Self-Learning, Self-Evolving Smart Quantum Technologies for Secure Communication

Researchers from Louisiana State University have introduced a smart quantum technology for the spatial mode correction of single photons. In a paper featured on the cover of the March 2021 issue of Advanced Quantum Technologies, the authors exploit the self-learning and self-evolving features of artificial neural networks to correct the distorted spatial profile of single photons.

The authors, PhD candidate Narayan Bhusal, postdoctoral researcher Chenglong You, graduate student Mingyuan Hong, undergraduate student Joshua Fabre, and Assistant Professor Omar S. Magaña‐Loaiza of LSU—together with collaborators Sanjaya Lohani, Erin M. Knutson, and Ryan T. Glasser of Tulane University and Pengcheng Zhao of Qingdao University of Science and Technology—report on the potential of artificial intelligence to correct spatial modes at the single-photon level.

“The random phase distortion is one of the biggest challenges in using spatial modes of light in a wide variety of quantum technologies, such as quantum communication, quantum cryptography, and quantum sensing,” said Bhusal. “In this paper, we use artificial neurons to correct distorted spatial modes of light at the single-photon level. Our method is remarkably effective and time-efficient compared to conventional techniques. This is an exciting development for the future of free-space quantum technologies.”

The newly developed technique boosts the channel capacity of optical communication protocols that rely on structured photons.

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