Spatial Mode Correction of Single Photons Using Machine Learning
Abstract
Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.
- Authors:
-
[1];
[2];
[1];
[2];
- Quantum Photonics Laboratory Department of Physics and Astronomy Louisiana State University Baton Rouge LA 70803 USA
- Tulane University New Orleans LA 70118 USA
- School of Information Science and Technology Qingdao University of Science and Technology Qingdao Shandong 260061 China
- Publication Date:
- Research Org.:
- Louisiana State Univ., Baton Rouge, LA (United States)
- Sponsoring Org.:
- USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division
- OSTI Identifier:
- 1761564
- Alternate Identifier(s):
- OSTI ID: 1786588; OSTI ID: 1830888
- Grant/Contract Number:
- DE‐SC0021069; SC0021069
- Resource Type:
- Published Article
- Journal Name:
- Advanced Quantum Technologies
- Additional Journal Information:
- Journal Name: Advanced Quantum Technologies Journal Volume: 4 Journal Issue: 3; Journal ID: ISSN 2511-9044
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- Germany
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; single-photon sources; networks; machine learning; optical communication; single-photon imaging; structured light; turbulence
Citation Formats
Bhusal, Narayan, Lohani, Sanjaya, You, Chenglong, Hong, Mingyuan, Fabre, Joshua, Zhao, Pengcheng, Knutson, Erin M., Glasser, Ryan T., and Magaña‐Loaiza, Omar S. Spatial Mode Correction of Single Photons Using Machine Learning. Germany: N. p., 2021.
Web. doi:10.1002/qute.202000103.
Bhusal, Narayan, Lohani, Sanjaya, You, Chenglong, Hong, Mingyuan, Fabre, Joshua, Zhao, Pengcheng, Knutson, Erin M., Glasser, Ryan T., & Magaña‐Loaiza, Omar S. Spatial Mode Correction of Single Photons Using Machine Learning. Germany. https://doi.org/10.1002/qute.202000103
Bhusal, Narayan, Lohani, Sanjaya, You, Chenglong, Hong, Mingyuan, Fabre, Joshua, Zhao, Pengcheng, Knutson, Erin M., Glasser, Ryan T., and Magaña‐Loaiza, Omar S. Fri .
"Spatial Mode Correction of Single Photons Using Machine Learning". Germany. https://doi.org/10.1002/qute.202000103.
@article{osti_1761564,
title = {Spatial Mode Correction of Single Photons Using Machine Learning},
author = {Bhusal, Narayan and Lohani, Sanjaya and You, Chenglong and Hong, Mingyuan and Fabre, Joshua and Zhao, Pengcheng and Knutson, Erin M. and Glasser, Ryan T. and Magaña‐Loaiza, Omar S.},
abstractNote = {Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.},
doi = {10.1002/qute.202000103},
journal = {Advanced Quantum Technologies},
number = 3,
volume = 4,
place = {Germany},
year = {Fri Jan 22 00:00:00 EST 2021},
month = {Fri Jan 22 00:00:00 EST 2021}
}
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