Pulse-Level Optimization of Parameterized Quantum Circuits for Variational Quantum Algorithms

Variational Quantum Algorithms (VQAs) have emerged as a powerful class of algorithms that is highly suitable for noisy quantum devices. Therefore, investigating their design has become key in quantum computing research. Previous works have shown that choosing an effective parameterized quantum circuit (PQC) or ansatz for VQAs is crucial to their overall performance, especially on near-term devices. In this paper, we utilize pulse-level access to quantum machines and our understanding of their two-qubit interactions to optimize the design of two-qubit entanglers in a manner suitable for VQAs. Our analysis results show that pulse-optimized ansatze reduce state preparation times by more than half, maintain expressibility relative to standard PQCs, and are more trainable through local cost function analysis. Our algorithm performance results show that in three cases, our PQC configuration outperforms the base implementation. Our algorithm performance results, executed on IBM Quantum hardware, demonstrate that our pulse-optimized PQC configurations are more capable of solving MaxCut and Chemistry problems compared to a standard configuration.