3 papers
physics.comp-ph2026
Cartesian tensor equivariant machine-learning force field for spin-dependent atomistic simulations
Junjie Wang, Yijie Zhu, Zhongwei Zhang +5
Magnetic materials exhibit an intricate coupling between atomic structure and spin degrees of freedom, posing a fundamental challenge for atomistic simulations across experimentall…
cond-mat.mtrl-sci2025
Observation of cooperative strong coupling between optical phonon and crystal-field excitations in a pseudo Jahn-Teller system
Fangliang Wu, Xiaoxuan Ma, Zhongwei Zhang +6
Cooperative interactions between localized electronic excitations and crystal lattice are central to the emergence of complex structural phases in materials. However, the scaling r…
physics.comp-ph2025
GPU-MetaD: Full-Life-Cycle GPU Accelerated Metadynamics with Machine Learning Potentials
Haoting Zhang, Qiuhan Jia, Zhennan Zhang +6
Large-scale molecular dynamics simulations with high accuracy have been increasingly popular for their capability to bridge the gap between atomistic modeling and mesoscale phenome…