The Need
Current quantum computing technologies face significant challenges in scalability, error correction, and computational efficiency. There is a critical need for a robust, scalable quantum processor that can perform complex computations with high fidelity and low error rates, enabling advancements in various industries such as chemistry, physics, and artificial intelligence.

The Technology
OSU researchers have developed a recurrent quantum photonic processor (QPP) that utilizes squeezed photon states generated through spontaneous four-wave mixing in silicon nitride microring resonators. This processor employs programmable linear-optic logic for error correction and performs unitary transformations, enabling efficient quantum computations with high fidelity and reduced error rates.

Commercial Applications
• Quantum computing for complex problem solving in chemistry and physics.
• Advanced machine learning and artificial intelligence algorithms.
• High-precision simulations of molecular dynamics and protein folding.
• Efficient matrix-vector multiplications for neural network training.
• Modeling of complex dynamical systems through quantum walks.

Benefits/Advantages
• Scalable architecture allowing for large-scale quantum circuits.
• High fidelity and low error rates through effective error correction.
• Reduced computational complexity from O(N2.37) to O(N).
• Compatibility with existing silicon-on-insulator processes.
• Enhanced optical sensitivity below the standard quantum limit

Patent application filed