Front Cover: Spatial Mode Correction of Single Photons Using Machine Learning (Adv. Quantum Technol. 3/2021). Issue 3 (15th March 2021)

• Record Type: Journal Article
• Authors: Bhusal, Narayan; Lohani, Sanjaya; You, Chenglong; Hong, Mingyuan; Fabre, Joshua; Zhao, Pengcheng; Knutson, Erin M.; Glasser, Ryan T.; Magaña‐Loaiza, Omar S.
• Is Part Of: Advanced quantum technologies. Volume 4:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-15
• Subjects: Quantum theory -- Periodicals; Quantum computing -- Periodicals; Quantum chemistry -- Periodicals; Quantum electronics -- Periodicals; 537.5
• DOI: 10.1002/qute.202170031
• Languages: English
• ISSNs: 2511-9044

Abstract

Abstract : Researchers from Louisiana introduce a smart quantum technology for the spatial mode correction of single photons. In article number 2000103, Narayan Bhusal, Chenglong You, and co‐workers exploit the self‐learning and self‐evolving features of artificial neural networks to correct the distorted spatial profile of single photons. The authors report a near‐unity fidelity in the correction of spatial modes of light. This technique boosts the channel capacity of optical communication protocols that rely on structured photons. This work has important implications for quantum technologies operating at the single‐photon level.