Dresden 2026 – wissenschaftliches Programm

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MA: Fachverband Magnetismus

MA 58: Computational Magnetism II

MA 58.2: Vortrag

Freitag, 13. März 2026, 09:45–10:00, POT/0151

A Fourier-Space Approach to Physics-Informed Magnetization Reconstruction from Nitrogen-Vacancy Measurements — •Alexander Setescak¹, Florian Bruckner¹, Dieter Suess¹, Young-Gwan Choi^2,3, Hayden Binger², Lotte Boer², Claire Donnelly², Uri Vool², and Claas Abert¹ — ¹University of Vienna, Vienna, Austria — ²Max Planck Institute for the Chemical Physics of Solids, Dresden, Germany — ³University of Ulsan, Ulsan, Republic of Korea

Reconstructing complex magnetization textures from nitrogen-vacancy (NV) magnetometry stray-field measurements presents a challenging inverse problem. In this work, we introduce a physics-informed method that addresses this by incorporating the full micromagnetic energy directly into the variational formulation.

Built on a PyTorch backend, our forward model integrates an auto-differentiable micromagnetic framework with FFT-based stray-field calculations and Fourier-space upward continuation. This enables efficient gradient-based optimization via the adjoint method and allows the sensor-sample distance to be treated as an optimization parameter. By doing so, we eliminate the experimental uncertainty arising from unknown NV implantation depths and surface oxidation layers.

Validation on synthetic data demonstrates high-fidelity reconstruction of spin textures and precise sensor height estimation. Furthermore, when applied to experimental NV measurements of the van der Waals magnet Fe_3−xGaTe₂, the framework reconstructs skyrmion bubbles that are consistent with theoretical micromagnetic behavior.

Keywords: Nitrogen-vacancy magnetometry; Inverse problems; Magnetization Reconstruction; Micromagnetics; Skyrmions