Optimization at the Boundary of the Tensor Network Variety

Explore tensor network states and their applications in quantum many-body systems through this lecture. Delve into the concept of tensor network states forming a variational ansatz class, and examine the implications when the underlying graph contains a cycle. Discover how states on the boundary of the tensor network variety can provide more efficient representations for states of physical interest. Learn about a new ansatz class that includes these boundary states and understand the optimization process for finding ground states of local Hamiltonians. Gain insights into recent research developments in this field and their potential impact on quantum physics and information theory.