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AUTOMATED OPTIMIZATION OF LARGE-SCALE QUANTUM CIRCUITS WITH CONTINUOUS PARAMETERS

机译:具有连续参数的大型量子电路的自动优化

摘要

The disclosure describes the implementation of automated techniques for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers. The disclosure shows how to handle continuous gate parameters and report a collection of fast algorithms capable of optimizing large-scale-scale quantum circuits. For the suite of benchmarks considered, the techniques described obtain substantial reductions in gate counts. In particular, the techniques in this disclosure provide better optimization in significantly less time than previous approaches, while making minimal structural changes so as to preserve the basic layout of the underlying quantum algorithms. The results provided by these techniques help bridge the gap between computations that can be run on existing quantum computing hardware and more advanced computations that are more challenging to implement in quantum computing hardware but are the ones that are expected to outperform what can be achieved with classical computers.
机译:本公开描述了用于优化尺寸的量子电路的自动化技术,以及在胜过经典计算机的量子计算中的尺寸和类型。本公开显示了如何处理连续栅极参数并报告能够优化大规模级量子电路的快速算法的集合。对于所考虑的基准套件,所描述的技术在栅极计数中获得了大量的减少。特别地,本公开中的技术在比以前的方法的时间内显着更少的时间提供更好的优化,同时制造最小的结构变化,以便保留底层量子算法的基本布局。这些技术提供的结果有助于弥合可以在现有量子计算硬件上运行的计算之间的差距以及更具高级计算,这些计算在量子计算硬件中实现更具挑战性,但是是预期胜过可以通过古典实现的所能实现的计算电脑。

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