Tensor Networks

Tensor Networks are a mathematical framework that efficiently represents and manipulates high-dimensional tensors using multilinear algebra methods, aiming to solve complex computational problems in quantum systems. Its core objective is to reduce computational complexity and enhance the accuracy and efficiency of numerical simulations by decomposing high-dimensional tensors. Tensor Networks have broad application value in fields such as quantum information science, condensed matter physics, and machine learning, effectively handling large-scale data and complex models, and advancing research in these areas.