Work

Self-Configuring Quantum Networks with Superposition of Trajectories

Year: 2026

Type: article

Abstract: Quantum networks are a backbone of future quantum technologies thanks to their role in communication and scalable quantum computing. However, their performance is challenged by noise and decoherence. We propose a self-configuring approach that integrates superposed quantum paths with variational quantum optimization techniques. By estimating a cost function via repeated network uses, our approach dynamically optimizes the superposition of noisy paths across multiple nodes to establish high-fidelity connections between different parties. Our framework is in principle capable of adapting to unknown noise without assuming parametric noise models or performing full process tomography. We also discuss the role of vacuum coherence, a quantum effect central to path superposition that impacts protocol performance. Additionally, we demonstrate that our approach remains beneficial even in the presence of imperfections in the generation of path superposition.

Source: PRX Quantum

DOI: 10.1103/rj5x-yqsj

Authors: Albie Chan, Zheng Shi, Jorge Miguel-Ramiro, Luca Dellantonio, Christine A. Muschik, Wolfgang Dür

Institutions: University of Waterloo, University of Exeter, Perimeter Institute

Language: English

Topic: Quantum Information and Cryptography

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,450