Continuous variables graph states shaped as complex networks: optimization and manipulation

TL;DR

This paper explores the creation and optimization of continuous variables quantum cluster states with complex network topologies, aiming to enhance measurement-based quantum computation through analytical and numerical methods.

Contribution

It introduces a method for optimizing complex network-shaped quantum states and demonstrates entanglement reshaping using linear optics, advancing quantum network design.

Findings

Denser, regular graphs enable better optimization.

Optimized quantum states reduce noise in quantum computation.

Entanglement connections can be reshaped via linear optics.

Abstract

Complex networks structures have been extensively used for describing complex natural and technological systems, like the Internet or social networks. More recently complex network theory has been applied to quantum systems, where complex network topologies may emerge in multiparty quantum states and quantum algorithms have been studied in complex graph structures. In this work we study multimode Continuous Variables entangled states, named cluster states, where the entanglement structure is arranged in typical real-world complex networks shapes. Cluster states are a resource for measurement-based quantum information protocols, where the quality of a cluster is assessed in term of the minimal amount of noise it introduces in the computation. We study optimal graph states that can be obtained with experimentally realistic quantum resources, when optimized via analytical procedure. We show that denser and regular graphs allow for better optimization. In the spirit of quantum routing we also show the reshaping of entanglement connections in small networks via linear optics operations based on numerical optimization.