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Quantum Optimization for the Graph Coloring Problem with Space-Efficient Embedding

机译:空间高效嵌入的图着色问题的量子优化

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Current quantum computing devices have different strengths and weaknesses depending on their architectures. This means that flexible approaches to circuit design are necessary. We address this task by introducing a novel space-efficient quantum optimization algorithm for the graph coloring problem. Our circuits are deeper than the ones of the standard approach. However, the number of required qubits is exponentially reduced in the number of colors. We present extensive numerical simulations demonstrating the performance of our approach. Furthermore, to explore currently available alternatives, we also perform a study of random graph coloring on a quantum annealer to test the limiting factors of that approach, too.
机译:当前的量子计算设备根据其架构而具有不同的优点和缺点。这意味着必须采用灵活的电路设计方法。我们通过为图形着色问题引入新颖的空间高效量子优化算法来解决此任务。我们的电路比标准方法的电路更深。但是,所需的量子位的数量在颜色数量上成倍减少。我们提供了广泛的数值模拟,证明了我们方法的性能。此外,为了探索当前可用的替代方法,我们还对量子退火炉上的随机图形着色进行了研究,以测试该方法的局限性。

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