论文标题
近期量子计算机上的量子自然语言处理
Quantum Natural Language Processing on Near-Term Quantum Computers
论文作者
论文摘要
在这项工作中，我们描述了近期量子计算机（aka QNLP）上自然语言处理的全栈管道。我们采用的语言模型框架是构图分布语义（DiscoCat），它扩展并补充了前组语法的组成结构。在此模型中，句子的语法减少被解释为图表，根据语法编码单词的特定相互作用。正是这种相互作用，再加上特定的单词嵌入方式，可以意识到句子的含义（或“语义”）。以这种相互作用的形式量子样性质为基础，我们提出了一种将圆顶图映射到量子电路的方法。我们的方法与NISQ设备以及既定的量子机学习技术都兼容，这为量子技术在自然语言处理中的近期应用铺平了道路。
In this work, we describe a full-stack pipeline for natural language processing on near-term quantum computers, aka QNLP. The language-modelling framework we employ is that of compositional distributional semantics (DisCoCat), which extends and complements the compositional structure of pregroup grammars. Within this model, the grammatical reduction of a sentence is interpreted as a diagram, encoding a specific interaction of words according to the grammar. It is this interaction which, together with a specific choice of word embedding, realises the meaning (or "semantics") of a sentence. Building on the formal quantum-like nature of such interactions, we present a method for mapping DisCoCat diagrams to quantum circuits. Our methodology is compatible both with NISQ devices and with established Quantum Machine Learning techniques, paving the way to near-term applications of quantum technology to natural language processing.
