Researchers from the Moscow Institute of Physics and Technology (MIPT) have begun developing a new generation of polaritonic nanolasers that could form the basis for a "photonic brain" — artificial neural networks operating at the speed of light. The project, supported by the Russian Science Foundation, combines plasmonic and polaritonic laser technologies, which will overcome the key limitations of modern nanophotonics.
Polaritonic lasers use exciton polaritons — hybrid quasiparticles that combine the properties of light and matter. Unlike conventional lasers, which require a lot of energy, polaritonic lasers operate on a principle similar to the behavior of atoms in superconductors, and therefore consume much less energy.
We face several tasks, including developing the technology for producing the first samples and creating a physical model of hybrid plasmon-exciton-polaritonic nanolasers. The main stages of work include achieving a strong coupling regime, demonstrating bosonic amplification of hybrid polariton scattering, and obtaining non-equilibrium bosonic condensates that emit coherent light. Two-dimensional semiconductors, monatomic layers of transition metal dichalcogenides, play a key role in achieving these goals. They provide a strong coupling mode of light with matter at room temperature, which is extremely important for applications in nanophotonics
A key element of the technology is two-dimensional transition metal dichalcogenides — materials one atom thick. They provide record-breaking indicators of the connection of light with matter, opening the way to creating compact photonic processors. According to scientists, such systems can demonstrate quantum effects, including superfluidity, which is critical for neuromorphic computing.
If the project is successful, Russia may take a leading position in the development of energy-efficient photonic processors, and will also create new prospects for conducting fundamental research in the field of polaritonics. This is especially important for AI tasks, where traditional electronic systems face limitations in speed and energy consumption.
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