AI RESEARCH
3D Magnetic Field Reconstruction and Mapping with Physics-Informed Neural Networks
arXiv CS.LG
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ArXi:2605.25640v1 Announce Type: cross Accurate reconstruction of magnetic fields in inaccessible regions is vital for many high-precision experiments in physics. Traditional methods, such as spherical harmonic expansion, often suffer from truncation errors that limit their precision. This study proposes an advanced Physics-Informed Neural Network (PINN) framework for high-precision 3D magnetic field mapping.