Optimizing Quantum Circuit Architecture with Graph-Based Bayesian Optimization

This ArXiv article presents a novel approach to optimizing quantum circuit architectures using a graph-based Bayesian optimization technique. The use of uncertainty-calibrated surrogates further enhances the model's reliability and performance in the optimization process.

• •Applies graph-based Bayesian optimization to quantum circuit architecture design.
• •Employs uncertainty-calibrated surrogates for improved model reliability.
• •The research aims to enhance the performance of quantum circuit design through automated optimization.