collaborators

7 papers

cond-mat.dis-nn2026

Non-Hermitian Delocalization Realizes Random Dirac Criticality in One Dimension

Bo Li, Shen Zhang, Ren Zhang

Non-Hermitian systems can evade Anderson localization and exhibit delocalized states even in one dimension. Here, we show that such non-Hermitian delocalized states under periodic…

cond-mat.dis-nn2026

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…

cond-mat.str-el2026

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…

cond-mat.str-el2026

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-…

cond-mat.str-el2026

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…

cond-mat.str-el2026

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…