New study reveals how maze-like magnetic patterns form and evolve in materials
Peer-Reviewed Publication
Updates every hour. Last Updated: 1-May-2026 17:16 ET (1-May-2026 21:16 GMT/UTC)
Maze magnetic domains in soft magnetic materials strongly influence energy loss in electric motors, particularly at high temperatures. However, existing models struggle to explain their complex, temperature-dependent behavior. To address this gap, researchers developed an entropy-extended Ginzburg-Landau model combined with data-driven analysis to study these structures. The approach reveals how entropy and energy interactions drive magnetization reversal and increasing domain complexity, providing new insights into magnetic energy-loss mechanisms.
Photonic circuits are key tools for information processing but scaling them usually requires many optical layers. We demonstrate a programmable free-space photonic platform performing a wide class of translation-invariant, high-dimensional transformations using only three layers. Encoding information in structured light, we realize quantum-walk dynamics over large lattices, distributing a single input into thousands of outputs. The approach supports operation with single photons, highlighting free-space optics as a promising route toward scalable photonic information processing.