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Andrii Trelin

Imaging and motion detection at the nanometer scale : a data-driven approach

Universität Rostock, 12.12.2024

https://doi.org/10.18453/rosdok_id00005764

Abstract: 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.

doctoral thesis   free access