Yu-Hsuan Lin

Physics-Informed Machine Learning for Response Tensors in Crystalline Magnets: Application to Kagome Metals

The prediction of response tensors from magnetic textures is a crucial challenge in the study of noncollinear magnets. Existing methods for constructing descriptors of a given response tensor are limited to first-order multipole expansions or restricted to simple magnetic structures. In this work, we construct a comple...