A Python-Based Control System for Automated 3D Magnetic Field Mapping on STAR_Lite
POSTER
Abstract
Accurate 3D magnetic field mapping is critical for validating coil alignment and optimizing the magnetic topology for plasma confinement in the STAR_Lite stellarator. To achieve this, a robust software control system was developed for a Thorlabs Kinesis LTS300C precision translation stage, which positions a 16-probe Hall effect array. Leveraging the Thorlabs .NET SDK via the Pythonnet API, the Python-based system provides comprehensive, automated control over the x, y, and z axes. Key functionalities include configurable velocity and acceleration profiles, absolute and relative positioning, automated homing routines, and sequential multi-axis movement through a command-line interface. This system ensures high-precision, reproducible probe positioning, thereby reducing measurement uncertainty and dramatically increasing mapping efficiency. The high-fidelity field maps generated by this system will serve as direct inputs for ongoing computational modeling of charged particle trajectories to analyze and improve confinement characteristics.
Presenters
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Abdul M Hamidu
Hampton University
Authors
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Georg F Harrer
Hampton University
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Abdul M Hamidu
Hampton University
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James Garner
Fayetteville State University
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Bishop Asare
Hampton University
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Angel Gayles
Hampton University
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Calvin Wayne Lowe
Hampton University
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Shibabrat Naik
Hampton University
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Alkesh Punjabi
Hampton University