QuaIL · Quantum Information Learning

Quantum Information Learning

Have you ever wondered how will space-faring humans make video calls with their friends on Earth, stream their favourite TV series or communicate important messages? Optical communications technology uses light propagating in free space and optical fiber to transmit data for telecommunications and networking. When the communication takes place over very long distances the light signals get extremely damped and the message they transmit becomes very difficult to read. Actually, the signals are so weak that the message cannot be read without errors, even when all the technical conditions are perfectly controlled and no external sources of noise are present. This is the realm where Quantum Physics enters the game: according to Heisenberg’s Uncertainty Principle, the position and velocity of a particle cannot be measured perfectly at the same time. The same principle applies to properties of the photons, when we use them to transfer a message over very long distances such as in optical-fiber, satellite or deep-space links. This inherent quantum noise constitutes a new challenge for the manipulation of information that cannot be solved with classical methods. Luckily, quantum physics also offers us new instruments to face this kind of challenges. The QuaIL project investigated how to build reliable quantum measurement devices, or decoders, that would allow us to increase current communication rates. These fundamentally deviate from classical measurement devices since they require to perform collective measurements of multiple signals at once. The project was based on the idea of combining basic building blocks of quantum optical circuits into a complex architecture, and optimize its structure with the help of machine-learning. The project implemented several algorithms for the optimization and control of quantum devices, applying them to the specific problem of finding an optical decoder capable of reading information written into optical coherent-state signals with minimum error. In particular, using reinforcement-learning methods, we implemented algorithms that were able to reach an exciting result: the calibration of an unknown quantum device by trial-and-error, based only on making an efficient use of limited communication experiments. Furthermore, we were able to discover decoders of medium-sized messages that increase up to 3 times the success rate with respect to single-signal receivers and are only 7%-away from the theoretically optimal decoder. Importantly, the decoders we found can be implemented with state-of-the-art optical technology. Finally, the project identified two communication settings of practical relevance where a quantum advantage can be guaranteed: communication in the absence of a phase reference; and communication with optical amplifiers, where we showed that up to 50% of the amplification energy cost can be spared by using a quantum optimal measurement. Being aware of the growing interest that the general public starts to have in quantum technologies, we also realized a popular science comic on the subject, with comic writer Martoz, titled “Erwyn and the photonic flea”.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз