论文标题
通过单量门近似较短的量子电路
Shorter quantum circuits via single-qubit gate approximation
论文作者
论文摘要
我们提供了一个新的程序,可以通过将问题减少到新的幅度近似问题来近似从有限的通用门近似一般的单量单位,从而使序列长度立即提高了7/9。扩展了Arxiv的作品:1612.01011和Arxiv:1612.02689,我们表明,将通道的概率混合物求解以求解后备(ARXIV:1409.3552),幅度近似问题可节省两个因子的因子。特别是,在Clifford+$ \ sqrt {\ Mathrm {t}} $ GATE集合中,我们达到了平均非clifford门计数$ 0.23 \ log_2(1/\ varepsilon)+2.13 $和T-count and t-count $ 0.56 $ 0.56 $ \ varepsilon $。 本文除了这些新见解外,还提供了门近似的整体概述。我们给出了与某些五季度代数相关的一般门集的门近似程序的端到端过程,使用常见的容忍故障的门集(V,Clifford+T和Clifford+T和Clifford+$ \ sqrt {\ Mathrm {t}}} $)提供教学示例(V,Clifford+T和Clifford+T和Clifford+$ \ sqrt {我们还为Clifford+T和Clifford+$ \ sqrt {\ Mathrm {t}} $ GATE SETS提供了详细的数值结果。为了保持纸张独立,我们概述了整数枚举和相对规范方程式解决方案的相关算法。我们在附录中提供了幅度近似问题的许多进一步应用,以及改进的精确合成算法。
We give a novel procedure for approximating general single-qubit unitaries from a finite universal gate set by reducing the problem to a novel magnitude approximation problem, achieving an immediate improvement in sequence length by a factor of 7/9. Extending the works arXiv:1612.01011 and arXiv:1612.02689, we show that taking probabilistic mixtures of channels to solve fallback (arXiv:1409.3552) and magnitude approximation problems saves factor of two in approximation costs. In particular, over the Clifford+$\sqrt{\mathrm{T}}$ gate set we achieve an average non-Clifford gate count of $0.23\log_2(1/\varepsilon)+2.13$ and T-count $0.56\log_2(1/\varepsilon)+5.3$ with mixed fallback approximations for diamond norm accuracy $\varepsilon$. This paper provides a holistic overview of gate approximation, in addition to these new insights. We give an end-to-end procedure for gate approximation for general gate sets related to some quaternion algebras, providing pedagogical examples using common fault-tolerant gate sets (V, Clifford+T and Clifford+$\sqrt{\mathrm{T}}$). We also provide detailed numerical results for Clifford+T and Clifford+$\sqrt{\mathrm{T}}$ gate sets. In an effort to keep the paper self-contained, we include an overview of the relevant algorithms for integer point enumeration and relative norm equation solving. We provide a number of further applications of the magnitude approximation problems, as well as improved algorithms for exact synthesis, in the Appendices.