论文标题
自然语言处理的混合古典量子工作流程
A hybrid classical-quantum workflow for natural language processing
论文作者
论文摘要
自然语言处理（NLP）问题在古典计算中无处不在，在这些计算中，它们通常需要大量的计算资源来推断句子含义。随着量子计算硬件和模拟器的出现，值得开发在这些平台上检查此类问题的方法。在本手稿中，我们演示了使用量子计算模型执行NLP任务的使用，在该任务中，我们表示语料库含义，并在给定结构的句子之间进行比较。我们开发了一个混合工作流程，用于表示要使用量子电路模型编码，处理和解码的小规模语料库数据集。此外，我们还提供了显示该方法功效的结果，并将开发的工具包释放为开放软件套件。
Natural language processing (NLP) problems are ubiquitous in classical computing, where they often require significant computational resources to infer sentence meanings. With the appearance of quantum computing hardware and simulators, it is worth developing methods to examine such problems on these platforms. In this manuscript we demonstrate the use of quantum computing models to perform NLP tasks, where we represent corpus meanings, and perform comparisons between sentences of a given structure. We develop a hybrid workflow for representing small and large scale corpus data sets to be encoded, processed, and decoded using a quantum circuit model. In addition, we provide our results showing the efficacy of the method, and release our developed toolkit as an open software suite.
