Introduction of self-learning and self-evolving intelligent quantum technology
In the “Advanced Quantum Technology” journal issued in March 2021, the research team at Louisiana State University (LSU) has just introduced an intelligent quantum technology for “single-photon spatial mode correction”. The co-authors of the research also include Sanjaya Lohani, Erin M. Knutson, Ryan T. Glasser of Tulane University, and Pengcheng Zhao of Qingdao University of Science and Technology, who have jointly demonstrated the great potential of artificial intelligence in single-photon spatial pattern correction.
Research Picture-1: Schematic diagram of the device used to demonstrate turbulence correction
In addition, this research has also gathered the joint efforts of LSU PhD student Narayan Bhusal, postdoctoral researcher Chenglong You, graduate student Mingyuan Hong, undergraduate student Joshua Fabre, assistant professor Omar S. Magaña-Loaiza and others.
Narayan Bhusal said: Random phase distortion is a major challenge that a variety of quantum technologies (such as quantum communication, quantum cryptography, quantum sensing, etc.) use optical space modes must face.
Research Picture-2: Spatial distribution of LG modes of high-photon and single-photon energy levels under different turbulences
However, in this new study, they used artificial intelligence technology to correct the photon-level distortion and spatial light patterns. Compared with traditional technology, the new solution is more efficient and time-saving.
Based on this, the new technology has increased the channel capacity of optical communication protocols that rely on structured photons, laying an exciting foundation for the future development of free space quantum technology.
Magaña-Loaiza added: An important goal of the LSU quantum photonics research team is to develop powerful quantum technologies that can operate under realistic conditions.
This intelligent quantum technology proves the possibility of encoding multi-bit information in a single photon in a realistic communication protocol affected by atmospheric turbulence, and has a huge impact on the future development of optical communication and quantum cryptography.
They are currently exploring ways to deploy new machine learning solutions in the state’s Optical Network Initiative (NONI) to make them more intelligent, secure and quantized.
In addition, the US Army Research Office is supporting a research project called “Quantum Sensing, Imaging, and Metrology Using Multiple Orbital Angular Momentum”.
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