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Quantum transport of high-dimensional spatial information with a nonlinear detector
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Journal Article
Quantum transport of high-dimensional spatial information with a nonlinear detector
2023
Overview
Information exchange between two distant parties, where information is shared without physically transporting it, is a crucial resource in future quantum networks. Doing so with high-dimensional states offers the promise of higher information capacity and improved resilience to noise, but progress to date has been limited. Here we demonstrate how a nonlinear parametric process allows for arbitrary high-dimensional state projections in the spatial degree of freedom, where a strong coherent field enhances the probability of the process. This allows us to experimentally realise quantum transport of high-dimensional spatial information facilitated by a quantum channel with a single entangled pair and a nonlinear spatial mode detector. Using sum frequency generation we upconvert one of the photons from an entangled pair resulting in high-dimensional spatial information transported to the other. We realise a
d
= 15 quantum channel for arbitrary photonic spatial modes which we demonstrate by faithfully transferring information encoded into orbital angular momentum, Hermite-Gaussian and arbitrary spatial mode superpositions, without requiring knowledge of the state to be sent. Our demonstration merges the nascent fields of nonlinear control of structured light with quantum processes, offering a new approach to harnessing high-dimensional quantum states, and may be extended to other degrees of freedom too.
High-dimensional quantum states allow for several advantages in quantum communication, but protocols such as teleportation require additional entangled photons as the dimension increases. Here, the authors show how to transport a high-dimensional quantum state from a bright coherent laser field to a single photon, using two entangled photons as the quantum channel.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
