16 citations · 22 across the 10 of their papers we have counts for
5 papers · 1 filter
Magnetic HIP-NN for spin dynamics in disordered itinerant magnets
Supriyo Ghosh, Yunhao Fan, Sheng Zhang +2
We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-mediated spin dynamics in disord…
Designing electronic magnetoelectric matter with organic quantum spin trimers
Yuko Hosokoshi, Christopher P. Aoyama, Zhuowei Zhang +17
Magnetoelectric (ME) phenomena are commonly driven by spin-lattice coupling. Here we demonstrate a different route based on frustrated quantum spin trimers that intrinsically inter…
Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems
Gia-Wei Chern, Yunhao Fan, Sheng Zhang +1
We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin systems. We generalize the Behler-…
Machine-learning force-field models for dynamical simulations of metallic magnets
Gia-Wei Chern, Yunhao Fan, Sheng Zhang +1
We review recent advances in machine learning (ML) force-field methods for Landau-Lifshitz-Gilbert (LLG) simulations of itinerant electron magnets, focusing on scalability and tran…
Machine learning nonequilibrium phase transitions in charge-density wave insulators
Yunhao Fan, Sheng Zhang, Gia-Wei Chern
Nonequilibrium electronic forces play a central role in voltage-driven phase transitions but are notoriously expensive to evaluate in dynamical simulations. Here we develop a machi…