ChiSCAT, an optical scheme and algorithm that recover membrane motion signals from non-image data, validated on human cells and shared as open datasets. It also presents an optimized NV tomography method that cuts acquisition time by ~10x. These results show how advanced data processing can unlock signals from challenging measurements, bridging data science and experimental physics.<eng> Open Access Urheberrechtsschutz 1.0 vorgelegt von Andrii Trelin Enthält Zeitschriftenartikel GutachterInnen: Dmitry Postnov (Aarhus University) ; Oliver Otto (Universität Greifswald) Dissertation Universität Rostock 2025 Kumulative Dissertation 530 621.3822 621.3 https://purl.uni-rostock.de/rosdok/id00005764 https://doi.org/10.18453/rosdok_id00005764 https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00005764-1 https://d-nb.info/1418060054/34 Imaging and motion detection at the nanometer scale--(DE-627)1982205334 urn:nbn:de:gbv:28-rosdok_id00005764-1 doi: 10.18453/rosdok_id00005764 oclc: 1612392384 ppn: (DE-627)1982199067