Hello! I am Tianyi Zhang (CV), a postdoctoral researcher at the Institute of Physics, Chinese Academy of Sciences.
My research focuses on the application of magnetic materials in artificial intelligence, primarily covering spin dynamics and neural networks.
- In spin dynamics, I investigate spin dynamic processes in magnetic materials, exploring how mechanisms such as magnetic fields, spin-transfer torque, and spin-orbit torque regulate magnetization dynamics. Through theoretical modeling and numerical simulations, I develop novel magnetic memory units with high speed, low power consumption, and high density, providing a theoretical foundation for next-generation magnetic memory.
- In neural networks, I focus on emergence phenomena and their physical origins. By comparing phase transition behaviors in magnetic systems with emergence in neural networks, I reveal the common mechanisms by which complex systems generate new capabilities near critical points. In particular, by integrating nonlinear magnetic subsystems, Hopfield networks, and Transformer models, I explore the principles underlying the emergence of intelligence in complex systems, offering a theoretical perspective for understanding emergence laws in artificial intelligence and constructing novel brain-inspired computing architectures.