3 papers
physics.optics2026
Hybrid-plasticity Photonic Synapses Enabling Hardware-Level Neural Reuse
Chenlei Li, Tao Shu, Cunyu Shi +12
Biological intelligence is distinguished by neural reuse, the capacity to preserve established learning memory while repurposing it for new tasks and dynamic environments. Bringing…
cond-mat.mtrl-sci2026
GPUMDkit: A User-Friendly Toolkit for GPUMD and NEP
Zihan Yan, Denan Li, Xin Wu +20
Machine-learned interatomic potentials have revolutionized molecular dynamics simulations by providing quantum-mechanical accuracy at empirical-potential speeds. The graphics proce…
cond-mat.mtrl-sci2026
A Perspective on Training Machine Learning Force Fields for Solid-State Electrolyte Materials
Zihan Yan, Shengjie Tang, Yizhou Zhu
Machine learning force fields enable high-accuracy modeling of solid-state electrolytes (SSEs). This perspective evaluates dataset size, reference quality, and model architectures.…