Dynamic Circuit Automation for Efficient Quantum Computation

Dynamic circuits in quantum computing incorporate mid-circuit measurements and feed-forward operations, enabling real-time classical processing and conditional quantum operations based on measurement outcomes. Originally proposed for quantum error correction, dynamic circuits utilize syndrome measurements to detect and correct errors in real-time. Beyond error correction, dynamic circuits have numerous applications, such as reducing quantum resource overhead in algorithms like Quantum Fourier Transform (QFT) and Quantum Phase Estimation (QPE), and scaling up quantum computing by preparing quantum states across multiple quantum computers. However, these applications have typically relied on manually prepared dynamic circuits. We propose a comprehensive mathematical framework that automates the use of dynamic circuits to prepare arbitrary quantum states and implement unitary operations. We demonstrate our methods by preparing various quantum states and long-range entanglement gates, and scaling these techniques to large quantum circuits. We validate our approach through both simulation and experimental results on quantum hardware. The dynamic circuits generated by our framework show significant improvements in reducing circuit depth and, in some cases, the number of gates required. Our framework opens new possibilities for using dynamic circuits in general quantum circuit synthesis and highlights the potential of dynamic circuits to enhance the performance of quantum algorithms on near-term quantum computers.