Machine learning research findings could bolster quantum information transferNews
March 26, 2021
RESEARCH TRIANGLE PARK, N.C. According to the Army Research Lab, Army-funded researchers have demonstrated a machine learning approach that could correct quantum information in systems composed of photons, intended to improve the outlook for deploying quantum sensing and quantum communications technologies on the battlefield.
Researchers claim that 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 have exploited a type of machine learning to correct 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 could help correct distorted information.
For this research, the team claims it used a type of neural network to correct for distorted spatial modes of light at the single-photon level. According to the research team, this smart quantum technology demonstrates the possibility of encoding of multiple bits of information in a single photon in realistic communication protocols affected by environmental complications.