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Tulane part of Navy/Army-funded research on improving communication

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A team of Louisiana researchers, including a group from the Tulane University School of Science and Engineering, has developed a smart quantum technology that could have real-world applications to quantum networks and future quantum communications systems used in the military.
Ryan Glasser, an associate professor of physics at Tulane, and his team in the Department of Physics, collaborated on the study with researchers from Louisiana State University. The study was featured on the cover of the March 2021 issue of
“Recent developments in optical technologies have resulted in extremely high information transfer rates using the spatial properties of light — i.e. images (and more complex structured beams),” Glasser said. “However, a difficulty in such communications using light through free-space is that turbulence can severely distort the beams, resulting in errors in the communication.” 

Quantum breakthroughs help Army, Air Force advance supercomputing

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Quantum breakthroughs help Army, Air Force advance supercomputing
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Army-funded research has led to recent breakthroughs in quantum computing. Such advances could lead to supercomputers vital to future military operations. (Army photo)
As the Army builds its forces on the multi-domain operations concept for future warfighting, a core problem for today’s technologists is figuring out how to have a constant view of the battlefield and share that information across the globe.
Today’s computers simply can’t handle the immense amount of data and speed necessary for commanders and soldiers to gain a clear picture of their surroundings and the ability to use that information.

DVIDS - News - Machine learning shows potential to enhance quantum information transfer

RESEARCH TRIANGLE PARK, N.C. – Army-funded researchers demonstrated a machine learning approach that corrects quantum information in systems composed of photons, improving the outlook for deploying quantum sensing and quantum communications technologies on the battlefield.
When photons are used as the carriers of quantum information to transmit data, that information is often distorted due to environment fluctuations destroying the fragile quantum states necessary to preserve it.
Researchers from Louisiana State University exploited a type of machine learning to correct for information distortion in quantum systems composed of photons. Published in Advanced Quantum Technologies, the team demonstrated that machine learning techniques using the self-learning and self-evolving features of artificial neural networks can help correct distorted information. This results outperformed traditional protocols that rely on conventional adaptive optics.

Smart quantum technologies for secure communication

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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.

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