Date: Tue, 16.03.21 23:30
Smart quantum technologies for secure co
March 16, 2021
Louisiana State University
Researchers have introduced a smart quantum technology for the
spatial mode correction of single photons. The authors exploit
the self-learning and self-evolving features of artificial neural
networks to correct the distorted spatial profile of single photons.
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. Magan~a?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
"One important goal of the Quantum Photonics Group at LSU is to develop
robust quantum technologies that work under realistic conditions,"
said Magan~a?Loaiza. "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." "We are still in the fairly early
stages of understanding the potential for machine learning techniques
to play a role in quantum information science," said Dr. Sara Gamble,
program manager at the Army Research Office, an element of DEVCOM
ARL. "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."
Story Source: Materials provided by Louisiana_State_University. Note:
Content may be edited for style and length.
1. Narayan Bhusal, Sanjaya Lohani, Chenglong You, Mingyuan Hong, Joshua
Fabre, Pengcheng Zhao, Erin M. Knutson, Ryan T. Glasser, Omar S.
Magan~a‐Loaiza. Spatial Mode Correction of Single Photons
Using Machine Learning. Advanced Quantum Technologies, 2021; 4
(3): 2000103 DOI: 10.1002/qute.202000103
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