论文标题

嘈杂的中间量子时代及以后的混合量子古典算法

Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond

论文作者

Callison, Adam, Chancellor, Nicholas

论文摘要

混合量子古典算法对于量子计算中当前的许多研究都是至关重要的,尤其是在考虑嘈杂的中间量子量子(NISQ)时代时,已经进行了许多实验演示。从这个角度来看,我们从很广泛的意义上讨论算法是混合量子古典的含义。我们首先通过基于抽象/表示理论的先前工作来构建定义,首先探讨了这个概念,认为使算法混合动力的原因不是直接运行的方式(或它消耗了多少古典资源),而是对计算的基本模型至关重要的。然后,我们对这个问题进行更广泛的看法,回顾了许多混合算法,并讨论了它们使它们混合的原因,以及它们出现的历史以及与硬件有关的考虑。这导致了对这些算法的未来的自然讨论。为了回答这个问题,我们转向在古典计算中使用专业处理器。古典趋势不是要完全替代旧技术,而是要增加旧技术。我们认为,量子计算的演变不太可能是不同的:混合算法可能在这里可能会超越NISQ时代,甚至进入完全耐受性,而量子处理器可以通过执行专业任务来增强已经强大的经典处理器。

Hybrid quantum-classical algorithms are central to much of the current research in quantum computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era, with a number of experimental demonstrations having already been performed. In this perspective, we discuss in a very broad sense what it means for an algorithm to be hybrid quantum-classical. We first explore this concept very directly, by building a definition based on previous work in abstraction/representation theory, arguing that what makes an algorithm hybrid is not directly how it is run (or how many classical resources it consumes), but whether classical components are crucial to an underlying model of the computation. We then take a broader view of this question, reviewing a number of hybrid algorithms and discussing what makes them hybrid, as well as the history of how they emerged, and considerations related to hardware. This leads into a natural discussion of what the future holds for these algorithms. To answer this question, we turn to the use of specialized processors in classical computing.The classical trend is not for new technology to completely replace the old, but to augment it. We argue that the evolution of quantum computing is unlikely to be different: hybrid algorithms are likely here to stay well past the NISQ era and even into full fault-tolerance, with the quantum processors augmenting the already powerful classical processors which exist by performing specialized tasks.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源