Técnicas Quantum-Inspired en Tensor Networks para Contextos Industriales
arXiv:2404.17645v1
Originality Synthesis-oriented
AI Analysis
This is an incremental study for industrial applications of quantum-inspired tensor networks.
This paper studies the applicability and feasibility of quantum-inspired algorithms in tensor networks for industrial contexts, compiling literature and analyzing use cases while exploring limitations to determine scalability.
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.