The problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilationtask, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to the MaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOA for Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we apply a planning approach to qubit initialization. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds, and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring. These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.

中文翻译：

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规划用于图着色的量子算法的编译

编译通用量子算法以在近期量子处理器上实现的问题已被引入 AI 社区。先前的工作表明，时间规划是该编译任务的一部分的有吸引力的方法，特别是实现应用于量子处理器架构上 MaxCut 问题的量子交替算子 Ansatz (QAOA) 的电路路由。在本文中，我们将早期工作扩展到为图形着色问题实现 QAOA 的路由电路。用于着色的 QAOA 需要在芯片上执行更多、更复杂的操作，这使得路由成为一个更具挑战性的问题。我们评估了来自领先量子计算公司的最先进硬件架构的方法。此外，我们将规划方法应用于量子位初始化。我们的经验评估表明，时间规划与合理的分析上限相比很好，并且使用经典规划器解决量子位初始化通常有助于时间规划者为图着色的 QAOA 寻找更短的编译期。这些进展表明，时间规划可以成为更复杂的量子计算算法和架构的有效方法。