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Summary
The paper presents a method for optimizing quantum circuit compilation by automating the allocation of auxiliary qubits for multi-qubit gate decompositions. This approach is implemented in the Ket high-level quantum programming platform and evaluated against Qiskit, a widely used quantum programming platform.
Highlights
- Automated auxiliary qubit allocation reduces the number of CNOT gates in compiled circuits.
- Ket's high-level quantum programming constructs enable more efficient programs.
- The approach is evaluated using Grover's algorithm and a state preparation algorithm.
- Ket achieves a quadratic reduction in CNOT gates compared to Qiskit.
- The allocation algorithm minimizes new interactions between qubits.
- The approach is not limited to specific decomposition algorithms.
- Ket's performance improvement is significant, especially for larger inputs.
Key Insights
- Automating auxiliary qubit allocation is crucial for optimizing quantum circuit compilation, as it reduces the number of CNOT gates and overall circuit depth.
- High-level quantum programming constructs, such as those provided by Ket, can significantly enhance the efficiency of quantum programs by minimizing the number of gates required.
- The choice of decomposition algorithm has a substantial impact on the performance of quantum circuits, and Ket's approach allows for the selection of the most efficient algorithm based on the available auxiliary qubits.
- The allocation algorithm's ability to minimize new interactions between qubits is essential for reducing the number of SWAP operations required during circuit mapping.
- Ket's performance improvement over Qiskit is substantial, especially for larger inputs, demonstrating the effectiveness of the automated auxiliary qubit allocation approach.
- The approach is flexible and can be adapted to different decomposition algorithms, making it a valuable contribution to the field of quantum computing.
- The results of this study highlight the importance of optimizing quantum circuit compilation for the development of efficient quantum algorithms and applications.
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Citation
Rosa, E. C. R., Marchi, J., Duzzioni, E. I., & de Santiago, R. (2024). Automated Auxiliary Qubit Allocation in High-Level Quantum Programming (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.20543