Prof.
Michał
Matuszewski
Institute of Physics PAS
Photonic information processing benefits from high speed, parallelization, low communication losses, and high bandwidth. We recently demonstrated hardware neural network systems where strong optical nonlinearity results solely from interactions of exciton-polaritons, quantum superpositions of light and matter. Such superpositions, in the form of mixed quasiparticles of photons and excitons, are characterized by excellent photon-mediated transport properties and strong exciton-mediated interactions. These semiconductor microcavity systems can be used to construct fully all-optical neural networks characterized by extremely high energy efficiency. We show why using polaritonics in place of standard nonlinear optical phenomena, can be the key to achieving such a performance.
The talk will be given in room D.
The meeting will be also accessible online via Zoom.
