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cond-mat.mtrl-sci2026

Laser-written reconfigurable energy landscapes and programmable Moiré spin textures

Matteo Panzeri, Piero Florio, Davide Girardi +18

Magnetic textures are central to emerging spintronic and unconventional computing technologies due to their rich dynamics, topological properties and nanoscale dimensions. A major…

cond-mat.mtrl-sci2026

Data-Driven Estimation of the interfacial Dzyaloshinskii-Moriya Interaction with Machine Learning

Davi Rodrigues, Andrea Meo, Ali Hasan +8

Machine learning offers powerful tools to support experimental techniques, particularly for extracting latent features from large datasets. In magnetic materials, accurately estima…

cond-mat.mtrl-sci2026

An all-magnonic neuron with tunable fading memory

David Breitbach, Moritz Bechberger, Hanadi Mortada +9

Magnonics offers nanometer-scale wave propagation and strong nonlinearities, making it attractive for neuromorphic applications such as artificial neurons. Yet, magnonic elements w…

cond-mat.mtrl-sci2025

Octupole-driven spin-transfer torque switching of all-antiferromagnetic tunnel junctions

Jaimin Kang, Mohammad Hamdi, Shun Kong Cheung +23

Magnetic tunnel junctions (MTJs) based on ferromagnets are canonical devices in spintronics, with wide-ranging applications in data storage, computing, and sensing. They simultaneo…

cond-mat.mtrl-sci2025

Multi-value Probabilistic Computing with current-controlled Skyrmion Diffusion

Thomas B. Winkler, Yuean Zhou, Grischa Beneke +6

Magnetic systems are highly promising for implementing probabilistic computing paradigms because of the fitting energy scales and conspicuous non-linearities. While conventional bi…