A research team at Chalmers University of Technology in Sweden has successfully developed a digital "super brain"—a neural network model that integrates physical laws, essentially enabling it to "grasp the principles of physics." This innovative model slashes the training time for screening nano-optical materials to just one-tenth of that required by traditional AI methods. It not only significantly boosts prediction accuracy but also minimizes errors. The key breakthrough of this model is the incorporation of the laws of physics and electromagnetism into the neural network, allowing it to utilize existing knowledge for learning, rather than solely depending on data to discern patterns.

Tests have demonstrated that the time needed for data generation and model training has been drastically reduced from 30 days to a mere 3 days. The trained model is capable of predicting the optical properties of nanostructures in milliseconds, thereby expediting technological research and development in areas such as quantum computing and advanced optical devices. The related research findings have been published in the esteemed journal Laser & Photonics Reviews.