Quantum-inspired Techniques in Tensor Networks for Industrial Contexts
Alejandro Mata Ali Iñigo Perez Delgado Aitor Moreno Fdez. de Leceta
In this paper we present a study of the applicability and feasibility of
quantum-inspired algorithms and techniques in tensor networks for industrial
environments and contexts, with a compilation of the available literature and
an analysis of the use cases that may be affected by such methods. In addition,
we explore the limitations of such techniques in order to determine their
potential scalability.