I conduct theoretical research on magnetization dynamics and magnon transport in magnetic systems, focusing on magnetic-field- and spin-torque-driven precession, nutation, and switching of magnetic moments, as well as magnon transport mechanisms. By constructing theoretical models of spin dynamics and quantum transport, I explore the intrinsic connection between magnetization dynamics and magnon transport, develop methods for predicting critical points in complex magnetic systems, and investigate their potential applications in novel magnetic memory and magnetic sensing devices.
I study emergence phenomena and their physical mechanisms in complex intelligent systems, investigating the intrinsic connection between abrupt performance changes in neural networks and nonlinear phase transitions. Using statistical physics methods such as order parameters and critical exponents, I analyze the critical behavior and capability emergence of models like Hopfield networks and Transformers during scaling. By integrating bistability and phase transition dynamics in nonlinear magnetic subsystems, I explore universal physical mechanisms underlying intelligent emergence. This research contributes to a deeper understanding of the formation mechanisms of emergent capabilities in large models and provides a theoretical basis for designing novel brain-inspired computing architectures.