Continuous-variable spatio-spectral quantum networks in nonlinear photonic lattices
Natalia Costas, Nadia Belabas, David Barral
TL;DR
This work addresses the scalability bottleneck of optical quantum networks by introducing continuous-variable entanglement generated through nondegenerate SPDC in a χ(2) nonlinear photonic lattice that encodes information in both spatial and spectral degrees of freedom. The authors develop a comprehensive framework, diagonalizing the low-gain SPDC dynamics across fixels, L-fixels, and N-fixels to produce broadband, distributable squeezed modes that form 2D spatio-spectral grid cluster states, representable by a complex-weighted adjacency matrix Z. Robustness to realistic losses is analyzed via nullifier variances and van Loock-Furusawa criteria, showing spectral entanglement remains tolerant to moderate loss while spatial entanglement is more fragile but can be mitigated with higher pump gain and media optimization. The results suggest practical routes to scalable quantum networks and measurement-based quantum computing using integrated photonics, with opportunities for phase-locked distribution, spectral demultiplexing, and pump-shaping-driven control of the generated graph states.
Abstract
Multiplexing information in different degrees of freedom and use of integrated and fiber-optic components are natural solutions to the scalability bottleneck in optical quantum communications and computing. However, for bulk-optics systems, where size, cost, stability, and reliability are factors, this remains either impractical or highly challenging to implement. In this paper we present a framework to engineer continuous-variable entanglement produced through nondegenerate spontaneous parametric down-conversion in χ^(2) nonlinear photonic lattices in spatial and spectral degrees of freedom that can solve the scalability challenge. We show how spatio-spectral pump shaping produce cluster states that are naturally distributable in quantum communication networks and a resource for measurement-based quantum computing.
