Bonn 2025 – wissenschaftliches Programm
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QI: Fachverband Quanteninformation
QI 37: Poster – Quantum Information Technologies (joint session Q/QI)
QI 37.15: Poster
Donnerstag, 13. März 2025, 17:00–19:00, Tent
Resolving the Low-Field Ambiguity in All-Optical Magnetometry in Resource Constrained Devices — •Ann-Sophie Bülter1, Ludwig Horsthemke1, Jens Pogorzelski1, Dennis Stiegekötter1, Frederik Hoffmann1, Sarah Kirschke2, Markus Gregor2, and Peter Glösekötter1 — 1Department of Electrical Engineering and Computer Science, FH Münster — 2Department of Engineering Physics, FH Münster
Machine learning algorithms offer a promising solution for unambiguous magnetic field determination in all-optical fluorescene intensity measurements with nitrogen-vacancy (NV) centers, addressing the ambiguity below 8 mT [1].
To continue this work, we exploit the dependency of the phase and the magnitude of the fluorescence on both the magnetic field and frequency, applying advanced regression techniques. The primary focus of our study is to investigate the effect of feature engineering to enhance the accuracy of magnetic field determination. By comparing the results of feature-engineering approaches with those using raw data alone, we demonstrate the potential of machine learning for precise and reliable magnetic field measurements in all-optical magnetic field sensing. Additionally, we assess the resource efficiency of these methods to ensure their feasibility for the implementation on a microcontroller.
[1] Horsthemke, L., et al. Towards Resolving the Ambiguity in Low-Field, All-Optical Magnetic Field Sensing with High NV-Density Diamonds. Engineering Proceedings 68, 8 (2024).
Keywords: NV Center; All-Optical; Fluorescence Lifetime; Magnetometry; Machine Learning