Quantum circuit synthesis with diffusion models | Gorka Muñoz Gil | QML CVC webinar

In this talk, I will show how to use generative denoising diffusion models (DMs) to produce desired quantum operations within gate-based quantum circuits, based on some input text defining the goal operation. DMs allow to sidestep during training the exponential overhead inherent in the classical simulation of quantum dynamics, a consistent bottleneck in preceding ML techniques. We demonstrate the model's capabilities across two tasks: entanglement generation and unitary compilation. The model excels at generating new circuits and supports typical DM extensions such as masking and editing to, for instance, align the circuit generation to the constraints of the targeted quantum device. Given their flexibility and generalization abilities, we envision DMs as pivotal in quantum circuit synthesis, enhancing both practical applications but also insights into theoretical quantum computation.