Spatial modes of light constitute valuable resources for various quantum technologies ranging from quantum communication and quantum imaging to remote sensing. In any case, their vulnerabilities to phase distortions, prompted by random media, impose significant limitations on the realistic implementation of various quantum‐photonic technologies.
Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, scientists have solved this problem through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics.
In a new study, scientists from Louisiana State University have introduced a smart quantum technology for single photons’ spatial mode correction. They used self-learning and self-evolving features of artificial neural networks to correct the distorted spatial profile of single photons.
Ph.D. candidate Narayan Bhusal said, “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 technique boosts the channel capacity of optical communication protocols that rely on structured photons.”
Assistant Professor Omar S. Magaña-Loaiza of LSU said, “One important goal of the Quantum Photonics Group at LSU is to develop robust quantum technologies that work under realistic conditions. This smart quantum technology demonstrates the possibility of encoding multiple bits of information in a single photon in realistic communication protocols affected by atmospheric turbulence. Our technique has enormous implications for optical communication and quantum cryptography. We are now exploring paths to implement our machine learning scheme in the Louisiana Optical Network Initiative (LONI) to make it smart, secure, and quantum.”
Dr. Sara Gamble, program manager at the Army Research Office, an element of DEVCOM ARL, said, “We are still in the fairly early stages of understanding the potential for machine learning techniques to play a role in quantum information science. The team’s result is an exciting step forward in developing this understanding, and it has the potential to ultimately enhance the Army’s sensing and communication capabilities on the battlefield.”
Journal Reference:
- Narayan Bhusal et al., Spatial Mode Correction of Single Photons Using Machine Learning, Advanced Quantum Technologies (2021). DOI: 10.1002/qute.202000103
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