A new perspective on tensor-network contractions

Tensor-network states have the potential to bypass the exponentially large number of parameters of quantum states. However, the computational cost of the faithful tensor-network contractions still grows exponentially with system sizes in higher dimensions. In this talk, we introduce a new perspective for tensor-network contractions based on optimization theory. We illustrate the conceptual idea through matrix product states and tree tensor networks.