Photonic Computing

Photonic computing harnesses the speed and parallelism of light to accelerate computation, primarily targeting computationally intensive tasks like artificial intelligence and financial modeling. Current research emphasizes developing efficient photonic architectures for deep neural networks, exploring both analog and quantum approaches, with a focus on optimizing energy efficiency, precision, and scalability through techniques like sparsity, time multiplexing, and residue number systems. These advancements hold significant promise for improving the performance and energy efficiency of various applications, ranging from autonomous driving and defect detection to high-frequency trading and scientific simulations.