Order of optimization steps affects quality of quantum circuits
Evaluating the Effect of the Order of Optimization Passes in Quantum Circuit Optimization
Emerging TechnologiesPerformance
Summary
Quantum computers use circuits made of commands to do calculations, but these can be noisy and slow. The authors studied how the order of improving these circuits matters. They found that the sequence in which optimization routines are applied changes how well the circuits perform. Sometimes repeating certain steps fixes initial problems caused by a bad order. The best sequence often depends on the basic commands the quantum machine understands.
What this means in practice
- •For quantum software engineers: Optimize the sequence of compiler passes to reduce errors and improve performance of quantum circuits for specific hardware gate sets.
- •For quantum hardware teams: Tailor quantum circuit optimization sequences to the native gate sets of devices to maximize circuit quality and minimize noise impacts.
Authors
Xiao-Ting Michelle To, Nils Quetschlich, Amr Elsharkawy, Martin Schulz, Robert Wille, Dieter Kranzlmüller
Abstract
Quantum circuit optimization is critical for mitigating the noise inherent in current quantum hardware. Quantum compilers typically sequentially apply multiple optimizations (also called ``optimization passes'') to improve the circuit. The impact of the order in which these passes are executed has yet been largely unexplored. This paper investigates the significance of the order of optimization passes within quantum circuit compilation, specifically analyzing interactions between different optimization methods and quantifying their mutual influences. Using Qiskit's compiler, we systematically evaluate pairwise combinations of 16 selected optimization passes, measuring circuit depth and gate count across various benchmark circuits. Our findings indicate dependencies between certain optimization passes, demonstrating that the order of the passes affects the optimization quality. In some cases, the worse performing sequence can be corrected through repeated pass application. %such that they are as good as the best performing one by extending the sequence. Experiments on multi-pass sequences show that more than two optimization passes may have an impact on each other but that this always links to the previously found pairwise effects. We observe that it is important to initially choose the best order of optimization passes to get the best possible optimization for the given circuit. The experiments reveal some factors which are important to choose the best, or at least a good, order; among those, the resulting optimization sequence depends the most on the native gate set.