Quantum Natural Language Processing on Near-Term Quantum Computers

• URL: http://arxiv.org/abs/2005.04147v2
• Date: Mon, 6 Sep 2021 01:00:15 GMT
• Title: Quantum Natural Language Processing on Near-Term Quantum Computers
• Authors: Konstantinos Meichanetzidis (University of Oxford and Cambridge Quantum Computing Ltd.), Stefano Gogioso (Hashberg), Giovanni de Felice (University of Oxford and Cambridge Quantum Computing Ltd.), Nicol\`o Chiappori (Hashberg), Alexis Toumi (University of Oxford and Cambridge Quantum Computing Ltd.), Bob Coecke (University of Oxford and Cambridge Quantum Computing Ltd.)
• Abstract summary: We describe a full-stack pipeline for natural language processing on near-term quantum computers, aka QNLP. DisCoCat is a language-modelling framework that extends and complements the compositional structure of pregroup grammars. We present a method for mapping DisCoCat diagrams to quantum circuits.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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