去k条边的降维完全二部图上的量子行走

Chen-Fu Chiang, Aaron Gregory
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引用次数: 1

摘要

由于当前量子技术的可扩展性问题,许多量子算法只能实现小尺寸问题。可扩展性仍然是当前量子技术的瓶颈。为了在短期内解决现实生活中的规模难题,我们探索了可以有效地减少到许多量子算法可实现规模的搜索图类。简化后的哈密顿量保留了原始哈密顿量的动力学性质。我们选择的一种简化哈密顿量的量子算法是连续时间量子行走(CTQW)。我们进一步展示了如何确定底层CTQW的耦合因子的正确值。如果耦合因子值不正确,可能会失去CTQW的最优性(二次加速)。在这项工作中,我们将可约图的类别扩展到随机移除$k$条边的完全二部图。通过数学证明和IBM Qiskit的仿真实验,进一步证明了CTQW保持了二次型加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum Walk on Dimensionality Reduced Complete Bipartite Graphs with k Edges Removed
Due to scalability issue in current quantum technologies, many quantum algorithms can only be implemented for small size problems. Scalability remains a bottleneck for current quantum technologies. For solving real-life size hard problems in the near-term, we explore classes of search graphs that can be efficiently reduced to a implementable scale for many quantum algorithms. The reduced Hamiltonian preserves the dynamics of the original Hamiltonian. One of the quantum algorithms we choose for the reduced Hamiltonian is continuous time quantum walk (CTQW). We further show how to determine the correct value of the coupling factor of the underlying CTQW. With wrong couple factor values, the optimality (quadratic speedup) from CTQW might be lost. In this work, we extend the class of reducible graphs to complete bipartite graphs with random $k$ edges removed. We further demonstrate through mathematical proof and simulation experiment using IBM Qiskit to show that the quadratic speed-up is preserved for the CTQW.
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