2 papers
cond-mat.str-el2026
Beyond Stoner-Wohlfarth: Machine-Learning Models and Symbolic Regression of Hard-Magnet Properties
Samuel J. R. Holt, Christina Winkler, Timoteo Colnaghi +7
Predicting the extrinsic properties from hysteresis loops of a magnetic grain, namely the coercive field, remanent magnetisation, and maximum energy product, from its intrinsic mic…
cond-mat.quant-gas2024
Fermionic Quantum Turbulence: Pushing the Limits of High-Performance Computing
Gabriel Wlazlowski, Michael McNeil Forbes, Saptarshi Rajan Sarkar +2
Ultracold atoms provide a platform for analog quantum computer capable of simulating the quantum turbulence that underlies puzzling phenomena like pulsar glitches in rapidly spinni…