2021-04-06

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security

By yqqlm yqqlm

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security

Research Picture-1: Used to demonstrate turbulence correction Schematic diagram of the device

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.) used in optical space modes must face.

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security(1)

Research Picture-2: Different Spatial distribution of high-photon and single-photon energy level LG modes under turbulence

However, in this new study, they used artificial intelligence technology to correct the photon-level distortion and spatial light mode. Compared with traditional technology, the new solution is more efficient and time-saving.

Based on this, the new technology increases 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.

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security(2)

Research Picture-3: Mean Square Error (MSE) Correspondence with GDO iteration number

Magaña-Loaiza added: An important goal of the LSU quantum photonics research team is to develop a powerful quantum technology 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, which is important for the future development of optical communication and quantum cryptography. Has a huge impact.

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security(3)

Research Picture-4: In Conditional probability/cross-correlation matrix of transmission/detection mode based on OAM

Currently, they are exploring ways to deploy new machine learning solutions in the state’s Optical Network Initiative (NONI) to make it Be smarter, safer and quantized.

In addition, the U.S. Army Research Office is supporting a research project called “Quantum Sensing, Imaging, and Metrology Using Multiple Orbital Angular Momentum”.

Researchers use self-learning and self-evolving intelligent quantum technology to ensure communication security(4)

Research Picture-5: Based on Real and imaginary density matrix of OAM-encoded qubits