Unlocking the Benefits of Dynamic Quantum Circuits in Resource Constraint Architecture

The execution of large-scale quantum algorithms is currently constrained by the limited number of available qubits, qubit connectivity restrictions, and the inherent noise in quantum processors. To address these limitations, a design methodology known as Dynamic Quantum Circuits (DQC) has emerged. DQC leverages non-unitary operations-such as active reset, midcircuit measurement, and classically controlled gate operationsto reduce qubit requirements during circuit design. Recently, DQC-based implementations have been explored for various algorithms, including Shor’s Prime Factorization, Quantum Phase Estimation (QPE), and Bernstein-Vazirani (BV), as well as for key operations like state preparation, Toffoli networks, and nonlocal gates. While DQC offers a significant reduction in qubit usage, it introduces a trade-off in the form of increased circuit depth. Therefore, assessing the reliability of such circuits becomes crucial in the context of current quantum hardware architectures. In this paper, we analyze the reliability of DQC-based quantum circuit realizations as a function of qubit count and circuit depth. We present empirical results for two algorithms and evaluate how architectural parameters impact their reliability.