The project

Microscale optical resonators are devices which efficiently confine photons long enough to interact strongly with embedded matter such as semiconductor quantum wells. The electronic excitations within absorb and reemit the confined photons at such high rates that a new mixture of light and matter emerges known as exciton-polaritons. These emergent bosonic light-matter quasiparticles can form macroscopic quantum fluids, sometimes referred as “liquid light” or “polariton Bose-Einstein condensates”, at elevated temperatures. Polariton condensates have numerous exotic properties not found in many other condensed matter systems such as superfluidity, quantized vorticity, ultralow threshold lasing, spontaneous synchronization like in Huygens’ clocks experiment, and self-organized behaviours through their nontrivial dynamics.

Motivated by recent advancements in material design and patterned light sources to generate coherent large-scale polariton networks, we aim to design novel and necessary theoretical frameworks to underpin the quality of polariton networks as platforms for reprogrammable analogue many-body simulation and unconventional neural-inspired optical computation. Theoretical outcomes are communicated to partner laboratories who will help demonstrate proof of concept, unleashing the potential disruptive performance of this new highly nonlinear technological platform in the strong light-matter coupling regime. Application of reprogrammable ultralow threshold coherent polariton networks, integrated on-chip, touches upon topological lasers, subpicosecond optical spin switches, simulating extreme many-body systems to generate new scholarly knowledge, optimization of complex energy functions, and task-specific optical neuromorphic computation which could help solve pressing problems requiring on-the-fly optimization with impact on material synthesis, drug design, financial prediction, logistics, and much more.

 Supported by the National Science Center of Poland under the project  2022/45/P/ST3/00467 co-funded by the European Union Framework Programme for Research and Innovation Horizon 2020 under the Marie Skłodowska-Curie grant agreement No. 945339.