Linear nearest neighbor optimization in quantum circuits: a multiobjective perspective
Linear nearest neighbor optimization in quantum circuits: a multiobjective perspective
复制标题
量子电路中的线性最近邻优化：多目标视角
DOI：
10.1007/s11128-017-1662-3
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发表时间：
2017
影响因子：
2.5
通讯作者：
B. Barán
中科院分区：
文献类型：
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作者：
Daniel Ruffinelli;B. Barán
量子电路的几个当前实现依赖于线性最近邻限制，其仅允许相邻量子位之间的相互作用。解决将通用电路转换为满足此限制的等效电路的过程的大多数方法使此过程所需的附加SWAP门的数量最小化。此外，解决这个问题的大多数方法都是针对1D电路设计的。考虑到2D量子电路的新的和有前途的建议，我们提出的是一个新的角度对这个问题，即它可以被看作是一个多目标优化问题。为了验证我们的假设，我们开发了一种多目标进化算法，通过考虑两个目标来解决这个问题：最小化电路放置的2D网格的大小，以及最小化额外SWAP门的数量。在为2D电路设计的方法中，只有一种方法考虑了比严格必要的大得多的不同网格尺寸。因此，我们的算法考虑了其他方法没有考虑的因素，因为它自然地找到了电路转换所需SWAP门较少的网格，无论是一维还是二维。我们的实验结果表明，允许一个更大的网格大小的结果在更少的额外交换门在约73%的测试电路。此外，我们发现使用较大网格尺寸时的平均改进约为30%，而使用尽可能小的网格时的最佳改进为63.8%。
Several current implementations of quantum circuits rely on the linear nearest neighbor restriction, which only allows interaction between adjacent qubits. Most methods that address the process of converting a generic circuit to an equivalent circuit which satisfies this restriction, minimize the number of additional SWAP gates required by this process. Moreover, most methods which address this problem are designed for 1D circuits. Considering the new and promising proposals for 2D quantum circuits, what we propose is a new perspective on this problem, namely that it can be seen as a multiobjective optimization problem. To test our hypothesis, we developed a multiobjective evolutionary algorithm that solves this problem by considering two objectives: minimizing the size of the 2D grid where the circuit is placed, and minimizing the number of additional SWAP gates. Of the methods designed for 2D circuits, only one considers different grid sizes which are much larger than strictly necessary. Consequently, our algorithm makes considerations which other methods do not make, since it naturally finds the grid which requires fewer SWAP gates for the circuit conversion, whether it is one-dimensional or two-dimensional. Our experimental results indicate that allowing a larger grid size results in fewer additional SWAP gates in about 73% of the tested circuits. Additionally, the average improvement we found when using larger grid sizes is about 30%, while the best improvement over using the smallest possible grid is 63.8%.
更改门顺序以实现最佳 LNN 转换
DOI：
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发表时间：
2011
期刊：
Proceedings of the 3rd Workshop on Reversible Computation
影响因子：
--
作者：
A. Matsuo;S. Yamashita
通讯作者：
S. Yamashita
线性最近邻体系结构上的量子傅立叶变换
DOI：
--
发表时间：
2007
期刊：
Quantum Information and Computation Vol.7 No.4
影响因子：
--
作者：
村山芳隆;小澤哲也;堀越直;薮上信;石山和志;荒井賢一;Yasuhiro Takahashi
通讯作者：
Yasuhiro Takahashi